[jira] [Resolved] (SPARK-19699) createOrReplaceTable does not always replace an existing table of the same name

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-19699?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-19699.
----------------------------------
    Resolution: Incomplete

> 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
>              Labels: bulk-closed
>
> 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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