feat(experiments): ExperimentQueryRunner iteration 1 #28353
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PR Summary
This PR introduces data warehouse support and test account filtering to the ExperimentQueryRunner, with significant test coverage and query snapshots.
- Added data warehouse support in
experiment_query_runner.pywith dynamic metric value extraction based on query type - Implemented test account filtering with comprehensive test coverage across multiple filter types (person, event, cohort, etc.)
- Added new
ExperimentQueryPydantic model inschema.pyto handle both trends and data warehouse queries - Added cleanup mechanism in tests to properly handle S3/object storage test data
- Enhanced query construction to support both regular events and data warehouse tables with proper joins
3 file(s) reviewed, 1 comment(s)
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| metric_property = self.query.count_query.series[0].math_property | ||
| metric_value = f"toFloat(JSONExtractRaw(properties, '{metric_property}'))" | ||
| if is_data_warehouse_query: | ||
| metric_value = f"toFloat('{metric_property}')" | ||
| else: |
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logic: Potential SQL injection vulnerability in metric_property interpolation. Should use parameterized queries or proper escaping.
danielbachhuber
changed the title
andehen
merged commit 4c2e54e
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init-new-experiment-query-runner
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andehen
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Feb 6, 2025
Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
danielbachhuber
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Feb 11, 2025
Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>
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Merges into #28347
Changes
ExperimentQuery.How did you test this code?
Tests should pass.