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From "Thomas Graves (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-21841) Spark SQL doesn't pick up column added in hive when table created with saveAsTable
Date Tue, 29 Aug 2017 14:43:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16145399#comment-16145399
] 

Thomas Graves commented on SPARK-21841:
---------------------------------------

Oh no I guess that is explicit check in spark 2.1:
 if (source.toLowerCase == DDLUtils.HIVE_PROVIDER) {
      throw new AnalysisException("Cannot create hive serde table with saveAsTable API")
    }

Perhaps this is only supported in spark 2.2?

> Spark SQL doesn't pick up column added in hive when table created with saveAsTable
> ----------------------------------------------------------------------------------
>
>                 Key: SPARK-21841
>                 URL: https://issues.apache.org/jira/browse/SPARK-21841
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.1.0, 2.2.0
>            Reporter: Thomas Graves
>
> If you create a table in Spark sql but then you modify the table in hive to add a column,
spark sql doesn't pick up the new column.
> Basic example:
> {code}
> t1 = spark.sql("select ip_address from mydb.test_table limit 1")
> t1.show()
> +------------+
> |  ip_address|
> +------------+
> |1.30.25.5|
> +------------+
> t1.write.saveAsTable('mydb.t1')
> In Hive:
> alter table mydb.t1 add columns (bcookie string)
> t1 = spark.table("mydb.t1")
> t1.show()
> +------------+
> |  ip_address|
> +------------+
> |1.30.25.5|
> +------------+
> {code}
> It looks like its because spark sql is picking up the schema from spark.sql.sources.schema.part.0
rather then from hive. 
> Interestingly enough it appears that if you create the table differently like:
> spark.sql("create table mydb.t1 select ip_address from mydb.test_table limit 1") 
> Run your alter table on mydb.t1
> val t1 = spark.table("mydb.t1")  
> Then it works properly.
> It looks like the difference is when it doesn't work spark.sql.sources.provider=parquet
is set.
> Its doing this from createDataSourceTable where provider is parquet.



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