[jira] [Created] (SPARK-32553) Spark application failed due to stage fatch failed without retry

["wangshengjie (Jira)" <ji...@apache.org>]

wangshengjie created SPARK-32553:
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             Summary: Spark application failed due to stage fatch failed without retry
                 Key: SPARK-32553
                 URL: https://issues.apache.org/jira/browse/SPARK-32553
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 3.0.0, 2.3.4
            Reporter: wangshengjie


We got a exception when running a spark application under spark 2.3.4 and spark 3.0 using conf : *spark.shuffle.useOldFetchProtocol=true*, the application failed due to stage fatch failed and the stage not retry.
code like following:
{code:java}
val Array(input) = args

val sparkConf = new SparkConf().setAppName("Spark Fatch Failed Test")
// for running directly in IDE
sparkConf.setIfMissing("spark.master", "local[2]")
val sc = new SparkContext(sparkConf)

val lines = sc.textFile(input)
  .repartition(1)
  .map(data => data.trim)
  .repartition(1)

val doc = lines.map(data => (data, 1)).reduceByKey(_ + _).collect(){code}
The application DAG like following:
 
!https://i.stack.imgur.com/0TfZW.png!
If stage 3 failed due to fatch failed,  the application will not retry stage 2 and stage 3 and fail the job. Because spark think stage 2 and stage 3 are non-retryable, rdds in stage 2 and stage 3 is *INDETERMINATE.*
 
Actually, if shuffle result belongs to stage 1 exist completely, stage 2 and stage 3 are retryable, because rdds in them is not order-sensitive. If allow stage 2 and stage 3 to retry, we have trouble in handling *DAGScheduler.getMissingParentStages.* And i am not sure if *DAGScheduler.getMissingParentStages* breaks the rule that *INDETERMINATE* rdd non-retryable.
 
I would appreciate it if someone would reply.
 



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