[ 
https://issues.apache.org/jira/browse/SPARK-5316?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Andrew Or updated SPARK-5316:
-----------------------------
    Affects Version/s: 1.0.0

> DAGScheduler may make shuffleToMapStage leak if getParentStages failes
> ----------------------------------------------------------------------
>
>                 Key: SPARK-5316
>                 URL: https://issues.apache.org/jira/browse/SPARK-5316
>             Project: Spark
>          Issue Type: Bug
>          Components: Scheduler
>    Affects Versions: 1.0.0
>            Reporter: YanTang Zhai
>
> DAGScheduler may make shuffleToMapStage leak if getParentStages failes.
> If getParentStages has exception for example input path does not exist, 
> DAGScheduler would fail to handle job submission, while shuffleToMapStage may 
> be put some records when getParentStages. However these records in 
> shuffleToMapStage aren't going to be cleaned.
> A simple job as follows:
> {code:java}
> val inputFile1 = ... // Input path does not exist when this job submits
> val inputFile2 = ...
> val outputFile = ...
> val conf = new SparkConf()
> val sc = new SparkContext(conf)
> val rdd1 = sc.textFile(inputFile1)
>                     .flatMap(line => line.split(" "))
>                     .map(word => (word, 1))
>                     .reduceByKey(_ + _, 1)
> val rdd2 = sc.textFile(inputFile2)
>                     .flatMap(line => line.split(","))
>                     .map(word => (word, 1))
>                     .reduceByKey(_ + _, 1)
> try {
>   val rdd3 = new PairRDDFunctions(rdd1).join(rdd2, 1)
>   rdd3.saveAsTextFile(outputFile)
> } catch {
>   case e : Exception =>
>       logError(e)
> }
> // print the information of DAGScheduler's shuffleToMapStage to check
> // whether it still has uncleaned records.
> ...
> {code}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to