[SPARK-56804][SQL] Add bulk read+convert path for DATE to TimestampNTZ Parquet vector updater#55855
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[SPARK-56804][SQL] Add bulk read+convert path for DATE to TimestampNTZ Parquet vector updater#55855LuciferYang wants to merge 4 commits into
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What changes were proposed in this pull request?
Extend the bulk read+convert pattern introduced in SPARK-56791 to
DateToTimestampNTZUpdater(parquet INT32 DATE read into a SparkTimestampNTZTypeat UTC, CORRECTED rebase mode).A new
readIntegersAsTimestampMicrosdefault method onVectorizedValuesReaderdoes the per-row fallback.VectorizedPlainValuesReaderoverrides it to fetch source bytes once viagetBuffer(total * 4)and run a tight in-method conversion loop.DateToTimestampNTZUpdater.readValuesbecomes a one-line delegation. The per-element conversion isDateTimeUtils.daysToMicros(days, ZoneOffset.UTC), matching the per-row Updater's exact semantics including theMath.multiplyExactoverflow check. TheLEGACY/EXCEPTIONrebase variants (handled byDateToTimestampNTZWithRebaseUpdater) are out of scope.Unlike the pure-primitive-cast siblings (SPARK-56791/56801/56802), the per-element conversion here is a function call rather than a JVM-native widen, so the expected speedup is smaller; the win still comes from collapsing N
getBuffer(4)allocations into one.Why are the changes needed?
DateToTimestampNTZUpdater.readValuesallocates a freshByteBufferslice insidegetBuffer(4)for every element on the legacy path. Collapsing N allocations into one is the same win SPARK-56791 delivered for the INT32 -> Long sibling.Does this PR introduce any user-facing change?
No.
How was this patch tested?
(To be updated after the GHA benchmark and test runs complete.)
Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Code