[python] Reduce memory usage for Parquet row-id updates - #9840
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XiaoHongbo-Hope wants to merge 6 commits into
Open
XiaoHongbo-Hope wants to merge 6 commits into
XiaoHongbo-Hope wants to merge 6 commits into
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XiaoHongbo-Hope
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XiaoHongbo-Hope
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September 15, 2026 12:56
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Background
Data-evolution column updates rewrite the affected file-group range, even when only a few rows change. Materializing the projected columns and buffering the merged output can cause high memory usage for large string or nested columns.
Changes
Stream ordinary Parquet updates with bounded row-group buffering independent of read batch size. Preserve row-id ranges, statistics, metadata, and failure cleanup. Deduplicate update projections consistently. Specialized format paths remain unchanged.
This reduces whole-group buffering, but does not eliminate read/write amplification or impose a hard process-memory limit.
Tests
Cover batch/stream upserts, duplicate update columns, nested values, nulls, row-group boundaries, and write/close failure cleanup, including Python 3.6 / PyArrow 6 compatibility.