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[SPARK-40245][SQL] Fix FileScan equality check when partition or data filter columns are not read #37693

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[SPARK-40245][SQL] Fix FileScan equality check when partition or data filter columns are not read #37693

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[SPARK-40245][SQL] Fix FileScan equality check when partition or data…
peter-toth Aug 27, 2022
e575547
Merge commit '527ddece8fdbe703dcd239401c97ddb2c6122182' into SPARK-40…
peter-toth Aug 29, 2022
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11 changes: 5 additions & 6 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/FileScan.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -83,15 +83,14 @@ trait FileScan extends Scan
protected def seqToString(seq: Seq[Any]): String = seq.mkString("[", ", ", "]")

private lazy val (normalizedPartitionFilters, normalizedDataFilters) = {
val output = readSchema().toAttributes
val partitionFilterAttributes = AttributeSet(partitionFilters).map(a => a.name -> a).toMap
val dataFiltersAttributes = AttributeSet(dataFilters).map(a => a.name -> a).toMap
val normalizedPartitionFilters = ExpressionSet(partitionFilters.map(
QueryPlan.normalizeExpressions(_,
output.map(a => partitionFilterAttributes.getOrElse(a.name, a)))))
QueryPlan.normalizeExpressions(_, fileIndex.partitionSchema.toAttributes
.map(a => partitionFilterAttributes.getOrElse(a.name, a)))))
val dataFiltersAttributes = AttributeSet(dataFilters).map(a => a.name -> a).toMap
val normalizedDataFilters = ExpressionSet(dataFilters.map(
QueryPlan.normalizeExpressions(_,
output.map(a => dataFiltersAttributes.getOrElse(a.name, a)))))
QueryPlan.normalizeExpressions(_, dataSchema.toAttributes
.map(a => dataFiltersAttributes.getOrElse(a.name, a)))))
(normalizedPartitionFilters, normalizedDataFilters)
}

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30 changes: 30 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Expand Up @@ -4028,6 +4028,36 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
}
}

test("SPARK-40245: Fix FileScan canonicalization when partition or data filter columns are not " +
"read") {
withSQLConf(SQLConf.USE_V1_SOURCE_LIST.key -> "") {
withTempPath { path =>
spark.range(5)
.withColumn("p", $"id" % 2)
.write
.mode("overwrite")
.partitionBy("p")
.parquet(path.toString)
withTempView("t") {
spark.read.parquet(path.toString).createOrReplaceTempView("t")
val df = sql(
"""
|SELECT t1.id, t2.id, t3.id
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@cloud-fan cloud-fan Aug 29, 2022

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do we return wrong result before?

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@peter-toth peter-toth Aug 29, 2022 •
edited
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No, only exchange reuse didn't happen.

|FROM t AS t1
|JOIN t AS t2 ON t2.id = t1.id
|JOIN t AS t3 ON t3.id = t2.id
|WHERE t1.p = 1 AND t2.p = 1 AND t3.p = 1
|""".stripMargin)
df.collect()
val reusedExchanges = collect(df.queryExecution.executedPlan) {
case r: ReusedExchangeExec => r
}
assert(reusedExchanges.size == 1)
}
}
}
}

test("SPARK-35331: Fix resolving original expression in RepartitionByExpression after aliased") {
Seq("CLUSTER", "DISTRIBUTE").foreach { keyword =>
Seq("a", "substr(a, 0, 3)").foreach { expr =>
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