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[SPARK-32816][SQL] Fix analyzer bug when aggregating multiple distinct DECIMAL columns #29673

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[SPARK-32816][SQL] Fix analyzer bug when aggregating multiple distinct DECIMAL columns #29673

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b1ce4b5
[SPARK-32816][SQL] Fix analyzer bug when aggregating multiple distinc…
linhongliu-db Sep 8, 2020
4df4f7c
fix comments
linhongliu-db Sep 9, 2020
737f996
use temp view
linhongliu-db Sep 10, 2020
f2111df
change to SQLQueryTestSuite
linhongliu-db Sep 10, 2020
8510ff9
code clean
linhongliu-db Sep 11, 2020
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3 changes: 2 additions & 1 deletion sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -142,7 +142,6 @@ abstract class Optimizer(catalogManager: CatalogManager)
RewriteNonCorrelatedExists,
ComputeCurrentTime,
GetCurrentDatabaseAndCatalog(catalogManager),
RewriteDistinctAggregates,
ReplaceDeduplicateWithAggregate) ::
//////////////////////////////////////////////////////////////////////////////////////////
// Optimizer rules start here
Expand Down Expand Up @@ -196,6 +195,8 @@ abstract class Optimizer(catalogManager: CatalogManager)
EliminateSorts) :+
Batch("Decimal Optimizations", fixedPoint,
DecimalAggregates) :+
Batch("Distinct Aggregate Rewrite", Once,
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@cloud-fan cloud-fan Sep 8, 2020

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can we add a comment to say: this batch must be run after "Decimal Optimizations", as "Decimal Optimizations" may change the aggregate distinct column?

RewriteDistinctAggregates) :+
Batch("Object Expressions Optimization", fixedPoint,
EliminateMapObjects,
CombineTypedFilters,
Expand Down
13 changes: 13 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
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Expand Up @@ -2555,6 +2555,19 @@ class DataFrameSuite extends QueryTest
val df = Seq(0.0 -> -0.0).toDF("pos", "neg")
checkAnswer(df.select($"pos" > $"neg"), Row(false))
}

test("SPARK-32816: aggregating multiple distinct DECIMAL columns") {
withTempPath { path =>
spark.range(0, 100, 1, 1)
.selectExpr("id", "cast(id as decimal(9, 0)) as decimal_col")
.write.mode("overwrite")
.parquet(path.getAbsolutePath)
spark.read.parquet(path.getAbsolutePath).createOrReplaceTempView("test_table")
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@TJX2014 TJX2014 Sep 8, 2020

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Seems we need not to write parquet.

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@TJX2014 TJX2014 Sep 8, 2020 •
edited
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val df = spark.range(0, 50000, 1, 1).selectExpr("id", "cast(id as decimal(9, 0)) as ss_ext_list_price")
df.createOrReplaceTempView("test_table")
sql("select avg(distinct ss_ext_list_price), sum(distinct ss_ext_list_price) from test_table").explain
seems enough to reproduce.

checkAnswer(
sql("select avg(distinct decimal_col), sum(distinct decimal_col) from test_table"),
Row(49.5, 4950))
}
}
}

case class GroupByKey(a: Int, b: Int)