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Write various tests for metric queries with custom granularity
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tests_metricflow/query_rendering/test_custom_granularity.py
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| """Tests metric query rendering for granularity and date part operations. | ||
| This module runs query requests for various granularity/date part options and compares | ||
| the rendered output against snapshot files. | ||
| """ | ||
|
|
||
| from __future__ import annotations | ||
|
|
||
| import pytest | ||
| from _pytest.fixtures import FixtureRequest | ||
| from dbt_semantic_interfaces.references import EntityReference | ||
| from dbt_semantic_interfaces.type_enums.time_granularity import TimeGranularity | ||
| from metricflow_semantics.specs.metric_spec import MetricSpec | ||
| from metricflow_semantics.specs.query_spec import MetricFlowQuerySpec | ||
| from metricflow_semantics.specs.time_dimension_spec import TimeDimensionSpec | ||
| from metricflow_semantics.test_helpers.config_helpers import MetricFlowTestConfiguration | ||
| from metricflow_semantics.time.granularity import ExpandedTimeGranularity | ||
|
|
||
| from metricflow.dataflow.builder.dataflow_plan_builder import DataflowPlanBuilder | ||
| from metricflow.plan_conversion.dataflow_to_sql import DataflowToSqlQueryPlanConverter | ||
| from metricflow.protocols.sql_client import SqlClient | ||
| from tests_metricflow.query_rendering.compare_rendered_query import render_and_check | ||
|
|
||
| metric_time_with_custom_grain = TimeDimensionSpec( | ||
| "metric_time", | ||
| entity_links=(), | ||
| time_granularity=ExpandedTimeGranularity(name="martian_day", base_granularity=TimeGranularity.DAY), | ||
| ) | ||
| normal_time_dim_with_custom_grain1 = TimeDimensionSpec( | ||
| element_name="ds", | ||
| time_granularity=ExpandedTimeGranularity(name="martian_day", base_granularity=TimeGranularity.DAY), | ||
| entity_links=(EntityReference("booking"),), | ||
| ) | ||
| normal_time_dim_with_custom_grain2 = TimeDimensionSpec( | ||
| element_name="bio_added_ts", | ||
| time_granularity=ExpandedTimeGranularity(name="martian_day", base_granularity=TimeGranularity.DAY), | ||
| entity_links=(EntityReference("user"),), | ||
| ) | ||
|
|
||
|
|
||
| # TODO: subqueries in this test should be collapsed. Update optimizer | ||
| @pytest.mark.sql_engine_snapshot | ||
| def test_simple_metric_with_custom_granularity( # noqa: D103 | ||
| request: FixtureRequest, | ||
| mf_test_configuration: MetricFlowTestConfiguration, | ||
| dataflow_plan_builder: DataflowPlanBuilder, | ||
| dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter, | ||
| sql_client: SqlClient, | ||
| ) -> None: | ||
| query_spec = MetricFlowQuerySpec( | ||
| metric_specs=(MetricSpec("bookings"),), | ||
| time_dimension_specs=(normal_time_dim_with_custom_grain1,), | ||
| ) | ||
|
|
||
| render_and_check( | ||
| request=request, | ||
| mf_test_configuration=mf_test_configuration, | ||
| dataflow_to_sql_converter=dataflow_to_sql_converter, | ||
| sql_client=sql_client, | ||
| dataflow_plan_builder=dataflow_plan_builder, | ||
| query_spec=query_spec, | ||
| ) | ||
|
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||
|
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||
| @pytest.mark.sql_engine_snapshot | ||
| def test_cumulative_metric_with_custom_granularity( # noqa: D103 | ||
| request: FixtureRequest, | ||
| mf_test_configuration: MetricFlowTestConfiguration, | ||
| dataflow_plan_builder: DataflowPlanBuilder, | ||
| dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter, | ||
| sql_client: SqlClient, | ||
| ) -> None: | ||
| query_spec = MetricFlowQuerySpec( | ||
| metric_specs=(MetricSpec("trailing_2_months_revenue"),), | ||
| time_dimension_specs=(metric_time_with_custom_grain,), | ||
| ) | ||
|
|
||
| render_and_check( | ||
| request=request, | ||
| mf_test_configuration=mf_test_configuration, | ||
| dataflow_to_sql_converter=dataflow_to_sql_converter, | ||
| sql_client=sql_client, | ||
| dataflow_plan_builder=dataflow_plan_builder, | ||
| query_spec=query_spec, | ||
| ) | ||
|
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||
|
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||
| @pytest.mark.sql_engine_snapshot | ||
| def test_derived_metric_with_custom_granularity( # noqa: D103 | ||
| request: FixtureRequest, | ||
| mf_test_configuration: MetricFlowTestConfiguration, | ||
| dataflow_plan_builder: DataflowPlanBuilder, | ||
| dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter, | ||
| sql_client: SqlClient, | ||
| ) -> None: | ||
| query_spec = MetricFlowQuerySpec( | ||
| metric_specs=(MetricSpec("booking_fees_per_booker"),), | ||
| time_dimension_specs=(normal_time_dim_with_custom_grain1,), | ||
| ) | ||
|
|
||
| render_and_check( | ||
| request=request, | ||
| mf_test_configuration=mf_test_configuration, | ||
| dataflow_to_sql_converter=dataflow_to_sql_converter, | ||
| sql_client=sql_client, | ||
| dataflow_plan_builder=dataflow_plan_builder, | ||
| query_spec=query_spec, | ||
| ) | ||
|
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||
|
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||
| # TODO: subqueries in this test should be collapsed. Update optimizer | ||
| @pytest.mark.sql_engine_snapshot | ||
| def test_multiple_metrics_with_custom_granularity( # noqa: D103 | ||
| request: FixtureRequest, | ||
| mf_test_configuration: MetricFlowTestConfiguration, | ||
| dataflow_plan_builder: DataflowPlanBuilder, | ||
| dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter, | ||
| sql_client: SqlClient, | ||
| ) -> None: | ||
| query_spec = MetricFlowQuerySpec( | ||
| metric_specs=(MetricSpec("bookings"), MetricSpec("listings")), | ||
| time_dimension_specs=(metric_time_with_custom_grain,), | ||
| ) | ||
|
|
||
| render_and_check( | ||
| request=request, | ||
| mf_test_configuration=mf_test_configuration, | ||
| dataflow_to_sql_converter=dataflow_to_sql_converter, | ||
| sql_client=sql_client, | ||
| dataflow_plan_builder=dataflow_plan_builder, | ||
| query_spec=query_spec, | ||
| ) | ||
|
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| # TODO: subqueries in this test should be collapsed. Update optimizer | ||
| @pytest.mark.sql_engine_snapshot | ||
| def test_metric_custom_granularity_joined_to_non_default_grain( # noqa: D103 | ||
| request: FixtureRequest, | ||
| mf_test_configuration: MetricFlowTestConfiguration, | ||
| dataflow_plan_builder: DataflowPlanBuilder, | ||
| dataflow_to_sql_converter: DataflowToSqlQueryPlanConverter, | ||
| sql_client: SqlClient, | ||
| ) -> None: | ||
| query_spec = MetricFlowQuerySpec( | ||
| metric_specs=(MetricSpec("listings"),), | ||
| time_dimension_specs=( | ||
| metric_time_with_custom_grain, | ||
| TimeDimensionSpec( | ||
| element_name="ds", | ||
| time_granularity=ExpandedTimeGranularity.from_time_granularity(TimeGranularity.MONTH), | ||
| entity_links=(EntityReference("listing"),), | ||
| ), | ||
| ), | ||
| ) | ||
|
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| render_and_check( | ||
| request=request, | ||
| mf_test_configuration=mf_test_configuration, | ||
| dataflow_to_sql_converter=dataflow_to_sql_converter, | ||
| sql_client=sql_client, | ||
| dataflow_plan_builder=dataflow_plan_builder, | ||
| query_spec=query_spec, | ||
| ) |
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...nularity.py/SqlQueryPlan/DuckDB/test_cumulative_metric_with_custom_granularity__plan0.sql
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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| -- Re-aggregate Metric via Group By | ||
| SELECT | ||
| subq_9.metric_time__martian_day | ||
| , subq_9.trailing_2_months_revenue | ||
| FROM ( | ||
| -- Window Function for Metric Re-aggregation | ||
| SELECT | ||
| subq_8.metric_time__martian_day | ||
| , AVG(subq_8.trailing_2_months_revenue) OVER (PARTITION BY subq_8.metric_time__martian_day) AS trailing_2_months_revenue | ||
| FROM ( | ||
| -- Compute Metrics via Expressions | ||
| SELECT | ||
| subq_7.metric_time__martian_day | ||
| , subq_7.metric_time__day | ||
| , subq_7.txn_revenue AS trailing_2_months_revenue | ||
| FROM ( | ||
| -- Aggregate Measures | ||
| SELECT | ||
| subq_6.metric_time__martian_day | ||
| , subq_6.metric_time__day | ||
| , SUM(subq_6.txn_revenue) AS txn_revenue | ||
| FROM ( | ||
| -- Pass Only Elements: ['txn_revenue', 'metric_time__day', 'metric_time__day'] | ||
| -- Join to Custom Granularity Dataset | ||
| SELECT | ||
| subq_4.metric_time__day AS metric_time__day | ||
| , subq_4.txn_revenue AS txn_revenue | ||
| , subq_5.martian_day AS metric_time__martian_day | ||
| FROM ( | ||
| -- Join Self Over Time Range | ||
| SELECT | ||
| subq_2.metric_time__day AS metric_time__day | ||
| , subq_1.ds__day AS ds__day | ||
| , subq_1.ds__week AS ds__week | ||
| , subq_1.ds__month AS ds__month | ||
| , subq_1.ds__quarter AS ds__quarter | ||
| , subq_1.ds__year AS ds__year | ||
| , subq_1.ds__extract_year AS ds__extract_year | ||
| , subq_1.ds__extract_quarter AS ds__extract_quarter | ||
| , subq_1.ds__extract_month AS ds__extract_month | ||
| , subq_1.ds__extract_day AS ds__extract_day | ||
| , subq_1.ds__extract_dow AS ds__extract_dow | ||
| , subq_1.ds__extract_doy AS ds__extract_doy | ||
| , subq_1.revenue_instance__ds__day AS revenue_instance__ds__day | ||
| , subq_1.revenue_instance__ds__week AS revenue_instance__ds__week | ||
| , subq_1.revenue_instance__ds__month AS revenue_instance__ds__month | ||
| , subq_1.revenue_instance__ds__quarter AS revenue_instance__ds__quarter | ||
| , subq_1.revenue_instance__ds__year AS revenue_instance__ds__year | ||
| , subq_1.revenue_instance__ds__extract_year AS revenue_instance__ds__extract_year | ||
| , subq_1.revenue_instance__ds__extract_quarter AS revenue_instance__ds__extract_quarter | ||
| , subq_1.revenue_instance__ds__extract_month AS revenue_instance__ds__extract_month | ||
| , subq_1.revenue_instance__ds__extract_day AS revenue_instance__ds__extract_day | ||
| , subq_1.revenue_instance__ds__extract_dow AS revenue_instance__ds__extract_dow | ||
| , subq_1.revenue_instance__ds__extract_doy AS revenue_instance__ds__extract_doy | ||
| , subq_1.metric_time__week AS metric_time__week | ||
| , subq_1.metric_time__month AS metric_time__month | ||
| , subq_1.metric_time__quarter AS metric_time__quarter | ||
| , subq_1.metric_time__year AS metric_time__year | ||
| , subq_1.metric_time__extract_year AS metric_time__extract_year | ||
| , subq_1.metric_time__extract_quarter AS metric_time__extract_quarter | ||
| , subq_1.metric_time__extract_month AS metric_time__extract_month | ||
| , subq_1.metric_time__extract_day AS metric_time__extract_day | ||
| , subq_1.metric_time__extract_dow AS metric_time__extract_dow | ||
| , subq_1.metric_time__extract_doy AS metric_time__extract_doy | ||
| , subq_1.user AS user | ||
| , subq_1.revenue_instance__user AS revenue_instance__user | ||
| , subq_1.txn_revenue AS txn_revenue | ||
| FROM ( | ||
| -- Time Spine | ||
| SELECT | ||
| subq_3.ds AS metric_time__day | ||
| FROM ***************************.mf_time_spine subq_3 | ||
| ) subq_2 | ||
| INNER JOIN ( | ||
| -- Metric Time Dimension 'ds' | ||
| SELECT | ||
| subq_0.ds__day | ||
| , subq_0.ds__week | ||
| , subq_0.ds__month | ||
| , subq_0.ds__quarter | ||
| , subq_0.ds__year | ||
| , subq_0.ds__extract_year | ||
| , subq_0.ds__extract_quarter | ||
| , subq_0.ds__extract_month | ||
| , subq_0.ds__extract_day | ||
| , subq_0.ds__extract_dow | ||
| , subq_0.ds__extract_doy | ||
| , subq_0.revenue_instance__ds__day | ||
| , subq_0.revenue_instance__ds__week | ||
| , subq_0.revenue_instance__ds__month | ||
| , subq_0.revenue_instance__ds__quarter | ||
| , subq_0.revenue_instance__ds__year | ||
| , subq_0.revenue_instance__ds__extract_year | ||
| , subq_0.revenue_instance__ds__extract_quarter | ||
| , subq_0.revenue_instance__ds__extract_month | ||
| , subq_0.revenue_instance__ds__extract_day | ||
| , subq_0.revenue_instance__ds__extract_dow | ||
| , subq_0.revenue_instance__ds__extract_doy | ||
| , subq_0.ds__day AS metric_time__day | ||
| , subq_0.ds__week AS metric_time__week | ||
| , subq_0.ds__month AS metric_time__month | ||
| , subq_0.ds__quarter AS metric_time__quarter | ||
| , subq_0.ds__year AS metric_time__year | ||
| , subq_0.ds__extract_year AS metric_time__extract_year | ||
| , subq_0.ds__extract_quarter AS metric_time__extract_quarter | ||
| , subq_0.ds__extract_month AS metric_time__extract_month | ||
| , subq_0.ds__extract_day AS metric_time__extract_day | ||
| , subq_0.ds__extract_dow AS metric_time__extract_dow | ||
| , subq_0.ds__extract_doy AS metric_time__extract_doy | ||
| , subq_0.user | ||
| , subq_0.revenue_instance__user | ||
| , subq_0.txn_revenue | ||
| FROM ( | ||
| -- Read Elements From Semantic Model 'revenue' | ||
| SELECT | ||
| revenue_src_28000.revenue AS txn_revenue | ||
| , DATE_TRUNC('day', revenue_src_28000.created_at) AS ds__day | ||
| , DATE_TRUNC('week', revenue_src_28000.created_at) AS ds__week | ||
| , DATE_TRUNC('month', revenue_src_28000.created_at) AS ds__month | ||
| , DATE_TRUNC('quarter', revenue_src_28000.created_at) AS ds__quarter | ||
| , DATE_TRUNC('year', revenue_src_28000.created_at) AS ds__year | ||
| , EXTRACT(year FROM revenue_src_28000.created_at) AS ds__extract_year | ||
| , EXTRACT(quarter FROM revenue_src_28000.created_at) AS ds__extract_quarter | ||
| , EXTRACT(month FROM revenue_src_28000.created_at) AS ds__extract_month | ||
| , EXTRACT(day FROM revenue_src_28000.created_at) AS ds__extract_day | ||
| , EXTRACT(isodow FROM revenue_src_28000.created_at) AS ds__extract_dow | ||
| , EXTRACT(doy FROM revenue_src_28000.created_at) AS ds__extract_doy | ||
| , DATE_TRUNC('day', revenue_src_28000.created_at) AS revenue_instance__ds__day | ||
| , DATE_TRUNC('week', revenue_src_28000.created_at) AS revenue_instance__ds__week | ||
| , DATE_TRUNC('month', revenue_src_28000.created_at) AS revenue_instance__ds__month | ||
| , DATE_TRUNC('quarter', revenue_src_28000.created_at) AS revenue_instance__ds__quarter | ||
| , DATE_TRUNC('year', revenue_src_28000.created_at) AS revenue_instance__ds__year | ||
| , EXTRACT(year FROM revenue_src_28000.created_at) AS revenue_instance__ds__extract_year | ||
| , EXTRACT(quarter FROM revenue_src_28000.created_at) AS revenue_instance__ds__extract_quarter | ||
| , EXTRACT(month FROM revenue_src_28000.created_at) AS revenue_instance__ds__extract_month | ||
| , EXTRACT(day FROM revenue_src_28000.created_at) AS revenue_instance__ds__extract_day | ||
| , EXTRACT(isodow FROM revenue_src_28000.created_at) AS revenue_instance__ds__extract_dow | ||
| , EXTRACT(doy FROM revenue_src_28000.created_at) AS revenue_instance__ds__extract_doy | ||
| , revenue_src_28000.user_id AS user | ||
| , revenue_src_28000.user_id AS revenue_instance__user | ||
| FROM ***************************.fct_revenue revenue_src_28000 | ||
| ) subq_0 | ||
| ) subq_1 | ||
| ON | ||
| ( | ||
| subq_1.metric_time__day <= subq_2.metric_time__day | ||
| ) AND ( | ||
| subq_1.metric_time__day > subq_2.metric_time__day - INTERVAL 2 month | ||
| ) | ||
| ) subq_4 | ||
| LEFT OUTER JOIN | ||
| ***************************.mf_time_spine subq_5 | ||
| ON | ||
| subq_4.metric_time__day = subq_5.ds | ||
| ) subq_6 | ||
| GROUP BY | ||
| subq_6.metric_time__martian_day | ||
| , subq_6.metric_time__day | ||
| ) subq_7 | ||
| ) subq_8 | ||
| ) subq_9 | ||
| GROUP BY | ||
| subq_9.metric_time__martian_day | ||
| , subq_9.trailing_2_months_revenue |
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...y/SqlQueryPlan/DuckDB/test_cumulative_metric_with_custom_granularity__plan0_optimized.sql
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| @@ -0,0 +1,45 @@ | ||
| -- Re-aggregate Metric via Group By | ||
| SELECT | ||
| metric_time__martian_day | ||
| , trailing_2_months_revenue | ||
| FROM ( | ||
| -- Compute Metrics via Expressions | ||
| -- Window Function for Metric Re-aggregation | ||
| SELECT | ||
| metric_time__martian_day | ||
| , AVG(txn_revenue) OVER (PARTITION BY metric_time__martian_day) AS trailing_2_months_revenue | ||
| FROM ( | ||
| -- Pass Only Elements: ['txn_revenue', 'metric_time__day', 'metric_time__day'] | ||
| -- Join to Custom Granularity Dataset | ||
| -- Aggregate Measures | ||
| SELECT | ||
| subq_15.martian_day AS metric_time__martian_day | ||
| , subq_14.metric_time__day AS metric_time__day | ||
| , SUM(subq_14.txn_revenue) AS txn_revenue | ||
| FROM ( | ||
| -- Join Self Over Time Range | ||
| SELECT | ||
| subq_13.ds AS metric_time__day | ||
| , revenue_src_28000.revenue AS txn_revenue | ||
| FROM ***************************.mf_time_spine subq_13 | ||
| INNER JOIN | ||
| ***************************.fct_revenue revenue_src_28000 | ||
| ON | ||
| ( | ||
| DATE_TRUNC('day', revenue_src_28000.created_at) <= subq_13.ds | ||
| ) AND ( | ||
| DATE_TRUNC('day', revenue_src_28000.created_at) > subq_13.ds - INTERVAL 2 month | ||
| ) | ||
| ) subq_14 | ||
| LEFT OUTER JOIN | ||
| ***************************.mf_time_spine subq_15 | ||
| ON | ||
| subq_14.metric_time__day = subq_15.ds | ||
| GROUP BY | ||
| subq_15.martian_day | ||
| , subq_14.metric_time__day | ||
| ) subq_17 | ||
| ) subq_19 | ||
| GROUP BY | ||
| metric_time__martian_day | ||
| , trailing_2_months_revenue |
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