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https://issues.apache.org/jira/browse/SPARK-57828?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Max Gekk updated SPARK-57828:
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Shepherd: Max Gekk
> Add vectorized Parquet reader support for nanosecond-precision timestamp types
> ------------------------------------------------------------------------------
>
> Key: SPARK-57828
> URL: https://issues.apache.org/jira/browse/SPARK-57828
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 4.3.0
> Reporter: Max Gekk
> Priority: Major
>
> This sub-task is part of the umbrella SPARK-56822 (timestamps with nanosecond
> precision).
> h2. Problem
> Nanosecond Parquet READ only works via the row-based reader.
> {{TimestampNanosParquetOps.isBatchReadSupported}}
> (datasources/parquet/TimestampNanosParquetOps.scala ~L54-58) stays at the
> trait default {{false}}, and {{ParquetUtils.isBatchReadSupportedForSchema}}
> requires every column to support batch read, so any nanosecond column forces
> the whole file onto {{ParquetRowConverter}} even when vectorized reading is
> enabled. {{ParquetVectorUpdaterFactory}} (~L140-161) only has MICROS/MILLIS
> timestamp updaters. Correct but slow; Parquet WRITE + non-vectorized READ are
> already done (SPARK-57102).
> h2. Goal
> Read {{TIMESTAMP(NANOS)}} columns through the vectorized path, materializing
> the 16-byte {{TimestampNanosVal}} (epoch micros + nanosecond remainder) into
> the columnar batch.
> h2. Scope
> Implement a nanosecond updater in {{ParquetVectorUpdaterFactory}} /
> {{VectorizedColumnReader}}; flip {{isBatchReadSupported}} for the nanosecond
> ops; ensure the columnar layout matches the nanosecond {{ColumnVector}}
> (added under SPARK-57100).
> h2. Acceptance criteria
> * Nanosecond Parquet files read correctly with
> {{spark.sql.parquet.enableVectorizedReader=true}}, matching the row-reader
> results; no fallback for nanosecond-only schemas.
> h2. Testing
> {{ParquetTimestampNanosSuite}} (with the vectorized reader on),
> {{ParquetQuerySuite}}.
> h2. Dependencies
> None - independent (columnar layout resolved in SPARK-57100).
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