[HUDI-7045] fix evolution by using legacy ff for reader#10007
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jonvex wants to merge 1 commit intoapache:masterfrom
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[HUDI-7045] fix evolution by using legacy ff for reader#10007jonvex wants to merge 1 commit intoapache:masterfrom
jonvex wants to merge 1 commit intoapache:masterfrom
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codope
reviewed
Nov 8, 2023
| supportBatchResult | ||
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| private def wrapWithBatchConverter(reader: PartitionedFile => Iterator[InternalRow]): PartitionedFile => Iterator[InternalRow] = { |
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why is this needed? i think the flatmap per row could incur some significant cost for a large batch. Instead of wrapping everytime, can it be guarded for some cases such as when schema on read is enabled?
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Right. @jonvex I think Spark internally handles the batch processing (InternalRow vs ColumnarBatch) based on the boolean supportBatch returns. So we don't have to do batch converter here?
yihua
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Change Logs
Some of schema on write schema evolution happens inside the reader so we need to use legacy file format
Impact
schema evolution works with the new reader and ff
Risk level (write none, low medium or high below)
low
Documentation Update
N/A
Contributor's checklist