Last updated: July 22, 2025
Expected numbers in use count data quality checks, SQL examples
A column-level check that counts unique values in a numeric column and counts how many values out of a list of expected numeric values were found in the column. The check raises a data quality issue when the threshold for the maximum number of missing has been exceeded (too many expected values were not found in the column). This check is useful for analysing columns with a low number of unique values, such as status codes, to detect whether all status codes are used in any row.
The expected numbers in use count data quality check has the following variants for each type of data quality checks supported by DQOps.
profile expected numbers in use count
Check description
Verifies that the expected numeric values were found in the column. Raises a data quality issue when too many expected values were not found (were missing).
Data quality check name | Friendly name | Category | Check type | Time scale | Quality dimension | Sensor definition | Quality rule | Standard |
---|---|---|---|---|---|---|---|---|
profile_expected_numbers_in_use_count |
Maximum number of expected numeric values that are not in use | accepted_values | profiling | Reasonableness | expected_numbers_in_use_count | max_missing |
Command-line examples
Please expand the section below to see the DQOps command-line examples to run or activate the profile expected numbers in use count data quality check.
Managing profile expected numbers in use count check from DQOps shell
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the warning rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=profile_expected_numbers_in_use_count --enable-warning
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=profile_expected_numbers_in_use_count --enable-warning
Additional rule parameters are passed using the -Wrule_parameter_name=value.
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the error rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=profile_expected_numbers_in_use_count --enable-error
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=profile_expected_numbers_in_use_count --enable-error
Additional rule parameters are passed using the -Erule_parameter_name=value.
Run this data quality check using the check run CLI command by providing the check name and all other targeting filters. The following example shows how to run the profile_expected_numbers_in_use_count check on all tables and columns on a single data source.
It is also possible to run this check on a specific connection and table. In order to do this, use the connection name and the full table name parameters.
dqo> check run -c=connection_name -t=schema_name.table_name -ch=profile_expected_numbers_in_use_count
You can also run this check on all tables (and columns) on which the profile_expected_numbers_in_use_count check is enabled using patterns to find tables.
YAML configuration
The sample schema_name.table_name.dqotable.yaml file with the check configured is shown below.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
columns:
target_column:
profiling_checks:
accepted_values:
profile_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
Samples of generated SQL queries for each data source type
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count data quality sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Expand the Configure with data grouping section to see additional examples for configuring this data quality checks to use data grouping (GROUP BY).
Configuration with data grouping
Sample configuration with data grouping enabled (YAML) The sample below shows how to configure the data grouping and how it affects the generated SQL query.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
default_grouping_name: group_by_country_and_state
groupings:
group_by_country_and_state:
level_1:
source: column_value
column: country
level_2:
source: column_value
column: state
columns:
target_column:
profiling_checks:
accepted_values:
profile_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
country:
labels:
- column used as the first grouping key
state:
labels:
- column used as the second grouping key
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.[country] AS grouping_level_1,
analyzed_table.[state] AS grouping_level_2
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY analyzed_table.[country], analyzed_table.[state]
ORDER BY level_1, level_2
,
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
daily expected numbers in use count
Check description
Verifies that the expected numeric values were found in the column. Raises a data quality issue when too many expected values were not found (were missing). Stores the most recent captured value for each day when the data quality check was evaluated.
Data quality check name | Friendly name | Category | Check type | Time scale | Quality dimension | Sensor definition | Quality rule | Standard |
---|---|---|---|---|---|---|---|---|
daily_expected_numbers_in_use_count |
Maximum number of expected numeric values that are not in use | accepted_values | monitoring | daily | Reasonableness | expected_numbers_in_use_count | max_missing |
Command-line examples
Please expand the section below to see the DQOps command-line examples to run or activate the daily expected numbers in use count data quality check.
Managing daily expected numbers in use count check from DQOps shell
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the warning rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=daily_expected_numbers_in_use_count --enable-warning
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=daily_expected_numbers_in_use_count --enable-warning
Additional rule parameters are passed using the -Wrule_parameter_name=value.
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the error rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=daily_expected_numbers_in_use_count --enable-error
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=daily_expected_numbers_in_use_count --enable-error
Additional rule parameters are passed using the -Erule_parameter_name=value.
Run this data quality check using the check run CLI command by providing the check name and all other targeting filters. The following example shows how to run the daily_expected_numbers_in_use_count check on all tables and columns on a single data source.
It is also possible to run this check on a specific connection and table. In order to do this, use the connection name and the full table name parameters.
You can also run this check on all tables (and columns) on which the daily_expected_numbers_in_use_count check is enabled using patterns to find tables.
YAML configuration
The sample schema_name.table_name.dqotable.yaml file with the check configured is shown below.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
columns:
target_column:
monitoring_checks:
daily:
accepted_values:
daily_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
Samples of generated SQL queries for each data source type
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count data quality sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Expand the Configure with data grouping section to see additional examples for configuring this data quality checks to use data grouping (GROUP BY).
Configuration with data grouping
Sample configuration with data grouping enabled (YAML) The sample below shows how to configure the data grouping and how it affects the generated SQL query.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
default_grouping_name: group_by_country_and_state
groupings:
group_by_country_and_state:
level_1:
source: column_value
column: country
level_2:
source: column_value
column: state
columns:
target_column:
monitoring_checks:
daily:
accepted_values:
daily_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
country:
labels:
- column used as the first grouping key
state:
labels:
- column used as the second grouping key
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.[country] AS grouping_level_1,
analyzed_table.[state] AS grouping_level_2
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY analyzed_table.[country], analyzed_table.[state]
ORDER BY level_1, level_2
,
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
monthly expected numbers in use count
Check description
Verifies that the expected numeric values were found in the column. Raises a data quality issue when too many expected values were not found (were missing). Stores the most recent captured value for each month when the data quality check was evaluated.
Data quality check name | Friendly name | Category | Check type | Time scale | Quality dimension | Sensor definition | Quality rule | Standard |
---|---|---|---|---|---|---|---|---|
monthly_expected_numbers_in_use_count |
Maximum number of expected numeric values that are not in use | accepted_values | monitoring | monthly | Reasonableness | expected_numbers_in_use_count | max_missing |
Command-line examples
Please expand the section below to see the DQOps command-line examples to run or activate the monthly expected numbers in use count data quality check.
Managing monthly expected numbers in use count check from DQOps shell
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the warning rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=monthly_expected_numbers_in_use_count --enable-warning
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=monthly_expected_numbers_in_use_count --enable-warning
Additional rule parameters are passed using the -Wrule_parameter_name=value.
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the error rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=monthly_expected_numbers_in_use_count --enable-error
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=monthly_expected_numbers_in_use_count --enable-error
Additional rule parameters are passed using the -Erule_parameter_name=value.
Run this data quality check using the check run CLI command by providing the check name and all other targeting filters. The following example shows how to run the monthly_expected_numbers_in_use_count check on all tables and columns on a single data source.
It is also possible to run this check on a specific connection and table. In order to do this, use the connection name and the full table name parameters.
dqo> check run -c=connection_name -t=schema_name.table_name -ch=monthly_expected_numbers_in_use_count
You can also run this check on all tables (and columns) on which the monthly_expected_numbers_in_use_count check is enabled using patterns to find tables.
YAML configuration
The sample schema_name.table_name.dqotable.yaml file with the check configured is shown below.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
columns:
target_column:
monitoring_checks:
monthly:
accepted_values:
monthly_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
Samples of generated SQL queries for each data source type
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count data quality sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
Expand the Configure with data grouping section to see additional examples for configuring this data quality checks to use data grouping (GROUP BY).
Configuration with data grouping
Sample configuration with data grouping enabled (YAML) The sample below shows how to configure the data grouping and how it affects the generated SQL query.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
default_grouping_name: group_by_country_and_state
groupings:
group_by_country_and_state:
level_1:
source: column_value
column: country
level_2:
source: column_value
column: state
columns:
target_column:
monitoring_checks:
monthly:
accepted_values:
monthly_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
country:
labels:
- column used as the first grouping key
state:
labels:
- column used as the second grouping key
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.[country] AS grouping_level_1,
analyzed_table.[state] AS grouping_level_2
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY analyzed_table.[country], analyzed_table.[state]
ORDER BY level_1, level_2
,
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2
ORDER BY grouping_level_1, grouping_level_2
daily partition expected numbers in use count
Check description
Verifies that the expected numeric values were found in the column. Raises a data quality issue when too many expected values were not found (were missing). Stores a separate data quality check result for each daily partition.
Data quality check name | Friendly name | Category | Check type | Time scale | Quality dimension | Sensor definition | Quality rule | Standard |
---|---|---|---|---|---|---|---|---|
daily_partition_expected_numbers_in_use_count |
Maximum number of expected numeric values that are not in use | accepted_values | partitioned | daily | Reasonableness | expected_numbers_in_use_count | max_missing |
Command-line examples
Please expand the section below to see the DQOps command-line examples to run or activate the daily partition expected numbers in use count data quality check.
Managing daily partition expected numbers in use count check from DQOps shell
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the warning rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=daily_partition_expected_numbers_in_use_count --enable-warning
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=daily_partition_expected_numbers_in_use_count --enable-warning
Additional rule parameters are passed using the -Wrule_parameter_name=value.
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the error rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=daily_partition_expected_numbers_in_use_count --enable-error
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=daily_partition_expected_numbers_in_use_count --enable-error
Additional rule parameters are passed using the -Erule_parameter_name=value.
Run this data quality check using the check run CLI command by providing the check name and all other targeting filters. The following example shows how to run the daily_partition_expected_numbers_in_use_count check on all tables and columns on a single data source.
It is also possible to run this check on a specific connection and table. In order to do this, use the connection name and the full table name parameters.
dqo> check run -c=connection_name -t=schema_name.table_name -ch=daily_partition_expected_numbers_in_use_count
You can also run this check on all tables (and columns) on which the daily_partition_expected_numbers_in_use_count check is enabled using patterns to find tables.
YAML configuration
The sample schema_name.table_name.dqotable.yaml file with the check configured is shown below.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
timestamp_columns:
partition_by_column: date_column
incremental_time_window:
daily_partitioning_recent_days: 7
monthly_partitioning_recent_months: 1
columns:
target_column:
partitioned_checks:
daily:
accepted_values:
daily_partition_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
date_column:
labels:
- "date or datetime column used as a daily or monthly partitioning key, dates\
\ (and times) are truncated to a day or a month by the sensor's query for\
\ partitioned checks"
Samples of generated SQL queries for each data source type
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count data quality sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table.`date_column` AS DATE) AS time_period,
TIMESTAMP(CAST(analyzed_table.`date_column` AS DATE)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table."date_column" AS DATE) AS time_period,
toDateTime64(CAST(analyzed_table."date_column" AS DATE), 3) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table.`date_column` AS DATE) AS time_period,
TIMESTAMP(CAST(analyzed_table.`date_column` AS DATE)) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
CAST(original_table."date_column" AS DATE) AS time_period,
TIMESTAMP(CAST(original_table."date_column" AS DATE)) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table."date_column" AS date) AS time_period,
CAST((CAST(analyzed_table."date_column" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
CAST(original_table."date_column" AS DATE) AS time_period,
TO_TIMESTAMP(CAST(original_table."date_column" AS DATE)) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
TRUNC(CAST(original_table."date_column" AS DATE)) AS time_period,
CAST(TRUNC(CAST(original_table."date_column" AS DATE)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table."date_column" AS date) AS time_period,
CAST((CAST(analyzed_table."date_column" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
CAST(original_table."date_column" AS date) AS time_period,
CAST(CAST(original_table."date_column" AS date) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
CAST(DATE_TRUNC('day', original_table."date_column") AS DATE) AS time_period,
CAST((CAST(DATE_TRUNC('day', original_table."date_column") AS DATE)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table."date_column" AS date) AS time_period,
CAST((CAST(analyzed_table."date_column" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table."date_column" AS date) AS time_period,
TO_TIMESTAMP(CAST(analyzed_table."date_column" AS date)) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table.`date_column` AS DATE) AS time_period,
TIMESTAMP(CAST(analyzed_table.`date_column` AS DATE)) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table.[date_column] AS date) AS time_period,
CAST((CAST(analyzed_table.[date_column] AS date)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY CAST(analyzed_table.[date_column] AS date), CAST(analyzed_table.[date_column] AS date)
ORDER BY CAST(analyzed_table.[date_column] AS date)
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
CAST(analyzed_table."date_column" AS DATE) AS time_period,
CAST(CAST(analyzed_table."date_column" AS DATE) AS TIMESTAMP) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
CAST(original_table."date_column" AS date) AS time_period,
CAST(CAST(original_table."date_column" AS date) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Expand the Configure with data grouping section to see additional examples for configuring this data quality checks to use data grouping (GROUP BY).
Configuration with data grouping
Sample configuration with data grouping enabled (YAML) The sample below shows how to configure the data grouping and how it affects the generated SQL query.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
timestamp_columns:
partition_by_column: date_column
incremental_time_window:
daily_partitioning_recent_days: 7
monthly_partitioning_recent_months: 1
default_grouping_name: group_by_country_and_state
groupings:
group_by_country_and_state:
level_1:
source: column_value
column: country
level_2:
source: column_value
column: state
columns:
target_column:
partitioned_checks:
daily:
accepted_values:
daily_partition_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
date_column:
labels:
- "date or datetime column used as a daily or monthly partitioning key, dates\
\ (and times) are truncated to a day or a month by the sensor's query for\
\ partitioned checks"
country:
labels:
- column used as the first grouping key
state:
labels:
- column used as the second grouping key
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
CAST(analyzed_table.`date_column` AS DATE) AS time_period,
TIMESTAMP(CAST(analyzed_table.`date_column` AS DATE)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
CAST(analyzed_table."date_column" AS DATE) AS time_period,
toDateTime64(CAST(analyzed_table."date_column" AS DATE), 3) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
CAST(analyzed_table.`date_column` AS DATE) AS time_period,
TIMESTAMP(CAST(analyzed_table.`date_column` AS DATE)) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
CAST(original_table."date_column" AS DATE) AS time_period,
TIMESTAMP(CAST(original_table."date_column" AS DATE)) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
CAST(analyzed_table."date_column" AS date) AS time_period,
CAST((CAST(analyzed_table."date_column" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
CAST(original_table."date_column" AS DATE) AS time_period,
TO_TIMESTAMP(CAST(original_table."date_column" AS DATE)) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-%d 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
TRUNC(CAST(original_table."date_column" AS DATE)) AS time_period,
CAST(TRUNC(CAST(original_table."date_column" AS DATE)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
CAST(analyzed_table."date_column" AS date) AS time_period,
CAST((CAST(analyzed_table."date_column" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
CAST(original_table."date_column" AS date) AS time_period,
CAST(CAST(original_table."date_column" AS date) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
CAST(DATE_TRUNC('day', original_table."date_column") AS DATE) AS time_period,
CAST((CAST(DATE_TRUNC('day', original_table."date_column") AS DATE)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
CAST(analyzed_table."date_column" AS date) AS time_period,
CAST((CAST(analyzed_table."date_column" AS date)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
CAST(analyzed_table."date_column" AS date) AS time_period,
TO_TIMESTAMP(CAST(analyzed_table."date_column" AS date)) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
CAST(analyzed_table.`date_column` AS DATE) AS time_period,
TIMESTAMP(CAST(analyzed_table.`date_column` AS DATE)) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.[country] AS grouping_level_1,
analyzed_table.[state] AS grouping_level_2,
CAST(analyzed_table.[date_column] AS date) AS time_period,
CAST((CAST(analyzed_table.[date_column] AS date)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY analyzed_table.[country], analyzed_table.[state], CAST(analyzed_table.[date_column] AS date), CAST(analyzed_table.[date_column] AS date)
ORDER BY level_1, level_2CAST(analyzed_table.[date_column] AS date)
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
CAST(analyzed_table."date_column" AS DATE) AS time_period,
CAST(CAST(analyzed_table."date_column" AS DATE) AS TIMESTAMP) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
CAST(original_table."date_column" AS date) AS time_period,
CAST(CAST(original_table."date_column" AS date) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
monthly partition expected numbers in use count
Check description
Verifies that the expected numeric values were found in the column. Raises a data quality issue when too many expected values were not found (were missing). Stores a separate data quality check result for each monthly partition.
Data quality check name | Friendly name | Category | Check type | Time scale | Quality dimension | Sensor definition | Quality rule | Standard |
---|---|---|---|---|---|---|---|---|
monthly_partition_expected_numbers_in_use_count |
Maximum number of expected numeric values that are not in use | accepted_values | partitioned | monthly | Reasonableness | expected_numbers_in_use_count | max_missing |
Command-line examples
Please expand the section below to see the DQOps command-line examples to run or activate the monthly partition expected numbers in use count data quality check.
Managing monthly partition expected numbers in use count check from DQOps shell
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the warning rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=monthly_partition_expected_numbers_in_use_count --enable-warning
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=monthly_partition_expected_numbers_in_use_count --enable-warning
Additional rule parameters are passed using the -Wrule_parameter_name=value.
Activate this data quality using the check activate CLI command, providing the connection name, table name, check name, and all other filters. Activates the error rule with the default parameters.
dqo> check activate -c=connection_name -t=schema_name.table_name -col=column_name -ch=monthly_partition_expected_numbers_in_use_count --enable-error
You can also use patterns to activate the check on all matching tables and columns.
dqo> check activate -c=connection_name -t=schema_prefix*.fact_* -col=column_name -ch=monthly_partition_expected_numbers_in_use_count --enable-error
Additional rule parameters are passed using the -Erule_parameter_name=value.
Run this data quality check using the check run CLI command by providing the check name and all other targeting filters. The following example shows how to run the monthly_partition_expected_numbers_in_use_count check on all tables and columns on a single data source.
It is also possible to run this check on a specific connection and table. In order to do this, use the connection name and the full table name parameters.
dqo> check run -c=connection_name -t=schema_name.table_name -ch=monthly_partition_expected_numbers_in_use_count
You can also run this check on all tables (and columns) on which the monthly_partition_expected_numbers_in_use_count check is enabled using patterns to find tables.
YAML configuration
The sample schema_name.table_name.dqotable.yaml file with the check configured is shown below.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
timestamp_columns:
partition_by_column: date_column
incremental_time_window:
daily_partitioning_recent_days: 7
monthly_partitioning_recent_months: 1
columns:
target_column:
partitioned_checks:
monthly:
accepted_values:
monthly_partition_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
date_column:
labels:
- "date or datetime column used as a daily or monthly partitioning key, dates\
\ (and times) are truncated to a day or a month by the sensor's query for\
\ partitioned checks"
Samples of generated SQL queries for each data source type
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count data quality sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC(CAST(analyzed_table.`date_column` AS DATE), MONTH) AS time_period,
TIMESTAMP(DATE_TRUNC(CAST(analyzed_table.`date_column` AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('month', CAST(analyzed_table."date_column" AS DATE)) AS time_period,
toDateTime64(DATE_TRUNC('month', CAST(analyzed_table."date_column" AS DATE)), 3) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE)) AS time_period,
TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE))) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
DATE_TRUNC('MONTH', CAST(original_table."date_column" AS DATE)) AS time_period,
TIMESTAMP(DATE_TRUNC('MONTH', CAST(original_table."date_column" AS DATE))) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
SERIES_ROUND(CAST(original_table."date_column" AS DATE), 'INTERVAL 1 MONTH', ROUND_DOWN) AS time_period,
TO_TIMESTAMP(SERIES_ROUND(CAST(original_table."date_column" AS DATE), 'INTERVAL 1 MONTH', ROUND_DOWN)) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
TRUNC(CAST(original_table."date_column" AS DATE), 'MONTH') AS time_period,
CAST(TRUNC(CAST(original_table."date_column" AS DATE), 'MONTH') AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS time_period,
CAST(DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
CAST(DATE_TRUNC('month', original_table."date_column") AS DATE) AS time_period,
CAST((CAST(DATE_TRUNC('month', original_table."date_column") AS DATE)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE)) AS time_period,
TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE))) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1) AS time_period,
CAST((DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1), DATEADD(month, DATEDIFF(month, 0, analyzed_table.[date_column]), 0)
ORDER BY DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1)
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
TRUNC(CAST(analyzed_table."date_column" AS DATE), 'MM') AS time_period,
CAST(TRUNC(CAST(analyzed_table."date_column" AS DATE), 'MM') AS TIMESTAMP) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS time_period,
CAST(DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY time_period, time_period_utc
ORDER BY time_period, time_period_utc
Expand the Configure with data grouping section to see additional examples for configuring this data quality checks to use data grouping (GROUP BY).
Configuration with data grouping
Sample configuration with data grouping enabled (YAML) The sample below shows how to configure the data grouping and how it affects the generated SQL query.
# yaml-language-server: $schema=https://cloud.dqops.com/dqo-yaml-schema/TableYaml-schema.json
apiVersion: dqo/v1
kind: table
spec:
timestamp_columns:
partition_by_column: date_column
incremental_time_window:
daily_partitioning_recent_days: 7
monthly_partitioning_recent_months: 1
default_grouping_name: group_by_country_and_state
groupings:
group_by_country_and_state:
level_1:
source: column_value
column: country
level_2:
source: column_value
column: state
columns:
target_column:
partitioned_checks:
monthly:
accepted_values:
monthly_partition_expected_numbers_in_use_count:
parameters:
expected_values:
- 2
- 3
warning:
max_missing: 0
error:
max_missing: 1
fatal:
max_missing: 2
labels:
- This is the column that is analyzed for data quality issues
date_column:
labels:
- "date or datetime column used as a daily or monthly partitioning key, dates\
\ (and times) are truncated to a day or a month by the sensor's query for\
\ partitioned checks"
country:
labels:
- column used as the first grouping key
state:
labels:
- column used as the second grouping key
Please expand the database engine name section to see the SQL query rendered by a Jinja2 template for the expected_numbers_in_use_count sensor.
BigQuery
{% import '/dialects/bigquery.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_TRUNC(CAST(analyzed_table.`date_column` AS DATE), MONTH) AS time_period,
TIMESTAMP(DATE_TRUNC(CAST(analyzed_table.`date_column` AS DATE), MONTH)) AS time_period_utc
FROM `your-google-project-id`.`<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ClickHouse
{% import '/dialects/clickhouse.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
DATE_TRUNC('month', CAST(analyzed_table."date_column" AS DATE)) AS time_period,
toDateTime64(DATE_TRUNC('month', CAST(analyzed_table."date_column" AS DATE)), 3) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Databricks
{% import '/dialects/databricks.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE)) AS time_period,
TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE))) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
DB2
{% import '/dialects/db2.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(original_table."date_column" AS DATE)) AS time_period,
TIMESTAMP(DATE_TRUNC('MONTH', CAST(original_table."date_column" AS DATE))) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
DuckDB
{% import '/dialects/duckdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
HANA
{% import '/dialects/hana.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
SERIES_ROUND(CAST(original_table."date_column" AS DATE), 'INTERVAL 1 MONTH', ROUND_DOWN) AS time_period,
TO_TIMESTAMP(SERIES_ROUND(CAST(original_table."date_column" AS DATE), 'INTERVAL 1 MONTH', ROUND_DOWN)) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
MariaDB
{% import '/dialects/mariadb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
MySQL
{% import '/dialects/mysql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3
)
THEN analyzed_table.`target_column`
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00') AS time_period,
FROM_UNIXTIME(UNIX_TIMESTAMP(DATE_FORMAT(analyzed_table.`date_column`, '%Y-%m-01 00:00:00'))) AS time_period_utc
FROM `<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Oracle
{% import '/dialects/oracle.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
TRUNC(CAST(original_table."date_column" AS DATE), 'MONTH') AS time_period,
CAST(TRUNC(CAST(original_table."date_column" AS DATE), 'MONTH') AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
PostgreSQL
{% import '/dialects/postgresql.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_postgresql_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Presto
{% import '/dialects/presto.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS time_period,
CAST(DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_database"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
QuestDB
{% import '/dialects/questdb.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_actual_value() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_DISTINCT(
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{render_actual_value()}} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM(
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT_DISTINCT(
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2,
time_period,
time_period_utc
FROM(
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
CAST(DATE_TRUNC('month', original_table."date_column") AS DATE) AS time_period,
CAST((CAST(DATE_TRUNC('month', original_table."date_column") AS DATE)) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Redshift
{% import '/dialects/redshift.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
CAST((DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS TIMESTAMP WITH TIME ZONE) AS time_period_utc
FROM "your_redshift_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Snowflake
{% import '/dialects/snowflake.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT(*) = 0 THEN NULL
ELSE COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3
)
THEN analyzed_table."target_column"
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date)) AS time_period,
TO_TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table."date_column" AS date))) AS time_period_utc
FROM "your_snowflake_database"."<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Spark
{% import '/dialects/spark.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table.`target_column` IN (2, 3)
THEN analyzed_table.`target_column`
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.`country` AS grouping_level_1,
analyzed_table.`state` AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE)) AS time_period,
TIMESTAMP(DATE_TRUNC('MONTH', CAST(analyzed_table.`date_column` AS DATE))) AS time_period_utc
FROM `<target_schema>`.`<target_table>` AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
SQL Server
{% import '/dialects/sqlserver.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{values_list|join(', ')}}
{% endmacro %}
{%- macro render_else() -%}
{%- if parameters.expected_values|length == 0 -%}
0
{%- else -%}
COUNT_BIG(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE {{render_else()}}
END AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
CASE
WHEN COUNT_BIG(*) = 0 THEN MAX(0)
ELSE COUNT_BIG(DISTINCT
CASE
WHEN analyzed_table.[target_column] IN (2, 3
)
THEN analyzed_table.[target_column]
ELSE NULL
END
)
END AS actual_value,
MAX(2) AS expected_value,
analyzed_table.[country] AS grouping_level_1,
analyzed_table.[state] AS grouping_level_2,
DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1) AS time_period,
CAST((DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1)) AS DATETIME) AS time_period_utc
FROM [your_sql_server_database].[<target_schema>].[<target_table>] AS analyzed_table
GROUP BY analyzed_table.[country], analyzed_table.[state], DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1), DATEADD(month, DATEDIFF(month, 0, analyzed_table.[date_column]), 0)
ORDER BY level_1, level_2DATEFROMPARTS(YEAR(CAST(analyzed_table.[date_column] AS date)), MONTH(CAST(analyzed_table.[date_column] AS date)), 1)
Teradata
{% import '/dialects/teradata.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections('analyzed_table') }}
{{- lib.render_time_dimension_projection('analyzed_table') }}
FROM {{ lib.render_target_table() }} AS analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table."country" AS grouping_level_1,
analyzed_table."state" AS grouping_level_2,
TRUNC(CAST(analyzed_table."date_column" AS DATE), 'MM') AS time_period,
CAST(TRUNC(CAST(analyzed_table."date_column" AS DATE), 'MM') AS TIMESTAMP) AS time_period_utc
FROM "<target_schema>"."<target_table>" AS analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
Trino
{% import '/dialects/trino.sql.jinja2' as lib with context -%}
{%- macro extract_in_list(values_list) -%}
{{ values_list|join(', ') -}}
{% endmacro %}
{%- macro actual_value() -%}
{%- if 'expected_values' not in parameters or parameters.expected_values | length == 0 -%}
0
{%- else -%}
COUNT(DISTINCT
CASE
WHEN {{ lib.render_target_column('analyzed_table') }} IN ({{ extract_in_list(parameters.expected_values) }})
THEN {{ lib.render_target_column('analyzed_table') }}
ELSE NULL
END
)
{%- endif -%}
{% endmacro -%}
SELECT
{{ actual_value() }} AS actual_value,
MAX({{ parameters.expected_values | length }}) AS expected_value
{{- lib.render_data_grouping_projections_reference('analyzed_table') }}
{{- lib.render_time_dimension_projection_reference('analyzed_table') }}
FROM (
SELECT
original_table.*
{{- lib.render_data_grouping_projections('original_table') }}
{{- lib.render_time_dimension_projection('original_table') }}
FROM {{ lib.render_target_table() }} original_table
) analyzed_table
{{- lib.render_where_clause() -}}
{{- lib.render_group_by() -}}
{{- lib.render_order_by() -}}
SELECT
COUNT(DISTINCT
CASE
WHEN analyzed_table."target_column" IN (2, 3)
THEN analyzed_table."target_column"
ELSE NULL
END
) AS actual_value,
MAX(2) AS expected_value,
analyzed_table.grouping_level_1,
analyzed_table.grouping_level_2
,
time_period,
time_period_utc
FROM (
SELECT
original_table.*,
original_table."country" AS grouping_level_1,
original_table."state" AS grouping_level_2,
DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS time_period,
CAST(DATE_TRUNC('MONTH', CAST(original_table."date_column" AS date)) AS TIMESTAMP) AS time_period_utc
FROM "your_trino_catalog"."<target_schema>"."<target_table>" original_table
) analyzed_table
GROUP BY grouping_level_1, grouping_level_2, time_period, time_period_utc
ORDER BY grouping_level_1, grouping_level_2, time_period, time_period_utc
What's next
- Learn how to configure data quality checks in DQOps
- Look at the examples of running data quality checks, targeting tables and columns