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[GLUTEN-12538][VL] Unblock TIMESTAMP_NTZ min/max in Delta statistics - #12967

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zhouyuan merged 12 commits into
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felipepessoto:gluten-12538-timestamp-ntz-sort-aggregate
Sep 29, 2026
Merged

zhouyuan merged 12 commits into
apache:mainfrom
felipepessoto:gluten-12538-timestamp-ntz-sort-aggregate

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@felipepessoto felipepessoto commented Sep 4, 2026 •

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What changes are proposed in this pull request?

Enable native min/max aggregation for Spark TIMESTAMP_NTZ in the Velox backend, including the task-local SortAggregateExec used to collect Delta write statistics.

The implementation reuses Velox's existing Spark timestamp min/max kernels rather than introducing new aggregate kernels. TIMESTAMP_NTZ remains represented by the distinct Velox TIMESTAMP_UTC logical type, with microsecond precision (Velox implementation, Spark registration).

  • Accept TimestampNTZType in aggregate buffer/result and grouping type checks, and allow aggregate, shuffle, and the projection expressions needed by Delta statistics through the coarse NTZ fallback validator. Existing native function validation remains in place.
  • Use tsntz as the internal function-signature token. The previous ts_ntz token collides with _, which the native signature parser uses to separate argument types (parser).
  • Preserve TIMESTAMP_UTC as Substrait PrecisionTimestamp with precision 6 during type round-tripping.
  • Remove the 42 now-passing TIMESTAMP_NTZ data-skipping cases from the Delta known-failure baseline.

This addresses the NTZ aggregation failure encountered by the Delta statistics tracker in #12538. It does not implement a general fallback for arbitrary unsupported statistics plans or claim support for every NTZ expression. DATE/TIMESTAMP_NTZ cast support is handled separately in #12966.

Related #11622

How was this patch tested?

  • C++ signature, type, and min/max plan round-trip tests verify distinct NTZ type identity, Substrait precision 6, and preservation of microsecond values using Spark min/max.
  • GlutenTimestampNtzAggregateSuite on Spark 4.1 checks native SQL min/max execution and microsecond results, plus Spark fallback for NTZ JSON serialization in a non-UTC session timezone.
  • GlutenDeltaStatsSuite on Spark 3.5/Delta 3.3 and Spark 4.1/Delta 4.x checks writes and read-back of top-level and nested NTZ columns, with exact JSON-path assertions for their min/max statistics.
  • Existing DateFunctionsValidateSuite coverage exercises NTZ scalar functions after the signature-token change.
  • The Delta Spark UT workflow confirms the 42 data-skipping cases pass; unrelated type-widening failures remain in the baseline.

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

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@github-actions github-actions Bot added CORE works for Gluten Core VELOX labels Sep 4, 2026
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🔄 Delta Spark UT started by @felipepessoto (~2.5 h). View run

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@github-actions github-actions Bot added the INFRA label Sep 4, 2026
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felipepessoto marked this pull request as ready for review September 4, 2026 09:33
Copilot AI lite review requested due to automatic review settings September 4, 2026 09:33

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🟡 Changes recommended

A newly added Velox round-trip test uses millisecond-precision timestamps despite declaring microsecond precision, weakening coverage for the intended NTZ precision behavior.

Once you've addressed the issues Copilot identified, you can request another Copilot review.

Pull request overview

Enables native handling of TIMESTAMP_NTZ (Spark) / TIMESTAMP_UTC (Velox) in aggregation and related Delta statistics collection paths for the Velox backend, reducing Spark fallbacks and unblocking Delta stats plans previously rejected due to NTZ types.

Changes:

  • Extend the TimestampNTZ fallback validator to allow aggregates, shuffles, and direct NTZ projections needed by Delta stats plans.
  • Accept TimestampNTZType in aggregation buffer type checks and preserve a distinct native signature token (tsntz) plus Substrait PrecisionTimestamp encoding.
  • Add native regression coverage (Spark UT + Velox C++ tests) and remove now-fixed Delta data-skipping cases from the known-failure baseline.
File summaries
File Description
gluten-ut/spark41/src/test/scala/org/apache/spark/sql/GlutenTimestampNtzAggregateSuite.scala Adds Spark 4.1 regression coverage for NTZ min/max aggregation and a projection fallback case.
gluten-ut/spark41/src/test/scala/org/apache/gluten/utils/velox/VeloxTestSettings.scala Enables the new Spark 4.1 UT suite in Velox test settings.
gluten-substrait/src/main/scala/org/apache/gluten/extension/columnar/validator/Validators.scala Broadens NTZ fallback validation to permit additional plan nodes/expressions used by native stats aggregation.
gluten-substrait/src/main/scala/org/apache/gluten/expression/ConverterUtils.scala Maps Spark TimestampNTZType to Substrait timestamp NTZ type node and uses tsntz in signature naming.
gluten-substrait/src/main/scala/org/apache/gluten/execution/HashAggregateExecBaseTransformer.scala Allows TimestampNTZType in supported aggregation buffer type checks.
cpp/velox/tests/VeloxToSubstraitTypeTest.cc Adds a type-conversion test for TIMESTAMP_UTC -> Substrait PrecisionTimestamp.
cpp/velox/tests/VeloxSubstraitSignatureTest.cc Adds tsntz signature coverage for TIMESTAMP_UTC mapping in both directions.
cpp/velox/tests/VeloxSubstraitRoundTripTest.cc Adds a min/max aggregation round-trip test over TIMESTAMP_UTC.
cpp/velox/substrait/VeloxToSubstraitType.cc Encodes TIMESTAMP_UTC as Substrait precision_timestamp(6).
cpp/velox/substrait/VeloxSubstraitSignature.cc Maps TIMESTAMP_UTC to/from the tsntz signature token.
backends-velox/src-delta40/test/scala/org/apache/spark/sql/delta/GlutenDeltaStatsSuite.scala Adds Delta 4.0 stats regression coverage including nested NTZ columns.
backends-velox/src-delta33/test/scala/org/apache/spark/sql/delta/GlutenDeltaStatsSuite.scala Adds Delta 3.3 stats regression coverage including nested NTZ columns.
.github/workflows/util/delta-spark-ut/known-failures.txt Removes Delta data-skipping known failures resolved by native NTZ stats aggregation support.
Review details
  • Files reviewed: 13/13 changed files
  • Comments generated: 1
  • Review effort level: Lite

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Comment thread cpp/velox/tests/VeloxSubstraitRoundTripTest.cc Outdated
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@Mariamalmesfer @rui-mo I think you two have worked on other timestamp_ntz PRs. Could you take a look, please?

Copilot AI review requested due to automatic review settings September 4, 2026 17:57

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Warning

Copilot couldn't run its full agentic review because it didn't start before the timeout. Make sure your repository has a runner available, or add a copilot-code-review.yml file specifying one with the runs-on attribute. See the docs for more details.

Pull request overview

Copilot reviewed 13 out of 13 changed files in this pull request and generated 6 comments.

Comment thread cpp/velox/tests/VeloxSubstraitRoundTripTest.cc Outdated
Comment thread cpp/velox/substrait/VeloxToSubstraitType.cc Outdated
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Warning

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Pull request overview

Copilot reviewed 13 out of 13 changed files in this pull request and generated 2 comments.

Suppressed comments (1)

gluten-substrait/src/main/scala/org/apache/gluten/extension/columnar/validator/Validators.scala:1

  • The previous implementation used dataType.typeName == "timestamp_ntz", which is resilient across Spark versions/shims. Switching to a direct TimestampNTZType reference introduces a compile-time dependency that can break builds for Spark variants where TimestampNTZType is absent or shaded differently. If this module is cross-built across multiple Spark versions, consider keeping a version-tolerant check (e.g., match TimestampNTZType when available and fall back to typeName), ideally via a shim utility.
/*

Comment thread cpp/velox/substrait/VeloxSubstraitSignature.cc
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🟢 Approval recommended

The changes are cohesive and well-covered by targeted Spark + native regression tests, and the updated validator/signature/type mappings are consistent across JVM and C++ paths.

Review details
  • Files reviewed: 13/13 changed files
  • Comments generated: 0 new
  • Review effort level: Lite

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Comment on lines +34 to +41
if (type->equivalent(*velox::TIMESTAMP_UTC())) {
auto substraitPrecisionTimestamp =
google::protobuf::Arena::CreateMessage<::substrait::Type_PrecisionTimestamp>(&arena);
substraitPrecisionTimestamp->set_precision(6);
substraitPrecisionTimestamp->set_nullability(::substrait::Type_Nullability_NULLABILITY_NULLABLE);
substraitType->set_allocated_precision_timestamp(substraitPrecisionTimestamp);
return *substraitType;
}

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This converter currently accepts only  (arena, type) , with no nullability argument. The parser does not retain nullability in the Velox type, and existing conversion branches—including ordinary  TIMESTAMP —also emit  NULLABLE . Local probes confirmed that required inputs become nullable for both timestamp types, so this behavior is not introduced by the NTZ branch. @rui-mo, should we open a separate issue to track preserving schema nullability end to end, since this is existing converter-wide behavior?

Comment thread cpp/velox/tests/VeloxToSubstraitTypeTest.cc
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felipepessoto and others added 12 commits September 25, 2026 22:41
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Observe the task-local statistics plan in tests and require native aggregate offload in both Delta variants.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Add grouped min/max coverage with TIMESTAMP_NTZ keys and values. Check exact per-key results and require every aggregate stage to use native execution with an NTZ grouping key.

Clarify that disabling TimestampNTZ validation permits supported scans, aggregates, shuffles and projections while other validation rules still apply. Regenerate the public configuration reference.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Describe the high-level fallback behavior of enableTimestampNtzValidation without enumerating the evolving set of supported operators and expressions. Keep the other-validation caveat and regenerate the public configuration reference.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Allow IsNotNull alongside IsNull using the existing NTZ projection allowlist pattern. Add coverage for both null predicates and a compound projection, checking results and native execution when validation is disabled while preserving Spark fallback when it is enabled.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Copilot AI review requested due to automatic review settings September 25, 2026 22:41
@felipepessoto
felipepessoto force-pushed the gluten-12538-timestamp-ntz-sort-aggregate branch from 8f6587c to 92e2698 Compare September 25, 2026 22:41
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@zhouyuan
zhouyuan merged commit 321229a into apache:main Sep 29, 2026
71 checks passed
@felipepessoto
felipepessoto deleted the gluten-12538-timestamp-ntz-sort-aggregate branch September 29, 2026 11:59
malinjawi added a commit to malinjawi/incubator-gluten that referenced this pull request Sep 30, 2026
…ng MERGE's parents on Spark, 42 already gone on main

The delta_spark_ut run on 45bd4ad reports zero regressions and these
now-passing entries:

- 40 ImplicitMergeCastingSuite "MERGE overflow in WHEN MATCHED THEN UPDATE"
  cases. With only the guard, Spark's write projection raised
  SparkArithmeticException [CAST_OVERFLOW] as expected, but the
  RowToVeloxColumnar feeding the native filter above it wrapped that in a
  GlutenException, so the tests saw the wrong exception type. Keeping the
  filter and column drop on Spark removes the transition and the original
  exception propagates.
- 42 DataSkippingDeltaV1* TIMESTAMP_NTZ cases, which apache#12967 fixed and removed
  from the baseline on main after this branch was cut; CI tests the merge
  with main, so they only show against this branch's copy of the file.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
felipepessoto added a commit to felipepessoto/gluten that referenced this pull request Oct 15, 2026
Preserve NTZ logical types and microsecond values across JVM, Substrait and Velox literal conversion. Distinguish timestamp from timestamp_tz, retain complete types for null literals, and handle scalar vector-backed constants without a virtual-table container.

Connect the existing JVM NTZ literal node to the literal factory and nested type handling. Include the NTZ type mapping required by independent literal and Values round trips, with dedicated native and Spark 4.1 regression coverage.

Follow-up to apache#12967 (comment)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
meta-codesync Bot pushed a commit to facebookincubator/velox that referenced this pull request Oct 19, 2026
Spark `to_json` currently applies the session timezone to `TIMESTAMP_UTC` (`TIMESTAMP_NTZ`) values and appends an offset. For example, in an `America/Los_Angeles` session:

```sql
SELECT to_json(named_struct('ts', TIMESTAMP_NTZ '2024-01-01 00:00:00.123456'));
```

```text
Before: {"ts":"2023-12-31T16:00:00.123-08:00"}
After:  {"ts":"2024-01-01T00:00:00.123"}
```

Use timezone-free formatting for NTZ values, including values nested in collections. Ordinary timestamp formatting and timestamp map-key encoding are unchanged.

This follows [Spark's NTZ JSON formatting](https://github.com/apache/spark/blob/v4.1.1/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/json/JacksonGenerator.scala#L147-L156) and addresses serializer behavior exposed while reviewing apache/gluten#12967.

Generated-by: GitHub Copilot CLI 1.0.83

Differential Revision: D125968265

Pull Request resolved: #19199
felipepessoto added a commit to felipepessoto/gluten that referenced this pull request Oct 21, 2026
Preserve NTZ logical types and microsecond values across JVM, Substrait and Velox literal conversion. Distinguish timestamp from timestamp_tz, retain complete types for null literals, and handle scalar vector-backed constants without a virtual-table container.

Connect the existing JVM NTZ literal node to the literal factory and nested type handling. Include the NTZ type mapping required by independent literal and Values round trips, with dedicated native and Spark 4.1 regression coverage.

Follow-up to apache#12967 (comment)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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