mirror of
https://github.com/PostHog/posthog.git
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811 lines
26 KiB
Python
811 lines
26 KiB
Python
# isort: skip_file
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# Needs to be first to set up django environment
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from .helpers import benchmark_clickhouse, no_materialized_columns, now
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from datetime import timedelta
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from ee.clickhouse.materialized_columns.analyze import (
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backfill_materialized_columns,
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get_materialized_columns,
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materialize,
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)
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from ee.clickhouse.queries.stickiness import ClickhouseStickiness
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from ee.clickhouse.queries.funnels.funnel_correlation import FunnelCorrelation
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from posthog.queries.funnels import ClickhouseFunnel
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from posthog.queries.property_values import (
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get_property_values_for_key,
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get_person_property_values_for_key,
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)
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from posthog.queries.trends.trends import Trends
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from posthog.queries.session_recordings.session_recording_list import (
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SessionRecordingList,
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)
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from ee.clickhouse.queries.retention import ClickhouseRetention
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from posthog.queries.util import get_earliest_timestamp
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from posthog.models import Action, Cohort, Team, Organization
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from posthog.models.filters.retention_filter import RetentionFilter
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from posthog.models.filters.session_recordings_filter import SessionRecordingsFilter
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from posthog.models.filters.stickiness_filter import StickinessFilter
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from posthog.models.filters.filter import Filter
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from posthog.models.property import PropertyName, TableWithProperties
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from posthog.constants import FunnelCorrelationType
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MATERIALIZED_PROPERTIES: dict[TableWithProperties, list[PropertyName]] = {
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"events": [
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"$current_url",
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"$event_type",
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"$host",
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],
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"person": [
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"$browser",
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"email",
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],
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}
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DATE_RANGE = {"date_from": "2021-01-01", "date_to": "2021-10-01", "interval": "week"}
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SHORT_DATE_RANGE = {
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"date_from": "2021-07-01",
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"date_to": "2021-10-01",
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"interval": "week",
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}
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SESSIONS_DATE_RANGE = {"date_from": "2021-11-17", "date_to": "2021-11-22"}
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class QuerySuite:
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timeout = 3000.0 # Timeout for the whole suite
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version = "v001" # Version. Incrementing this will invalidate previous results
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team: Team
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cohort: Cohort
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@benchmark_clickhouse
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def track_trends_no_filter(self):
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filter = Filter(data={"events": [{"id": "$pageview"}], **DATE_RANGE})
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_event_property_filter(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [
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{
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"key": "$host",
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"operator": "is_not",
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"value": [
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"localhost:8000",
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"localhost:5000",
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"127.0.0.1:8000",
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"127.0.0.1:3000",
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"localhost:3000",
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],
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}
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],
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**SHORT_DATE_RANGE,
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}
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)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_event_property_filter_materialized(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [
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{
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"key": "$host",
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"operator": "is_not",
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"value": [
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"localhost:8000",
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"localhost:5000",
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"127.0.0.1:8000",
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"127.0.0.1:3000",
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"localhost:3000",
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],
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}
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],
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**DATE_RANGE,
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}
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)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_person_property_filter(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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**DATE_RANGE,
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}
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)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_person_property_filter_materialized(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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**DATE_RANGE,
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}
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)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_event_property_breakdown(self):
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filter = Filter(data={"events": [{"id": "$pageview"}], "breakdown": "$host", **DATE_RANGE})
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_event_property_breakdown_materialized(self):
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filter = Filter(data={"events": [{"id": "$pageview"}], "breakdown": "$host", **DATE_RANGE})
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_person_property_breakdown(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"breakdown": "$browser",
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"breakdown_type": "person",
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**DATE_RANGE,
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}
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)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_person_property_breakdown_materialized(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"breakdown": "$browser",
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"breakdown_type": "person",
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**DATE_RANGE,
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}
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)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_dau(self):
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filter = Filter(data={"events": [{"id": "$pageview", "math": "dau"}], **DATE_RANGE})
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_dau_person_property_filter(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview", "math": "dau"}],
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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**DATE_RANGE,
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}
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)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_dau_person_property_filter_materialized(self):
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filter = Filter(
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data={
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"events": [{"id": "$pageview", "math": "dau"}],
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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**DATE_RANGE,
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}
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)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_cohort_precalculated(self):
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self.cohort.last_calculation = now()
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self.cohort.save()
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [{"key": "id", "value": self.cohort.pk, "type": "cohort"}],
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**DATE_RANGE,
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},
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team=self.team,
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)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_cohort(self):
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self.cohort.last_calculation = None
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self.cohort.save()
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [{"key": "id", "value": self.cohort.pk, "type": "cohort"}],
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**DATE_RANGE,
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},
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team=self.team,
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)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_cohort_materialized(self):
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self.cohort.last_calculation = None
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self.cohort.save()
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filter = Filter(
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data={
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"events": [{"id": "$pageview"}],
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"properties": [{"key": "id", "value": self.cohort.pk, "type": "cohort"}],
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**DATE_RANGE,
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},
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team=self.team,
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)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_action_current_url_materialized(self):
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action = Action.objects.create(
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team=self.team,
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name="docs view",
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steps_json=[{"event": "$pageview", "url": "docs", "url_matching": "contains"}],
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)
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filter = Filter(data={"actions": [{"id": action.id}], **DATE_RANGE}, team=self.team)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_action_current_url(self):
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action = Action.objects.create(
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team=self.team,
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name="docs view",
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steps_json=[{"event": "$pageview", "url": "docs", "url_matching": "contains"}],
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)
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filter = Filter(data={"actions": [{"id": action.id}], **DATE_RANGE}, team=self.team)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_action_with_person_filters_materialized(self):
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action = Action.objects.create(
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team=self.team,
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name=".com-users page views",
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steps_json=[
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{
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"event": "$pageview",
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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}
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],
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)
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filter = Filter(data={"actions": [{"id": action.id}], **DATE_RANGE}, team=self.team)
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_trends_filter_by_action_with_person_filters(self):
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action = Action.objects.create(
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team=self.team,
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name=".com-users page views",
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steps_json=[
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{
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"event": "$pageview",
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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}
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],
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)
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filter = Filter(data={"actions": [{"id": action.id}], **DATE_RANGE}, team=self.team)
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with no_materialized_columns():
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Trends().run(filter, self.team)
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@benchmark_clickhouse
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def track_funnel_normal(self):
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filter = Filter(
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data={
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"insight": "FUNNELS",
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"events": [
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{"id": "user signed up", "order": 0},
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{"id": "insight analyzed", "order": 1},
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],
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**DATE_RANGE,
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},
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team=self.team,
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)
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ClickhouseFunnel(filter, self.team).run()
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@benchmark_clickhouse
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def track_correlations_by_events(self):
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filter = Filter(
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data={
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"events": [{"id": "user signed up"}, {"id": "insight analyzed"}],
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**SHORT_DATE_RANGE,
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},
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team=self.team,
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)
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FunnelCorrelation(filter, self.team).run()
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@benchmark_clickhouse
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def track_correlations_by_properties_materialized(self):
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filter = Filter(
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data={
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"events": [{"id": "user signed up"}, {"id": "insight analyzed"}],
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**SHORT_DATE_RANGE,
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"funnel_correlation_type": FunnelCorrelationType.PROPERTIES,
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"funnel_correlation_names": ["$browser"],
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},
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team=self.team,
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)
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FunnelCorrelation(filter, self.team).run()
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@benchmark_clickhouse
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def track_correlations_by_properties(self):
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filter = Filter(
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data={
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"events": [{"id": "user signed up"}, {"id": "insight analyzed"}],
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**SHORT_DATE_RANGE,
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"funnel_correlation_type": FunnelCorrelationType.PROPERTIES,
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"funnel_correlation_names": ["$browser"],
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},
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team=self.team,
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)
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with no_materialized_columns():
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FunnelCorrelation(filter, self.team).run()
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@benchmark_clickhouse
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def track_correlations_by_event_properties(self):
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filter = Filter(
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data={
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"events": [{"id": "user signed up"}, {"id": "insight analyzed"}],
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**SHORT_DATE_RANGE,
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"funnel_correlation_type": FunnelCorrelationType.EVENT_WITH_PROPERTIES,
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"funnel_correlation_event_names": ["$autocapture"],
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},
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team=self.team,
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)
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with no_materialized_columns():
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FunnelCorrelation(filter, self.team).run()
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@benchmark_clickhouse
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def track_correlations_by_event_properties_materialized(self):
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filter = Filter(
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data={
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"events": [{"id": "user signed up"}, {"id": "insight analyzed"}],
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**SHORT_DATE_RANGE,
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"funnel_correlation_type": FunnelCorrelationType.EVENT_WITH_PROPERTIES,
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"funnel_correlation_event_names": ["$autocapture"],
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},
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team=self.team,
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)
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FunnelCorrelation(filter, self.team).run()
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@benchmark_clickhouse
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def track_stickiness(self):
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filter = StickinessFilter(
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data={
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"insight": "STICKINESS",
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"events": [{"id": "$pageview"}],
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"shown_as": "Stickiness",
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"display": "ActionsLineGraph",
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**DATE_RANGE,
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},
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team=self.team,
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)
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ClickhouseStickiness().run(filter, self.team)
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@benchmark_clickhouse
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def track_stickiness_filter_by_person_property(self):
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filter = StickinessFilter(
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data={
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"insight": "STICKINESS",
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"events": [{"id": "$pageview"}],
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"shown_as": "Stickiness",
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"display": "ActionsLineGraph",
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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**DATE_RANGE,
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},
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team=self.team,
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)
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with no_materialized_columns():
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ClickhouseStickiness().run(filter, self.team)
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@benchmark_clickhouse
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def track_stickiness_filter_by_person_property_materialized(self):
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filter = StickinessFilter(
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data={
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"insight": "STICKINESS",
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"events": [{"id": "$pageview"}],
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"shown_as": "Stickiness",
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"display": "ActionsLineGraph",
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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**DATE_RANGE,
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},
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team=self.team,
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)
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ClickhouseStickiness().run(filter, self.team)
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@benchmark_clickhouse
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def track_session_recordings_list(self):
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filter = SessionRecordingsFilter(data=SESSIONS_DATE_RANGE, team=self.team)
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SessionRecordingList(filter, self.team).run()
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@benchmark_clickhouse
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def track_session_recordings_list_event_filter(self):
|
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filter = SessionRecordingsFilter(
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data={"events": [{"id": "$pageview"}], **SESSIONS_DATE_RANGE},
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team=self.team,
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)
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SessionRecordingList(filter, self.team).run()
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@benchmark_clickhouse
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|
def track_session_recordings_list_person_property_filter(self):
|
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filter = SessionRecordingsFilter(
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data={
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"events": [
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{
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"id": "$pageview",
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"properties": [
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{
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"key": "email",
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"operator": "icontains",
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"value": ".com",
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"type": "person",
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}
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],
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}
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],
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**SESSIONS_DATE_RANGE,
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},
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team=self.team,
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)
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SessionRecordingList(filter, self.team).run()
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|
|
@benchmark_clickhouse
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|
def track_retention(self):
|
|
filter = RetentionFilter(
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data={
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"insight": "RETENTION",
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"target_event": {"id": "$pageview"},
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"returning_event": {"id": "$pageview"},
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"total_intervals": 14,
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|
"retention_type": "retention_first_time",
|
|
"period": "Week",
|
|
**DATE_RANGE,
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},
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team=self.team,
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)
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|
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ClickhouseRetention().run(filter, self.team)
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|
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@benchmark_clickhouse
|
|
def track_retention_with_person_breakdown(self):
|
|
filter = RetentionFilter(
|
|
data={
|
|
"insight": "RETENTION",
|
|
"target_event": {"id": "$pageview"},
|
|
"returning_event": {"id": "$pageview"},
|
|
"total_intervals": 14,
|
|
"retention_type": "retention_first_time",
|
|
"breakdown_type": "person",
|
|
"breakdowns": [
|
|
{"type": "person", "property": "$browser"},
|
|
{"type": "person", "property": "$browser_version"},
|
|
],
|
|
"period": "Week",
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
with no_materialized_columns():
|
|
ClickhouseRetention().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_retention_filter_by_person_property(self):
|
|
filter = RetentionFilter(
|
|
data={
|
|
"insight": "RETENTION",
|
|
"target_event": {"id": "$pageview"},
|
|
"returning_event": {"id": "$pageview"},
|
|
"total_intervals": 14,
|
|
"retention_type": "retention_first_time",
|
|
"period": "Week",
|
|
"properties": [
|
|
{
|
|
"key": "email",
|
|
"operator": "icontains",
|
|
"value": ".com",
|
|
"type": "person",
|
|
}
|
|
],
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
with no_materialized_columns():
|
|
ClickhouseRetention().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_retention_filter_by_person_property_materialized(self):
|
|
filter = RetentionFilter(
|
|
data={
|
|
"insight": "RETENTION",
|
|
"target_event": {"id": "$pageview"},
|
|
"returning_event": {"id": "$pageview"},
|
|
"total_intervals": 14,
|
|
"retention_type": "retention_first_time",
|
|
"period": "Week",
|
|
"properties": [
|
|
{
|
|
"key": "email",
|
|
"operator": "icontains",
|
|
"value": ".com",
|
|
"type": "person",
|
|
}
|
|
],
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
ClickhouseRetention().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_lifecycle(self):
|
|
filter = Filter(
|
|
data={
|
|
"insight": "LIFECYCLE",
|
|
"events": [{"id": "$pageview", "type": "events"}],
|
|
"interval": "week",
|
|
"shown_as": "Lifecycle",
|
|
"date_from": "-14d",
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
Trends().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_lifecycle_event_property_filter(self):
|
|
filter = Filter(
|
|
data={
|
|
"insight": "LIFECYCLE",
|
|
"events": [{"id": "$pageview", "type": "events"}],
|
|
"interval": "week",
|
|
"shown_as": "Lifecycle",
|
|
"date_from": "-14d",
|
|
"properties": [
|
|
{
|
|
"key": "$host",
|
|
"operator": "is_not",
|
|
"value": [
|
|
"localhost:8000",
|
|
"localhost:5000",
|
|
"127.0.0.1:8000",
|
|
"127.0.0.1:3000",
|
|
"localhost:3000",
|
|
],
|
|
}
|
|
],
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
with no_materialized_columns():
|
|
Trends().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_lifecycle_event_property_filter_materialized(self):
|
|
filter = Filter(
|
|
data={
|
|
"insight": "LIFECYCLE",
|
|
"events": [{"id": "$pageview", "type": "events"}],
|
|
"interval": "week",
|
|
"shown_as": "Lifecycle",
|
|
"date_from": "-14d",
|
|
"properties": [
|
|
{
|
|
"key": "$host",
|
|
"operator": "is_not",
|
|
"value": [
|
|
"localhost:8000",
|
|
"localhost:5000",
|
|
"127.0.0.1:8000",
|
|
"127.0.0.1:3000",
|
|
"localhost:3000",
|
|
],
|
|
}
|
|
],
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
Trends().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_lifecycle_person_property_filter(self):
|
|
filter = Filter(
|
|
data={
|
|
"insight": "LIFECYCLE",
|
|
"events": [{"id": "$pageview", "type": "events"}],
|
|
"interval": "week",
|
|
"shown_as": "Lifecycle",
|
|
"date_from": "-14d",
|
|
"properties": [
|
|
{
|
|
"key": "email",
|
|
"operator": "icontains",
|
|
"value": ".com",
|
|
"type": "person",
|
|
}
|
|
],
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
with no_materialized_columns():
|
|
Trends().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_lifecycle_person_property_filter_materialized(self):
|
|
filter = Filter(
|
|
data={
|
|
"insight": "LIFECYCLE",
|
|
"events": [{"id": "$pageview", "type": "events"}],
|
|
"interval": "week",
|
|
"shown_as": "Lifecycle",
|
|
"date_from": "-14d",
|
|
"properties": [
|
|
{
|
|
"key": "email",
|
|
"operator": "icontains",
|
|
"value": ".com",
|
|
"type": "person",
|
|
}
|
|
],
|
|
**DATE_RANGE,
|
|
},
|
|
team=self.team,
|
|
)
|
|
|
|
Trends().run(filter, self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_earliest_timestamp(self):
|
|
get_earliest_timestamp(2)
|
|
|
|
@benchmark_clickhouse
|
|
def track_event_property_values(self):
|
|
with no_materialized_columns():
|
|
get_property_values_for_key("$browser", self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_event_property_values_materialized(self):
|
|
get_property_values_for_key("$browser", self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_person_property_values(self):
|
|
with no_materialized_columns():
|
|
get_person_property_values_for_key("$browser", self.team)
|
|
|
|
@benchmark_clickhouse
|
|
def track_person_property_values_materialized(self):
|
|
get_person_property_values_for_key("$browser", self.team)
|
|
|
|
def setup(self):
|
|
for table, properties in MATERIALIZED_PROPERTIES.items():
|
|
existing_materialized_columns = get_materialized_columns(table)
|
|
for property in properties:
|
|
if (property, "properties") not in existing_materialized_columns:
|
|
materialize(table, property)
|
|
backfill_materialized_columns(
|
|
table,
|
|
[(property, "properties")],
|
|
backfill_period=timedelta(days=1_000),
|
|
)
|
|
|
|
# :TRICKY: Data in benchmark servers has ID=2
|
|
team = Team.objects.filter(id=2).first()
|
|
if team is None:
|
|
organization = Organization.objects.create()
|
|
team = Team.objects.create(id=2, organization=organization, name="The Bakery")
|
|
self.team = team
|
|
|
|
cohort = Cohort.objects.filter(name="benchmarking cohort").first()
|
|
if cohort is None:
|
|
cohort = Cohort.objects.create(
|
|
team_id=2,
|
|
name="benchmarking cohort",
|
|
groups=[
|
|
{
|
|
"properties": [
|
|
{
|
|
"key": "email",
|
|
"operator": "icontains",
|
|
"value": ".com",
|
|
"type": "person",
|
|
}
|
|
]
|
|
}
|
|
],
|
|
)
|
|
cohort.calculate_people_ch(pending_version=0)
|
|
self.cohort = cohort
|