[ https://issues.apache.org/jira/browse/SPARK-28699?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun updated SPARK-28699: ---------------------------------- Affects Version/s: 2.3.3 2.4.3 > Cache an indeterminate RDD could lead to incorrect result while stage rerun > --------------------------------------------------------------------------- > > Key: SPARK-28699 > URL: https://issues.apache.org/jira/browse/SPARK-28699 > Project: Spark > Issue Type: Bug > Components: Spark Core > Affects Versions: 2.3.3, 3.0.0, 2.4.3 > Reporter: Yuanjian Li > Priority: Blocker > Labels: correctness > > It's another case for the indeterminate stage/RDD rerun while stage rerun > happened. In the CachedRDDBuilder. > We can reproduce this by the following code, thanks to Tyson for reporting > this! > > {code:scala} > import scala.sys.process._ > import org.apache.spark.TaskContext > val res = spark.range(0, 10000 * 10000, 1).map{ x => (x % 1000, x)} > // kill an executor in the stage that performs repartition(239) > val df = res.repartition(113).cache.repartition(239).map { x => > if (TaskContext.get.attemptNumber == 0 && TaskContext.get.partitionId < 1 && > TaskContext.get.stageAttemptNumber == 0) { > throw new Exception("pkill -f -n java".!!) > } > x > } > val r2 = df.distinct.count() > {code} -- This message was sent by Atlassian Jira (v8.3.2#803003) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org