Neuw84 opened a new pull request, #17296: URL: https://github.com/apache/iceberg/pull/17296
RowIdVectorReader and LastUpdatedSeqVectorReader allocated a fresh BigIntVector from the root allocator on every batch, ignored the reuse parameter, kept no reference to the returned vector and had no-op close() methods. Nothing downstream closes the holders' vectors either, so every batch of a vectorized read that projects _row_id or _last_updated_sequence_number leaked one direct-memory vector. On long-running Spark row-level operations against format-version 3 tables this grows without bound until the executor is killed (the identical workload against a v2 table runs flat, as the lineage readers are never instantiated). The readers now own their result vector like the base reader owns vec: they allocate it lazily, reuse it across batches while its capacity suffices and release it in close(), which also closes the delegate readers. New tests assert the root allocator returns to its baseline after close and fail against the previous implementation. AI Disclosure Model: Claude Fable Platform/Tool: Kiro Human Oversight: reviewed Relates to https://github.com/apache/iceberg/issues/17241 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
