LantaoJin commented on a change in pull request #25840: [SPARK-29166][SQL] Add
parameters to limit the number of dynamic partitions for data source table
URL: https://github.com/apache/spark/pull/25840#discussion_r326968291
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/SQLHadoopMapReduceCommitProtocol.scala
##########
@@ -63,7 +70,29 @@ class SQLHadoopMapReduceCommitProtocol(
committer = ctor.newInstance()
}
}
+ totalPartitions = new AtomicInteger(0)
logInfo(s"Using output committer class
${committer.getClass.getCanonicalName}")
committer
}
+
+ override def newTaskTempFile(
+ taskContext: TaskAttemptContext, dir: Option[String], ext: String):
String = {
+ val path = super.newTaskTempFile(taskContext, dir, ext)
+ totalPartitions.incrementAndGet()
+ if (dynamicPartitionOverwrite) {
+ if (totalPartitions.get > maxDynamicPartitions) {
Review comment:
> it is the max number of partitions a data source can have at any given time
I don't think so. We should keep the same syntax with Hive. Notice that
**hive.exec.max.dynamic.partitions** (default value being 1000) is the total
number of dynamic partitions could be created by one DML.
https://cwiki.apache.org/confluence/display/Hive/Tutorial#Tutorial-Dynamic-PartitionInsert
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