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https://issues.apache.org/jira/browse/SPARK-16741?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15394501#comment-15394501
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Zoltan Fedor commented on SPARK-16741:
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Thanks Sean. I agree, it is debatable whether this is a bug or not.
My thinking is that as I don't see a scenario where jdbc.write() would need to
be running in speculative mode, it should automatically turn off speculative
mode when you call jdbc.write(). jdbc.write() not turning speculative mode off
automatically - whether that is a bug or a feature, is debatable. I am okey to
change this to a feature request.
> spark.speculation causes duplicate rows in df.write.jdbc()
> ----------------------------------------------------------
>
> Key: SPARK-16741
> URL: https://issues.apache.org/jira/browse/SPARK-16741
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.6.2
> Environment: PySpark 1.6.2, Oracle Linux 6.5, Oracle 11.2
> Reporter: Zoltan Fedor
>
> Since a fix added to Spark 1.6.2 we can write string data back into an Oracle
> database, so I went to try it out and found that rows showed up duplicated in
> the database table after they got inserted into our Oracle database.
> The code we use it very simple:
> df = sqlContext.sql("SELECT * FROM example_temp_table")
> df.write.jdbc("jdbc:oracle:thin:"+connection_script, "target_table")
> The data in the 'target_table' in the database has twice as many rows as the
> 'df' dataframe in SparkSQL.
> After some investigation it turns out that this is caused by our
> spark.speculation setting is being set to True.
> As soon as we turned this off, there were no more duplicates generated.
> This somewhat makes sense - spark.speculation causes the map jobs to run 2
> copies - resulting in every row being inserted into our Oracle databases
> twice.
> Probably the df.jdbc.write() method does not consider a Spark context running
> in speculative mode, hence the inserts coming from the speculative map also
> get inserted - causing to have every record inserted twice.
> Likely that this bug is independent from the database type (we use Oracle)
> and whether PySpark is used or Scala or Java.
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