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From "Sreelal S L (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-17621) Accumulator value is doubled when using DataFrame.orderBy()
Date Wed, 21 Sep 2016 08:35:20 GMT

    [ https://issues.apache.org/jira/browse/SPARK-17621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15509213#comment-15509213
] 

Sreelal S L commented on SPARK-17621:
-------------------------------------

Hi Sean, 
Thanks for your quick reply. 
I didnt understand what you meant by "evaluating usersDFwithCount twice". Does creating a
DataFrame from existing RDD fires a extra job. 

One more catch is i am observing this only for orderBy() . 
If i try a groupBy , ie :  counterDF.groupBy("name").count().collect()  the accumulator value
is proper. 
In groupBy case also i create DataFrame from the rdd. 

What could be the difference here. 

 


> 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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