Repository: spark
Updated Branches:
refs/heads/master 626aab79c -> 6987c0679
[SPARK-11009] [SQL] fix wrong result of Window function in cluster mode
Currently, All windows function could generate wrong result in cluster
sometimes.
The root cause is that AttributeReference is called in executor, then id of it
may not be unique than others created in driver.
Here is the script that could reproduce the problem (run in local cluster):
```
from pyspark import SparkContext, HiveContext
from pyspark.sql.window import Window
from pyspark.sql.functions import rowNumber
sqlContext = HiveContext(SparkContext())
sqlContext.setConf("spark.sql.shuffle.partitions", "3")
df = sqlContext.range(1<<20)
df2 = df.select((df.id % 1000).alias("A"), (df.id / 1000).alias('B'))
ws = Window.partitionBy(df2.A).orderBy(df2.B)
df3 = df2.select("client", "date", rowNumber().over(ws).alias("rn")).filter("rn
< 0")
assert df3.count() == 0
```
Author: Davies Liu <[email protected]>
Author: Yin Huai <[email protected]>
Closes #9050 from davies/wrong_window.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/6987c067
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/6987c067
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/6987c067
Branch: refs/heads/master
Commit: 6987c067937a50867b4d5788f5bf496ecdfdb62c
Parents: 626aab7
Author: Davies Liu <[email protected]>
Authored: Tue Oct 13 09:40:36 2015 -0700
Committer: Yin Huai <[email protected]>
Committed: Tue Oct 13 09:43:33 2015 -0700
----------------------------------------------------------------------
.../org/apache/spark/sql/execution/Window.scala | 20 +++++-----
.../spark/sql/hive/HiveSparkSubmitSuite.scala | 41 ++++++++++++++++++++
2 files changed, 51 insertions(+), 10 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/spark/blob/6987c067/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
----------------------------------------------------------------------
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
index f892953..55035f4 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/execution/Window.scala
@@ -145,11 +145,10 @@ case class Window(
// Construct the ordering. This is used to compare the result of
current value projection
// to the result of bound value projection. This is done manually
because we want to use
// Code Generation (if it is enabled).
- val (sortExprs, schema) = exprs.map { case e =>
- val ref = AttributeReference("ordExpr", e.dataType, e.nullable)()
- (SortOrder(ref, e.direction), ref)
- }.unzip
- val ordering = newOrdering(sortExprs, schema)
+ val sortExprs = exprs.zipWithIndex.map { case (e, i) =>
+ SortOrder(BoundReference(i, e.dataType, e.nullable), e.direction)
+ }
+ val ordering = newOrdering(sortExprs, Nil)
RangeBoundOrdering(ordering, current, bound)
case RowFrame => RowBoundOrdering(offset)
}
@@ -205,14 +204,15 @@ case class Window(
*/
private[this] def createResultProjection(
expressions: Seq[Expression]): MutableProjection = {
- val unboundToAttr = expressions.map {
- e => (e, AttributeReference("windowResult", e.dataType, e.nullable)())
+ val references = expressions.zipWithIndex.map{ case (e, i) =>
+ // Results of window expressions will be on the right side of child's
output
+ BoundReference(child.output.size + i, e.dataType, e.nullable)
}
- val unboundToAttrMap = unboundToAttr.toMap
- val patchedWindowExpression =
windowExpression.map(_.transform(unboundToAttrMap))
+ val unboundToRefMap = expressions.zip(references).toMap
+ val patchedWindowExpression =
windowExpression.map(_.transform(unboundToRefMap))
newMutableProjection(
projectList ++ patchedWindowExpression,
- child.output ++ unboundToAttr.map(_._2))()
+ child.output)()
}
protected override def doExecute(): RDD[InternalRow] = {
http://git-wip-us.apache.org/repos/asf/spark/blob/6987c067/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
----------------------------------------------------------------------
diff --git
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
index 5f1660b..10e4ae2 100644
---
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
+++
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/HiveSparkSubmitSuite.scala
@@ -30,6 +30,7 @@ import org.scalatest.time.SpanSugar._
import org.apache.spark._
import org.apache.spark.sql.{SQLContext, QueryTest}
+import org.apache.spark.sql.expressions.Window
import org.apache.spark.sql.hive.test.{TestHive, TestHiveContext}
import org.apache.spark.sql.test.ProcessTestUtils.ProcessOutputCapturer
import org.apache.spark.sql.types.DecimalType
@@ -107,6 +108,16 @@ class HiveSparkSubmitSuite
runSparkSubmit(args)
}
+ test("SPARK-11009 fix wrong result of Window function in cluster mode") {
+ val unusedJar = TestUtils.createJarWithClasses(Seq.empty)
+ val args = Seq(
+ "--class", SPARK_11009.getClass.getName.stripSuffix("$"),
+ "--name", "SparkSQLConfTest",
+ "--master", "local-cluster[2,1,1024]",
+ unusedJar.toString)
+ runSparkSubmit(args)
+ }
+
// NOTE: This is an expensive operation in terms of time (10 seconds+). Use
sparingly.
// This is copied from org.apache.spark.deploy.SparkSubmitSuite
private def runSparkSubmit(args: Seq[String]): Unit = {
@@ -320,3 +331,33 @@ object SPARK_9757 extends QueryTest {
}
}
}
+
+object SPARK_11009 extends QueryTest {
+ import org.apache.spark.sql.functions._
+
+ protected var sqlContext: SQLContext = _
+
+ def main(args: Array[String]): Unit = {
+ Utils.configTestLog4j("INFO")
+
+ val sparkContext = new SparkContext(
+ new SparkConf()
+ .set("spark.ui.enabled", "false")
+ .set("spark.sql.shuffle.partitions", "100"))
+
+ val hiveContext = new TestHiveContext(sparkContext)
+ sqlContext = hiveContext
+
+ try {
+ val df = sqlContext.range(1 << 20)
+ val df2 = df.select((df("id") % 1000).alias("A"), (df("id") /
1000).alias("B"))
+ val ws = Window.partitionBy(df2("A")).orderBy(df2("B"))
+ val df3 = df2.select(df2("A"), df2("B"),
rowNumber().over(ws).alias("rn")).filter("rn < 0")
+ if (df3.rdd.count() != 0) {
+ throw new Exception("df3 should have 0 output row.")
+ }
+ } finally {
+ sparkContext.stop()
+ }
+ }
+}
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