[CH] Support skewness aggregate function

[navaneethsujith09]

What changes are proposed in this pull request?

Support the skewness aggregate function in the ClickHouse backend:

• Maps Spark's skewness to ClickHouse's skewSamp
• Adds NaN→NULL conversion to match Spark's behavior when fewer than 3 non-null values are present
• Removes skewness from the unsupported function blacklist in CHExpressionUtil.scala

How was this patch tested?

Updated GlutenClickhouseCountDistinctSuite

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

Generated-by: Claude Opus 4.8

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Pull request overview

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This PR appears to add ClickHouse/native handling for Spark’s skewness aggregate and adjusts ClickHouse backend validation and tests accordingly.

Changes:

• Register skewness aggregate mapping to ClickHouse skewSamp in the local engine parser.
• Remove SKEWNESS from the ClickHouse expression validator map (previously always-invalid).
• Update an existing ClickHouse backend test to stop asserting an exception and instead compare results against vanilla Spark.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 2 comments.

File	Description
cpp-ch/local-engine/Parser/aggregate_function_parser/SimpleStatisticsFunctions.cpp	Registers skewness by mapping Spark name to ClickHouse aggregate function.
backends-clickhouse/src/main/scala/org/apache/gluten/utils/CHExpressionUtil.scala	Removes the explicit validator entry that previously forced SKEWNESS to be unsupported.
backends-clickhouse/src/test/scala/org/apache/gluten/execution/GlutenClickhouseCountDistinctSuite.scala	Changes test behavior from expecting failure to result comparison (allowing fallback).

Comments suppressed due to low confidence (1)

backends-clickhouse/src/main/scala/org/apache/gluten/utils/CHExpressionUtil.scala:1

• Removing SKEWNESS -> DefaultValidator() flips skewness from explicitly unsupported (since DefaultValidator returns false) to whatever the map’s default behavior is when an entry is missing. If the goal is to support skewness, it’s more robust to add an explicit validator for SKEWNESS (e.g., numeric input types) rather than relying on implicit defaults, and pair it with a test that confirms the intended backend behavior.

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