[jira] [Commented] (SPARK-17621) Accumulator value is doubled when using DataFrame.orderBy()

["Sean Owen (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-17621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15509168#comment-15509168 ] 

Sean Owen commented on SPARK-17621:
-----------------------------------

I think you've found the issue. You're actually evaluating usersDFwithCount twice here. I think the other one has to do with creating the data frame. So the accumulator is incremented twice.

> Accumulator value is doubled when using DataFrame.orderBy()
> -----------------------------------------------------------
>
>                 Key: SPARK-17621
>                 URL: https://issues.apache.org/jira/browse/SPARK-17621
>             Project: Spark
>          Issue Type: Bug
>          Components: Scheduler, SQL
>    Affects Versions: 2.0.0
>         Environment: Development environment. (Eclipse . Single process) 
>            Reporter: Sreelal S L
>            Priority: Minor
>
> We are tracing the records read by our source using an accumulator.  We do a orderBy on the Dataframe before the output operation. When the job is completed, the accumulator values is becoming double of the expected value . . 
> Below is the sample code i ran . 
> {code} 
>  val sqlContext = SparkSession.builder() 
>       .config("spark.sql.retainGroupColumns", false).config("spark.sql.warehouse.dir", "file:///C:/Test").master("local[*]")
>       .getOrCreate()
>     val sc = sqlContext.sparkContext
>     val accumulator1 = sc.accumulator(0, "accumulator1")
>     val usersDF = sqlContext.read.json("C:\\users.json") //  single row {"name":"sreelal" ,"country":"IND"}
>     val usersDFwithCount = usersDF.rdd.map(x => { accumulator1 += 1; x });
>     val counterDF = sqlContext.createDataFrame(usersDFwithCount, usersDF.schema);
>     val oderedDF = counterDF.orderBy("name")
>     val collected = oderedDF.collect()
>     collected.foreach { x => println(x) }
>     println("accumulator1 : " + accumulator1.value)
>     println("Done");
> {code}
> I have only one row in the users.json file.  I expect accumulator1 to have value 1. But its coming as 2. 
> In the Spark Sql UI , i see two jobs getting generated for the same. 



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