[SPARK-57568][SQL] Support TimeType in Parquet/ORC aggregate push-down

[MaxGekk]

What changes were proposed in this pull request?

Enable MIN/MAX/COUNT aggregate push-down over TIME columns for the Parquet and ORC data sources, computed from file-footer statistics.

• Add TimeType to the MIN/MAX type allow-list in AggregatePushDownUtils.getSchemaForPushedAggregation. This is shared, engine-agnostic code called by both ParquetScanBuilder and OrcScanBuilder, so the single change enables push-down eligibility for both engines at once.
• Add a TimeType case to OrcUtils.getMinMaxFromColumnStatistics. ORC stores TIME as a LONG, so its statistics are IntegerColumnStatistics; the min/max value is wrapped in a LongWritable and converted back to the Spark TimeType by OrcDeserializer.
• No Parquet reader change is needed: TIME is stored as Parquet INT64, so the existing INT64 branch in ParquetUtils.createAggInternalRowFromFooter feeds the footer stat into a ParquetRowConverter built from the footer PrimitiveType, which carries the TIME(MICROS)/TIME(NANOS) logical annotation and maps to TimeType.

The columnar conversion (AggregatePushDownUtils.convertAggregatesRowToBatch via RowToColumnConverter) already supports TimeType (SPARK-54203), so the columnar path works for TIME.

Why are the changes needed?

This is a sub-task of SPARK-57550 (extending support for the TIME data type). Aggregate push-down lets Parquet/ORC answer MIN/MAX/COUNT from footer statistics without reading and aggregating TIME data at the Spark layer.

Does this PR introduce any user-facing change?

No. This is an internal optimization on the aggregate push-down path; query results are unchanged.

How was this patch tested?

Added tests to the shared FileSourceAggregatePushDownSuite trait, which is extended by ParquetV1/V2AggregatePushDownSuite and OrcV1/V2AggregatePushDownSuite, so each test exercises all four engines:

• Positive: MIN/MAX/COUNT(col)/COUNT(*) push-down over a TIME column at precisions 0, 6, 7, and 9, covering both the Parquet micros (precision <= 6) and nanos (precision >= 7) storage paths, with a null row so COUNT(col) and COUNT(*) differ.
• Negative: a data filter on the TIME column, an aggregate over a non-column expression, and push-down disabled by config -- all asserting the aggregate is not pushed.

Ran:

build/sbt 'sql/testOnly *ParquetV1AggregatePushDownSuite *ParquetV2AggregatePushDownSuite *OrcV1AggregatePushDownSuite *OrcV2AggregatePushDownSuite'

All 92 tests pass.

Was this patch authored or co-authored using generative AI tooling?

Generated-by: Cursor (Claude Opus 4.8)

[MaxGekk]

Follow-up filed for the all-null aggregate push-down behavior found while reviewing this PR: SPARK-57739 (https://issues.apache.org/jira/browse/SPARK-57739). Parquet throws _LEGACY_ERROR_TEMP_3172 on a row group with an all-null chunk, while ORC returns NULL; the fix is type-agnostic and user-facing, so it's tracked separately rather than in this PR.

Update: _LEGACY_ERROR_TEMP_3172 has since been given a proper name in SPARK-57746 (#56859) -> PARQUET_AGGREGATE_PUSH_DOWN_UNSUPPORTED.NO_MIN_MAX (that PR also renames the sibling _LEGACY_ERROR_TEMP_3171 -> .NO_NUM_NULLS). If SPARK-57739 lands after #56859, it should update/remove that named sub-condition rather than the legacy one.