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https://issues.apache.org/jira/browse/SPARK-17775?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon updated SPARK-17775:
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Labels: bulk-closed (was: )
> pyspark: take(num) failed, but collect() worked for big dataset
> ---------------------------------------------------------------
>
> Key: SPARK-17775
> URL: https://issues.apache.org/jira/browse/SPARK-17775
> Project: Spark
> Issue Type: Bug
> Environment: Spark:1.6.1
> Python 2.7.12 :: Anaconda 4.1.1 (64-bit)
> Windows 7
> One machine
> Reporter: Rick Lin
> Priority: Major
> Labels: bulk-closed
>
> Hi, all:
> I ran one dataset with 39,501 data drew from the table of PostgreSQL DB in
> pyspark.
> The code was as:
> cur1.execute("select id from users")
> users = cur1.fetchall()
> users_rdd = sc.parallelize(users)
> users_rdd.take(1)
> where the error message was as:
> Py4JJavaError: An error occurred while calling
> z:org.apache.spark.api.python.PythonRDD.runJob.
> : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
> in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0
> (TID 0, localhost): java.net.SocketException: Connection reset by peer:
> socket write error
> However, when i changed from take(1) to collect(), it worked, as:
> [[25],
> [1439],
> ...
> ]
> When I ran the same code for a small dataset, here take(1) and collect()
> worked.
> I don't know why this happened and how to fix this problem for a big dataset?
> Could you help me to deal with this problem?
> Thanks
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