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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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Apache Spark reassigned SPARK-16946:
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Assignee: Apache Spark
> 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
> Assignee: Apache Spark
> 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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