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https://issues.apache.org/jira/browse/SPARK-19699?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15882385#comment-15882385
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Genmao Yu commented on SPARK-19699:
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Good catch! Maybe we can add {{rdd.id}} or something else. [~cloud_fan]
!https://cloud.githubusercontent.com/assets/7402327/23299586/02f7b73a-fabd-11e6-8daf-321ca9ab5ed0.png!
> createOrReplaceTable does not always replace an existing table of the same
> name
> -------------------------------------------------------------------------------
>
> Key: SPARK-19699
> URL: https://issues.apache.org/jira/browse/SPARK-19699
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.1.0
> Reporter: Barry Becker
> Priority: Minor
>
> There are cases when dataframe.createOrReplaceTempView does not replace an
> existing table with the same name.
> Please also refer to my [related stack-overflow
> post|http://stackoverflow.com/questions/42371690/in-spark-2-1-how-come-the-dataframe-createoreplacetemptable-does-not-replace-an].
> To reproduce, do
> {code}
> df.collect()
> df.createOrReplaceTempView("foo1")
> df.sqlContext.cacheTable("foo1")
> {code}
> with one dataframe, and then do exactly the same thing with a different
> dataframe. Then look in the storage tab in the spark UI and see multiple
> entries for "foo1" in the "RDD Name" column.
> Maybe I am misunderstanding, but this causes 2 apparent problems
> 1) How do you know which table will be retrieved with
> sqlContext.table("foo1") ?
> 2) The duplicate entries represent a memory leak.
> I have tried calling dropTempTable(existingName) first, but then have
> occasionally seen a FAILFAST error when trying to use the table. It's as if
> the dropTempTable is not synchronous, but maybe I am doing something wrong.
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