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added test
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@WilliamDee
WilliamDee committed Dec 15, 2023
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351 changes: 351 additions & 0 deletions metricflow/test/integration/test_cases/itest_conversion_metric.yaml
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---
integration_test:
name: conversion_rate_metric_infinite_window
description: Query a conversion metric that calculates the conversion rate
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate"]
group_bys: ["metric_time"]
check_query: |
SELECT
opportunities.metric_time AS metric_time__day
, CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate
FROM (
SELECT
metric_time, SUM(a.visits) AS visits
FROM (
SELECT
ds AS metric_time, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.metric_time
) opportunities
FULL OUTER JOIN (
SELECT
b.ds AS metric_time, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id AND v.ds <= buy_source.ds
) b
GROUP BY
b.ds
) conversions
ON opportunities.metric_time = conversions.metric_time
---
integration_test:
name: conversion_rate_metric_no_group_by
description: Query a conversion metric that calculates the conversion rate with no group bys
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate_7days"]
check_query: |
SELECT
CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate_7days
FROM (
SELECT
SUM(a.visits) AS visits
FROM (
SELECT
1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
) opportunities
CROSS JOIN (
SELECT
SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id AND v.ds <= buy_source.ds
) b
) conversions
---
integration_test:
name: conversion_rate_metric
description: Query a conversion metric that calculates the conversion rate
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate_7days"]
group_bys: ["metric_time"]
check_query: |
SELECT
opportunities.metric_time AS metric_time__day
, CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate_7days
FROM (
SELECT
metric_time, SUM(a.visits) AS visits
FROM (
SELECT
ds AS metric_time, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.metric_time
) opportunities
FULL OUTER JOIN (
SELECT
b.ds AS metric_time, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id AND v.ds <= buy_source.ds AND v.ds > {{ render_date_sub("buy_source", "ds", 7, TimeGranularity.DAY) }}
) b
GROUP BY
b.ds
) conversions
ON opportunities.metric_time = conversions.metric_time
---
integration_test:
name: conversion_rate_metric_with_dimension
description: Query a conversion metric that calculates the conversion rate without time dimension
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate_7days"]
group_bys: ["visit__referrer_id"]
check_query: |
SELECT
opportunities.referrer_id AS visit__referrer_id
, CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate_7days
FROM (
SELECT
referrer_id, SUM(a.visits) AS visits
FROM (
SELECT
referrer_id, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.referrer_id
) opportunities
FULL OUTER JOIN (
SELECT
referrer_id AS referrer_id, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id AND v.ds <= buy_source.ds AND v.ds > {{ render_date_sub("buy_source", "ds", 7, TimeGranularity.DAY) }}
) b
GROUP BY
b.referrer_id
) conversions
ON opportunities.referrer_id = conversions.referrer_id
---
integration_test:
name: conversion_rate_metric_with_multiple_dimension
description: Query a conversion metric that calculates the conversion rate with multiple dimension
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate_7days"]
group_bys: ["metric_time", "visit__referrer_id"]
check_query: |
SELECT
opportunities.referrer_id AS visit__referrer_id
, opportunities.metric_time AS metric_time__day
, CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate_7days
FROM (
SELECT
metric_time, referrer_id, SUM(a.visits) AS visits
FROM (
SELECT
ds AS metric_time, referrer_id, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.referrer_id, a.metric_time
) opportunities
FULL OUTER JOIN (
SELECT
b.ds AS metric_time, referrer_id AS referrer_id, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id AND v.ds <= buy_source.ds AND v.ds > {{ render_date_sub("buy_source", "ds", 7, TimeGranularity.DAY) }}
) b
GROUP BY
b.referrer_id, b.ds
) conversions
ON opportunities.referrer_id = conversions.referrer_id AND opportunities.metric_time = conversions.metric_time
---
integration_test:
name: conversion_count_metric_with_multiple_dimension
description: Query a conversion metric that calculates the conversion count with multiple dimension
model: SIMPLE_MODEL
metrics: ["visit_buy_conversions"]
group_bys: ["metric_time", "visit__referrer_id"]
check_query: |
SELECT
opportunities.referrer_id AS visit__referrer_id
, opportunities.metric_time AS metric_time__day
, conversions.buys AS visit_buy_conversions
FROM (
SELECT
metric_time, referrer_id, SUM(a.visits) AS visits
FROM (
SELECT
ds AS metric_time, referrer_id, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.referrer_id, a.metric_time
) opportunities
FULL OUTER JOIN (
SELECT
b.ds AS metric_time, referrer_id AS referrer_id, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id AND v.ds <= buy_source.ds AND v.ds > {{ render_date_sub("buy_source", "ds", 7, TimeGranularity.DAY) }}
) b
GROUP BY
b.referrer_id, b.ds
) conversions
ON opportunities.referrer_id = conversions.referrer_id AND opportunities.metric_time = conversions.metric_time
---
integration_test:
name: conversion_rate_metric_with_constant_property
description: Query a conversion metric that calculates the conversion rate held by a constant property
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate_by_session"]
group_bys: ["metric_time"]
check_query: |
SELECT
opportunities.metric_time AS metric_time__day
, CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate_by_session
FROM (
SELECT
metric_time, SUM(a.visits) AS visits
FROM (
SELECT
ds AS metric_time, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.metric_time
) opportunities
FULL OUTER JOIN (
SELECT
b.ds AS metric_time, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id, buy_source.session_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id, buy_source.session_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id, buy_source.session_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id
AND v.ds <= buy_source.ds AND v.ds > {{ render_date_sub("buy_source", "ds", 7, TimeGranularity.DAY) }}
AND buy_source.session_id = v.session_id
) b
GROUP BY
b.ds
) conversions
ON opportunities.metric_time = conversions.metric_time
---
integration_test:
name: conversion_rate_metric_with_constant_property_multiple_dimensions
description: Query a conversion metric that calculates the conversion rate held by a constant property
model: SIMPLE_MODEL
metrics: ["visit_buy_conversion_rate_by_session"]
group_bys: ["metric_time", "visit__referrer_id"]
check_query: |
SELECT
opportunities.referrer_id AS visit__referrer_id
, opportunities.metric_time AS metric_time__day
, CAST(conversions.buys AS {{ double_data_type_name }}) / CAST(NULLIF(opportunities.visits, 0) AS {{ double_data_type_name }}) AS visit_buy_conversion_rate_by_session
FROM (
SELECT
metric_time, referrer_id, SUM(a.visits) AS visits
FROM (
SELECT
ds AS metric_time, referrer_id, 1 AS visits
FROM {{ source_schema }}.fct_visits visits
) a
GROUP BY
a.referrer_id, a.metric_time
) opportunities
FULL OUTER JOIN (
SELECT
b.ds AS metric_time, referrer_id AS referrer_id, SUM(b.buys) AS buys
FROM (
SELECT DISTINCT
first_value(v.ds) OVER (PARTITION BY buy_source.ds, buy_source.user_id, buy_source.session_id ORDER BY v.ds DESC) AS ds
, first_value(v.user_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id, buy_source.session_id ORDER BY v.ds DESC) AS user_id
, first_value(v.referrer_id) OVER (PARTITION BY buy_source.ds, buy_source.user_id, buy_source.session_id ORDER BY v.ds DESC) AS referrer_id
, buy_source.uuid
, 1 AS buys
FROM {{ source_schema }}.fct_visits v
INNER JOIN
(
SELECT *, {{ generate_random_uuid() }} AS uuid FROM {{ source_schema }}.fct_buys
) buy_source
ON
v.user_id = buy_source.user_id
AND v.ds <= buy_source.ds AND v.ds > {{ render_date_sub("buy_source", "ds", 7, TimeGranularity.DAY) }}
AND buy_source.session_id = v.session_id
) b
GROUP BY
b.referrer_id, b.ds
) conversions
ON opportunities.referrer_id = conversions.referrer_id AND opportunities.metric_time = conversions.metric_time
8 changes: 8 additions & 0 deletions metricflow/test/integration/test_configured_cases.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@
SqlColumnReferenceExpression,
SqlDateTruncExpression,
SqlExtractExpression,
SqlGenerateUuidExpression,
SqlPercentileExpression,
SqlPercentileExpressionArgument,
SqlPercentileFunctionType,
Expand Down Expand Up @@ -172,6 +173,11 @@ def render_time_dimension_template(
f"{{{{ TimeDimension('{time_dimension_name}', '{time_granularity}', entity_path={repr(entity_path)}) }}}}"
)

def generate_random_uuid(self) -> str:
"""Returns the generate random UUID SQL function."""
expr = SqlGenerateUuidExpression()
return self._sql_client.sql_query_plan_renderer.expr_renderer.render_sql_expr(expr).sql


def filter_not_supported_features(
sql_client: SqlClient, required_features: Tuple[RequiredDwEngineFeatures, ...]
Expand Down Expand Up @@ -295,6 +301,7 @@ def test_case(
render_dimension_template=check_query_helpers.render_dimension_template,
render_entity_template=check_query_helpers.render_entity_template,
render_time_dimension_template=check_query_helpers.render_time_dimension_template,
generate_random_uuid=check_query_helpers.generate_random_uuid,
)
if case.where_filter
else None,
Expand All @@ -319,6 +326,7 @@ def test_case(
render_percentile_expr=check_query_helpers.render_percentile_expr,
mf_time_spine_source=semantic_manifest_lookup.time_spine_source.spine_table.sql,
double_data_type_name=check_query_helpers.double_data_type_name,
generate_random_uuid=check_query_helpers.generate_random_uuid,
)
)
# If we sort, it's effectively not checking the order whatever order that the output was would be overwritten.
Expand Down
2 changes: 1 addition & 1 deletion metricflow/test/model/test_semantic_model_container.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,7 +115,7 @@ def test_local_linked_elements_for_metric( # noqa: D
def test_get_semantic_models_for_entity(semantic_model_lookup: SemanticModelLookup) -> None: # noqa: D
entity_reference = EntityReference(element_name="user")
linked_semantic_models = semantic_model_lookup.get_semantic_models_for_entity(entity_reference=entity_reference)
assert len(linked_semantic_models) == 8
assert len(linked_semantic_models) == 10


def test_linkable_set( # noqa: D
Expand Down
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