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https://issues.apache.org/jira/browse/SPARK-21841?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16144540#comment-16144540
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Marcelo Vanzin commented on SPARK-21841:
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"DataSource tables" (those created, in certain cases, with {{saveAsTable}}),
have pretty spotty Hive compatibility. I've run into this in a recent PR
(SPARK-21617) and [~smilegator] suggested having an explicit config added to
ensure compatibility, although I don't think anyone is working on that.
The workaround you have (using DDL SQL commands instead of doing it via Scala
code) is what we have been suggesting to people for a really long time now.
I haven't looked closely at the spec to see whether it covers this, but maybe
this could be called out explicitly in SPARK-15689, which plans to update the
DataSource APIs.
> 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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