[SPARK-57775][SQL][4.2] Return one row for GROUP BY GROUPING SETS (()) over empty input#57134
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[SPARK-57775][SQL][4.2] Return one row for GROUP BY GROUPING SETS (()) over empty input#57134uros-b wants to merge 2 commits into
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Co-authored-by: Isaac
dongjoon-hyun
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When we introduce a breaking change forcefully like this, we need to update the SQL migration guide too, @uros-b .
cc @huaxingao since this is a correctness issue
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Thank you for the review @dongjoon-hyun, PTAL again.
Adding @huaxingao too, for 4.2 backport review.
Also, waiting for CI.
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also cc @MaxGekk @cloud-fan who reviewed the original PR (#56891) |
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| - Since Spark 4.2, when a SQL UDF has a parameter whose name matches a parameterless built-in function (`current_user`, `current_date`, `current_time`, `current_timestamp`, `user`, `session_user`, `grouping__id`), a bare reference to that name in the function body resolves to the built-in function instead of the parameter, matching the documented name resolution rules. Rename the parameter to avoid the collision, or set `spark.sql.legacy.allowUdfParameterToShadowParameterlessFunction` to `true` to restore the previous behavior. | ||
| - Since Spark 4.2, `SET CATALOG <name>` resolves a bare (unquoted) name as a session variable first, using the variable's value as the catalog name when such a variable exists, and otherwise treats the name as a literal catalog name. Use a string literal (`SET CATALOG 'name'`) to force it to be interpreted literally. | ||
| - Since Spark 4.2, when an error occurs while collecting observed metrics, `Observation.get` raises the underlying exception (for example, `SparkRuntimeException` in Scala or `PySparkException` in Python) instead of silently returning an empty result. Add error handling if your code relied on receiving an empty result on failure. | ||
| - Since Spark 4.2, `GROUP BY GROUPING SETS (())` (and the equivalent empty `GROUP BY CUBE()` / `GROUP BY ROLLUP()`) is treated as a grand total and returns one row over empty input, matching an aggregation with no `GROUP BY` clause; previously it returned no rows. To restore the previous behavior, set `spark.sql.analyzer.lowerEmptyGroupingSetToGlobalAggregate.enabled` to `false`. |
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if we decided to backport to 4.2, we should remove the migration guide in 4.2 to 4.3 section, as we don't need to duplicate it in two versions. (with a followup master branch pr)
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Jul 9, 2026
| val LOWER_EMPTY_GROUPING_SET_TO_GLOBAL_AGGREGATE = | ||
| buildConf("spark.sql.analyzer.lowerEmptyGroupingSetToGlobalAggregate.enabled") | ||
| .internal() | ||
| .version("4.2.0") |
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ditto, need a followup master branch to correct the conf version
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What changes were proposed in this pull request?
Note: this is a 4.2 backport of #56891.
Lower the single-empty-grouping-set case to a global
Aggregate(no grouping expressions, noExpand) inGroupingAnalyticsTransformer, so it returns one (grand total) row over empty input, matching theGROUP BY-less form and the SQL standard.grouping_id()folds to the constant0, andgrouping()/grouping_id()inHAVING/ORDER BYresolve against that constant. The fix lands in both the legacy fixed-point analyzer and the single-pass resolver, which shareGroupingAnalyticsTransformer.Why are the changes needed?
GROUP BY GROUPING SETS (())is a grand total, semantically identical to an aggregation with noGROUP BYclause. It was lowered to a groupedAggregateover anExpand(grouping byspark_grouping_id), so over empty input it returned zero rows instead of one. The same defect affected the equivalent emptyGROUP BY CUBE()andGROUP BY ROLLUP(), which also lower to a single empty grouping set.Does this PR introduce any user-facing change?
Yes, the new (correct) behavior is gated by an internal SQL config,
spark.sql.analyzer.lowerEmptyGroupingSetToGlobalAggregate.enabled(default true). When set to false, lowering reverts to the legacyExpand-based form (zero rows over empty input). The flag gates all three decision points (the transformer lowering and thegrouping_id()resolution in each analyzer) so the off state reproduces pre-fix behavior identically in both analyzers.How was this patch tested?
Tested via golden cases in
grouping_set.sql(empty-input grand total,grouping_id()in SELECT/HAVING/ORDER BY,grouping()rejection, non-empty input), flag-off coverage ingrouping_set_grand_total_disabled.sql, the regeneratedgroup-analyticsgolden file, andResolveGroupingAnalyticsSuite.Was this patch authored or co-authored using generative AI tooling?
Generated-by: Opus 4.8