dbtsai commented on a change in pull request #24865: [SPARK-27100][SQL]
dag-scheduler-event-loop" java.lang.StackOverflowError
URL: https://github.com/apache/spark/pull/24865#discussion_r295944426
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File path:
sql/core/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala
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@@ -735,4 +745,92 @@ abstract class BucketedReadSuite extends QueryTest with
SQLTestUtils {
df1.groupBy("j").agg(max("k")))
}
}
+
+ // A test with a partition where the number of files in the partition is
+ // large. tests for the condition where the serialization of such a task
may result in a stack
+ // overflow if the files list is stored in a recursive data structure
+ test("SPARK-27100 stack overflow: read data with large partitions") {
+ // Need a large number of files in the partition for the overflow
+ val numFilesInPartition = 100000
+
+ def getInputRDD(sparkSession: SparkSession, isBucketed: Boolean):
RDD[InternalRow] = {
+ val partitionValues = InternalRow.apply(Array("a"))
+
+ val schema = new StructType()
+ val fakeHadoopFsRelation =
+ HadoopFsRelation(null, schema, schema, null, new ParquetFileFormat,
null)(sparkSession)
+ val optionalBucketSet = null
+ val files = (0 until numFilesInPartition).toStream.map { i =>
+ new FileStatus(10, false, 1, 512, 1000, new Path(s"file${i}_0.zzz"))
+ }
+ val partitionDirectory = PartitionDirectory(partitionValues, files)
+
+ val fileSource = FileSourceScanExec(fakeHadoopFsRelation,
+ null,
+ schema,
Review comment:
this should be two spaces indentation.
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