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ericm-db
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…pressions in `buildAggExprList` ### What changes were proposed in this pull request? Trim aliases before matching Sort/Having/Filter expressions with semantically equal expression from the Aggregate below in `buildAggExprList` ### Why are the changes needed? For a query like: ``` SELECT course, year, GROUPING(course) FROM courseSales GROUP BY CUBE(course, year) ORDER BY GROUPING(course) ``` Plan after `ResolveReferences` and before `ResolveAggregateFunctions` looks like: ``` !Sort [cast((shiftright(tempresolvedcolumn(spark_grouping_id#18L, spark_grouping_id, false), 1) & 1) as tinyint) AS grouping(course)#22 ASC NULLS FIRST], true +- Aggregate [course#19, year#20, spark_grouping_id#18L], [course#19, year#20, cast((shiftright(spark_grouping_id#18L, 1) & 1) as tinyint) AS grouping(course)#21 AS grouping(course)#15] .... ``` Because aggregate list has `Alias(Alias(cast((shiftright(spark_grouping_id#18L, 1) & 1) as tinyint))` expression from `SortOrder` won't get matched as semantically equal and it will result in adding an unnecessary `Project`. By stripping inner aliases from aggregate list (that are going to get removed anyways in `CleanupAliases`) we can match `SortOrder` expression and resolve it as `grouping(course)#15` ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Existing tests ### Was this patch authored or co-authored using generative AI tooling? No Closes apache#51339 from mihailotim-db/mihailotim-db/fix_inner_aliases_semi_structured. Authored-by: Mihailo Timotic <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
ericm-db
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Aug 26, 2025
…onicalized expressions
### What changes were proposed in this pull request?
Make PullOutNonDeterministic use canonicalized expressions to dedup group and aggregate expressions. This affects pyspark udfs in particular. Example:
```
from pyspark.sql.functions import col, avg, udf
pythonUDF = udf(lambda x: x).asNondeterministic()
spark.range(10)\
.selectExpr("id", "id % 3 as value")\
.groupBy(pythonUDF(col("value")))\
.agg(avg("id"), pythonUDF(col("value")))\
.explain(extended=True)
```
Currently results in a plan like this:
```
Aggregate [_nondeterministic#15](#15), [_nondeterministic#15 AS dummyNondeterministicUDF(value)#12, avg(id#0L) AS avg(id)#13, dummyNondeterministicUDF(value#6L)#8 AS dummyNondeterministicUDF(value)#14](#15%20AS%20dummyNondeterministicUDF(value)#12,%20avg(id#0L)%20AS%20avg(id)#13,%20dummyNondeterministicUDF(value#6L)#8%20AS%20dummyNondeterministicUDF(value)#14)
+- Project [id#0L, value#6L, dummyNondeterministicUDF(value#6L)#7 AS _nondeterministic#15](#0L,%20value#6L,%20dummyNondeterministicUDF(value#6L)#7%20AS%20_nondeterministic#15)
+- Project [id#0L, (id#0L % cast(3 as bigint)) AS value#6L](#0L,%20(id#0L%20%%20cast(3%20as%20bigint))%20AS%20value#6L)
+- Range (0, 10, step=1, splits=Some(2))
```
and then it throws:
```
[[MISSING_AGGREGATION] The non-aggregating expression "value" is based on columns which are not participating in the GROUP BY clause. Add the columns or the expression to the GROUP BY, aggregate the expression, or use "any_value(value)" if you do not care which of the values within a group is returned. SQLSTATE: 42803
```
- how canonicalized fixes this:
- nondeterministic PythonUDF expressions always have distinct resultIds per udf
- The fix is to canonicalize the expressions when matching. Canonicalized means that we're setting the resultIds to -1, allowing us to dedup the PythonUDF expressions.
- for deterministic UDFs, this rule does not apply and "Post Analysis" batch extracts and deduplicates the expressions, as expected
### Why are the changes needed?
- the output of the query with the fix applied still makes sense - the nondeterministic UDF is invoked only once, in the project.
### Does this PR introduce _any_ user-facing change?
Yes, it's additive, it enables queries to run that previously threw errors.
### How was this patch tested?
- added unit test
### Was this patch authored or co-authored using generative AI tooling?
No
Closes apache#52061 from benrobby/adhoc-fix-pull-out-nondeterministic.
Authored-by: Ben Hurdelhey <[email protected]>
Signed-off-by: Wenchen Fan <[email protected]>
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What changes were proposed in this pull request?
Why are the changes needed?
Does this PR introduce any user-facing change?
How was this patch tested?
Was this patch authored or co-authored using generative AI tooling?