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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-8200) Exception in StreamingLinearAlgorithm on Stream with Empty RDD.
Date Wed, 10 Jun 2015 22:28:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-8200?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Sean Owen resolved SPARK-8200.
------------------------------
       Resolution: Fixed
    Fix Version/s: 1.4.1
                   1.5.0

Issue resolved by pull request 6713
[https://github.com/apache/spark/pull/6713]

> Exception in StreamingLinearAlgorithm on Stream with Empty RDD.
> ---------------------------------------------------------------
>
>                 Key: SPARK-8200
>                 URL: https://issues.apache.org/jira/browse/SPARK-8200
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib, Streaming
>    Affects Versions: 1.3.1
>         Environment: Ubuntu 14.04.2 LTS
> Linux 3.13.0-45-generic #74-Ubuntu SMP Tue Jan 13 19:36:28 UTC 2015
> java version "1.8.0_25"
> Java(TM) SE Runtime Environment (build 1.8.0_25-b17)
> Java HotSpot(TM) 64-Bit Server VM (build 25.25-b02, mixed mode)
> Scala code runner version 2.10.4 -- Copyright 2002-2013, LAMP/EPFL
>            Reporter: Paavo Parkkinen
>            Priority: Minor
>             Fix For: 1.5.0, 1.4.1
>
>
> When training a streaming logistic regression model or a streaming linear regression
model, any empty RDDs in a stream will cause an exception.
>   java.lang.UnsupportedOperationException: empty collection
>   at org.apache.spark.rdd.RDD$$anonfun$first$1.apply(RDD.scala:1288)
>   at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
>   at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
>   at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
>   at org.apache.spark.rdd.RDD.first(RDD.scala:1285)
>   at org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm.run(GeneralizedLinearAlgorithm.scala:215)
>   at org.apache.spark.mllib.regression.StreamingLinearAlgorithm$$anonfun$trainOn$1.apply(StreamingLinearAlgorithm.scala:91)
>   at org.apache.spark.mllib.regression.StreamingLinearAlgorithm$$anonfun$trainOn$1.apply(StreamingLinearAlgorithm.scala:85)
>   at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:42)
>   at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:40)



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