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https://issues.apache.org/jira/browse/SPARK-16946?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-16946.
----------------------------------
    Resolution: Cannot Reproduce

I am resolving this per 
https://github.com/apache/spark/pull/14535#issuecomment-309930981 but I don't 
know which JIRA fixes it. Please fix my change on Resolution if anyone know.

> saveAsTable[append] with different number of columns should throw Exception
> ---------------------------------------------------------------------------
>
>                 Key: SPARK-16946
>                 URL: https://issues.apache.org/jira/browse/SPARK-16946
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>            Reporter: Huaxin Gao
>            Priority: Minor
>
> In HiveContext, if saveAsTable[append] has different number of columns, Spark 
> will throw Exception. 
> e.g.
> {code}
>     test("saveAsTable[append]: too many columns") {
>       withTable("saveAsTable_too_many_columns") {
>         Seq((1, 2)).toDF("i", 
> "j").write.saveAsTable("saveAsTable_too_many_columns")
>         val e = intercept[AnalysisException] {
>           Seq((3, 4, 5)).toDF("i", "j", 
> "k").write.mode("append").saveAsTable("saveAsTable_too_many_columns")
>         }
>         assert(e.getMessage.contains("doesn't match"))
>       }
>     }
> {code}
> However, in SparkSession or SQLContext, if use the above code example, the 
> extra column in the append data will be removed silently without any warning 
> or Exception.  The table becomes
> i    j
> 3  4
> 1  2
> We may want follow the HiveContext behavior and throw Exception



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