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[SPARK-33482][SQL] Fix FileScan canonicalization #31820

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[SPARK-33482][SQL] Fix FileScan canonicalization #31820

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99c1482
[SPARK-33482][SQL] Fix FileScan canonicalization
peter-toth Mar 12, 2021
c0fb9b2
address comments
peter-toth Mar 13, 2021
20624d1
Update sql/core/src/main/scala/org/apache/spark/sql/execution/datasou…
peter-toth Mar 14, 2021
52cc2ca
Update sql/core/src/main/scala/org/apache/spark/sql/execution/datasou…
peter-toth Mar 14, 2021
483686d
revert FileScan.equals change from this PR
peter-toth Mar 16, 2021
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11 changes: 10 additions & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/BatchScanExec.scala
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Expand Up @@ -49,6 +49,15 @@ case class BatchScanExec(
}

override def doCanonicalize(): BatchScanExec = {
this.copy(output = output.map(QueryPlan.normalizeExpressions(_, output)))
val canonicalizedScan = scan match {
case s: FileScan =>
s.withFilters(
QueryPlan.normalizePredicates(s.partitionFilters, output),
QueryPlan.normalizePredicates(s.dataFilters, output))
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This works, but is a bit hacky as it doesn't apply to all the Scan implementations.

I think we should add doc in the Scan interface to explain how the hashCode/equals should be implemented.

case _ => scan
}
this.copy(
output = output.map(QueryPlan.normalizeExpressions(_, output)),
scan = canonicalizedScan)
}
}
24 changes: 24 additions & 0 deletions sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala
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Expand Up @@ -40,6 +40,7 @@ import org.apache.spark.sql.execution.datasources.{LogicalRelation, SchemaColumn
import org.apache.spark.sql.execution.datasources.v2.BatchScanExec
import org.apache.spark.sql.execution.datasources.v2.orc.OrcScan
import org.apache.spark.sql.execution.datasources.v2.parquet.ParquetScan
import org.apache.spark.sql.execution.exchange.ReusedExchangeExec
import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, CartesianProductExec, SortMergeJoinExec}
import org.apache.spark.sql.functions._
import org.apache.spark.sql.internal.SQLConf
Expand Down Expand Up @@ -4065,6 +4066,29 @@ class SQLQuerySuite extends QueryTest with SharedSparkSession with AdaptiveSpark
}
}
}

test("SPARK-33482: Fix FileScan canonicalization") {
withSQLConf(SQLConf.USE_V1_SOURCE_LIST.key -> "") {
withTempPath { path =>
spark.range(5).toDF().write.mode("overwrite").parquet(path.toString)
withTempView("t") {
spark.read.parquet(path.toString).createOrReplaceTempView("t")
val df = sql(
"""
|SELECT *
|FROM t AS t1
|JOIN t AS t2 ON t2.id = t1.id
|JOIN t AS t3 ON t3.id = t2.id
|""".stripMargin)
df.collect()
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do we really need df.collect() here? shouldn't AdaptiveSparkPlanHelper.collect() below take care of going through query plan properly with AQE being enabled?

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Yes, we do need to run the query first and then check the plan as this is an AQE compatible query where ReusedExchangeExec nodes are inserted during execution.

val reusedExchanges = collect(df.queryExecution.executedPlan) {
case r: ReusedExchangeExec => r
}
assert(reusedExchanges.size == 1)
}
}
}
}
}

case class Foo(bar: Option[String])