You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2026/08/19 05:03:00 UTC
[jira] [Updated] (SPARK-58387) OptimizeExpand inserts a de-duplicating pre-aggregate under a non-distinct COUNT, returning the distinct-row count
[ https://issues.apache.org/jira/browse/SPARK-58387?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
ASF GitHub Bot updated SPARK-58387:
-----------------------------------
Labels: correctness pull-request-available (was: correctness)
> OptimizeExpand inserts a de-duplicating pre-aggregate under a non-distinct COUNT, returning the distinct-row count
> ------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-58387
> URL: https://issues.apache.org/jira/browse/SPARK-58387
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 4.2.0
> Reporter: Josh Rosen
> Priority: Major
> Labels: correctness, pull-request-available
>
> This is a report of a correctness bug in the {{OptimizeExpand}} rule introduced by SPARK-56315 (released in 4.2.0). The rule is gated by the internal conf {{spark.sql.optimizer.optimizeExpandRatio}} (default {{-1}} = disabled), so hitting it requires explicit opt-in.
>
> ----
>
> Background:
> * queries with multiple {{COUNT(DISTINCT)}} on different columns are rewritten by {{RewriteDistinctAggregates}} into an {{Expand}} that duplicates each input row once per distinct group.
> * {{OptimizeExpand}} reduces that amplification by inserting a de-duplicating {{Aggregate}} on (grouping keys + distinct columns) beneath the {{{}Expand{}}}.
> * The de-duplication is sound only for pure distinct aggregates (collapsing duplicate rows changes the value of any duplicate-sensitive aggregate computed alongside) and the [conf's own doc|https://github.com/apache/spark/blob/5ce51a624421acceec378e0170da24a8fc2a96eb/sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala#L3003-L3020] states exactly that precondition: _"Only applies to pure distinct aggregates without non-distinct aggregates or FILTER clauses."_
>
> The bug: the guard implementing that precondition tests {_}attributes{_}, not _aggregate functions_ ([OptimizeExpand.scala|https://github.com/apache/spark/blob/5ce51a624421acceec378e0170da24a8fc2a96eb/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/OptimizeExpand.scala#L106]):
> {code:java}
> val innerGroupByAttrs = AttributeSet(innerAgg.groupingExpressions.flatMap(_.references))
> if (!expand.producedAttributes.subsetOf(innerGroupByAttrs)) return false {code}
>
> The reasoning is that a non-distinct aggregate would force an Expand output column outside the inner GROUP BY. That only detects aggregates to which {{RewriteDistinctAggregates}} assigns a dedicated Expand slot.
> Any aggregate that reaches the inner Aggregate as {{count(1)}} — {{{}COUNT(1){}}}, {{{}COUNT(*){}}}, and {{COUNT(col)}} of a non-nullable column (which the rewrite normalizes to {{{}count(1){}}}) — references no attribute at all and always passes the guard:
> ||SQL shape||after RewriteDistinctAggregates||dedicated Expand slot?||guard||result||
> |{{COUNT(1)}} / {{COUNT(*)}}|{{count(1)}}|no|passes|*wrong*|
> |{{{}COUNT(a){}}}, {{a}} non-nullable|normalized to {{count(1)}}|no|passes|*wrong*|
> |{{{}COUNT(a){}}}, {{a}} nullable|{{count(a)}} over its own slot|yes|rejects|correct|
> |{{SUM(a)}}|{{sum(a)}} over its own slot|yes|rejects|correct|
>
> {*}Bug repro{*}:
> {code:java}
> CREATE TABLE oe USING parquet AS SELECT * FROM VALUES (1,5,7),(1,5,7),(1,5,7),(1,6,8),(2,9,9) AS t(k,a,b);
> SET spark.sql.optimizer.optimizeExpandRatio=2;
> SELECT k, COUNT(DISTINCT a), COUNT(DISTINCT b), COUNT(1) FROM oe GROUP BY k ORDER BY k;
> -- outputs: [1,2,2,2], [2,1,1,1] WRONG (expected [1,2,2,4]: k=1 has four rows) {code}
> {{k=1}} has four rows (three copies of {{(1,5,7)}} plus {{{}(1,6,8){}}}), so {{COUNT(1)}} must be 4; the returned 2 is the number of distinct {{(k,a,b)}} rows.
> {{COUNT(*)}} behaves identically. With the conf unset (or the rule excluded) the answer is correct.
>
> The optimized plan shows the inserted pre-aggregate (last {{{}Aggregate [k, a, b]{}}}) feeding the Expand whose downstream {{count(1)}} was supposed to count base rows:
> {code:java}
> Aggregate [k], [k, count(a) FILTER (gid=1), count(b) FILTER (gid=2),
> coalesce(first(count(1)) FILTER (gid=0), 0)]
> +- Aggregate [k, a, b, gid], [k, a, b, gid, count(1)]
> +- Expand [[k,null,null,0], [k,a,null,1], [k,null,b,2]], [k, a, b, gid]
> +- Aggregate [k, a, b], [k, a, b] <- inserted by OptimizeExpand
> +- Relation oe[k,a,b] parquet {code}
> With the rule excluded, the Expand's child is the relation itself and {{count(1)}} is 4.
>
> To fix this: check the inner aggregate's aggregate expressions rather than its grouping references — reject any {{AggregateExpression}} that is non-distinct and not duplicate-agnostic (cf. {{{}EliminateDistinct.isDuplicateAgnostic{}}}, the check {{RemoveRedundantAggregates}} uses for the same soundness question).
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org