cloud-fan commented on a change in pull request #24595:
[SPARK-20774][SPARK-27036][CORE] Cancel the running broadcast execution on
BroadcastTimeout
URL: https://github.com/apache/spark/pull/24595#discussion_r284072112
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/BroadcastExchangeExec.scala
##########
@@ -67,68 +70,74 @@ case class BroadcastExchangeExec(
@transient
private lazy val relationFuture: Future[broadcast.Broadcast[Any]] = {
- // broadcastFuture is used in "doExecute". Therefore we can get the
execution id correctly here.
+ // relationFuture is used in "doExecute". Therefore we can get the
execution id correctly here.
val executionId =
sparkContext.getLocalProperty(SQLExecution.EXECUTION_ID_KEY)
- Future {
- // This will run in another thread. Set the execution id so that we can
connect these jobs
- // with the correct execution.
- SQLExecution.withExecutionId(sqlContext.sparkSession, executionId) {
- try {
- val beforeCollect = System.nanoTime()
- // Use executeCollect/executeCollectIterator to avoid conversion to
Scala types
- val (numRows, input) = child.executeCollectIterator()
- if (numRows >= 512000000) {
- throw new SparkException(
- s"Cannot broadcast the table with 512 million or more rows:
$numRows rows")
- }
-
- val beforeBuild = System.nanoTime()
- longMetric("collectTime") += NANOSECONDS.toMillis(beforeBuild -
beforeCollect)
-
- // Construct the relation.
- val relation = mode.transform(input, Some(numRows))
-
- val dataSize = relation match {
- case map: HashedRelation =>
- map.estimatedSize
- case arr: Array[InternalRow] =>
- arr.map(_.asInstanceOf[UnsafeRow].getSizeInBytes.toLong).sum
- case _ =>
- throw new SparkException("[BUG] BroadcastMode.transform returned
unexpected type: " +
- relation.getClass.getName)
+ val task = new Callable[broadcast.Broadcast[Any]]() {
+ override def call(): broadcast.Broadcast[Any] = {
+ // This will run in another thread. Set the execution id so that we
can connect these jobs
+ // with the correct execution.
+ SQLExecution.withExecutionId(sqlContext.sparkSession, executionId) {
+ try {
+ sparkContext.setJobGroup(runId.toString, s"broadcast exchange
(runId $runId)",
Review comment:
let's add a comment to explain why we set up a job group here. There is no
other public API that can cancel a specific job AFAIK.
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