Jakub Leś created SPARK-38137:
---------------------------------
Summary: Repartition+Shuffle+ non deterministic function leads to
bad results
Key: SPARK-38137
URL: https://issues.apache.org/jira/browse/SPARK-38137
Project: Spark
Issue Type: Bug
Components: Spark Core
Affects Versions: 3.2.1, 3.1.1
Reporter: Jakub Leś
Hi,
The results when using a non deterministic function in repartition (like rand)
leads into incorrect results.
Reproduce: (correct)
{code:java}
// code placeholder
import scala.sys.process._
import org.apache.spark.TaskContext
import org.apache.spark.sql.functions.randval res = spark.range(0, 100 * 100,
1).repartition(200).map { x =>
x
}.repartition(200).map { x =>
if (TaskContext.get.attemptNumber == 0 && TaskContext.get.partitionId < 2) {
throw new Exception("pkill -f java".!!)
}
x
}
res.distinct().count() {code}
The correct result 10000
Reproduce: (bad)
{code:java}
// code placeholder
import scala.sys.process._
import org.apache.spark.TaskContext
import org.apache.spark.sql.functions.randval res = spark.range(0, 100 * 100,
1).repartition(200).map { x =>
x
}.repartition(10, Array(rand):_*).map { x =>
if (TaskContext.get.attemptNumber == 0 && TaskContext.get.partitionId < 2) {
throw new Exception("pkill -f java".!!)
}
x
}
res.distinct().count() {code}
The bad result 9396
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