Add RESULT_COLLECTOR profiling metric#38
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Instruments the executor.GetResult() call in FetchResultInternal with a new phase timing metric to measure time spent collecting and materializing query results. This helps diagnose latency gaps between DuckDB's reported execution time and actual wall-clock time. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Instruments two additional unprofiled gaps in the query execution path: - EXECUTOR_INITIALIZE: time spent building pipelines and scheduling tasks - CLEANUP: time spent in post-execution cleanup including transaction commit Together with RESULT_COLLECTOR, these cover all major gaps between profiler.StartQuery() and profiler.EndQuery(). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…ANUP The result collector's work is already captured in CPU_TIME as part of pipeline execution. The EXECUTOR_INITIALIZE and CLEANUP phase metrics cover the actual unprofiled gaps in the query lifecycle. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
RESULT_COLLECTORphase timing metric that measures time spent inexecutor.GetResult()during result materializationTest plan
test_custom_profiling_result_collector.testpasses (30 assertions)scripts/generate_metric_enums.py(72 metrics, 10 phase_timing)🤖 Generated with Claude Code