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[SPARK-24242][SQL] RangeExec should have correct outputOrdering and outputPartitioning #21291

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viirya wants to merge 11 commits into from
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[SPARK-24242][SQL] RangeExec should have correct outputOrdering and outputPartitioning #21291

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30b42d5
RangeExec should have correct outputOrdering.
viirya May 10, 2018
86c800c
Address comment.
viirya May 10, 2018
6039094
Implement outputPartitioning.
viirya May 10, 2018
015e2ad
Fix tests.
viirya May 11, 2018
3a14bd6
Address comment.
viirya May 11, 2018
59499ad
Remove redundant orderBy.
viirya May 14, 2018
f93738b
Add test for zero partition range.
viirya May 14, 2018
4bcac26
Merge remote-tracking branch 'upstream/master' into SPARK-24242
viirya May 16, 2018
b317777
Make row order deterministic by orderby.
viirya May 16, 2018
f41fc14
Address comment.
viirya May 17, 2018
14a3402
Address comment.
viirya May 18, 2018
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2 changes: 2 additions & 0 deletions sql/core/src/main/scala/org/apache/spark/sql/execution/basicPhysicalOperators.scala
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Expand Up @@ -345,6 +345,8 @@ case class RangeExec(range: org.apache.spark.sql.catalyst.plans.logical.Range)

override val output: Seq[Attribute] = range.output

override def outputOrdering: Seq[SortOrder] = range.outputOrdering
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@cloud-fan cloud-fan May 10, 2018

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since we are here, shall we also implement outputPartitioning?

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@viirya viirya May 10, 2018

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ok.


override lazy val metrics = Map(
"numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output rows"))

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13 changes: 12 additions & 1 deletion sql/core/src/test/scala/org/apache/spark/sql/execution/PlannerSuite.scala
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Expand Up @@ -22,7 +22,7 @@ import org.apache.spark.sql.{execution, Row}
import org.apache.spark.sql.catalyst.InternalRow
import org.apache.spark.sql.catalyst.expressions._
import org.apache.spark.sql.catalyst.plans.{Cross, FullOuter, Inner, LeftOuter, RightOuter}
import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Repartition, Sort}
import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Range, Repartition, Sort}
import org.apache.spark.sql.catalyst.plans.physical._
import org.apache.spark.sql.execution.columnar.InMemoryRelation
import org.apache.spark.sql.execution.exchange.{EnsureRequirements, ReusedExchangeExec, ReuseExchange, ShuffleExchangeExec}
Expand Down Expand Up @@ -621,6 +621,17 @@ class PlannerSuite extends SharedSQLContext {
requiredOrdering = Seq(orderingA, orderingB),
shouldHaveSort = true)
}

test("SPARK-24242: RangeExec should have correct output ordering") {
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@cloud-fan cloud-fan May 14, 2018

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ordering and partitioning

val df = spark.range(10).orderBy("id")
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@cloud-fan cloud-fan May 14, 2018

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why do we put an orderBy in the query?

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@viirya viirya May 14, 2018

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I used it to check Sort elimination. Removed now.

val rangeExec = df.queryExecution.executedPlan.collect {
case r: RangeExec => r
}
val range = df.queryExecution.optimizedPlan.collect {
case r: Range => r
}
assert(rangeExec.head.outputOrdering == range.head.outputOrdering)
}
}

// Used for unit-testing EnsureRequirements
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