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https://issues.apache.org/jira/browse/SPARK-16562?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-16562.
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Resolution: Not A Bug
This seems not a problem to me. Please my PR linked.
> Do not allow downcast in INT32 based types for non-vectorized Parquet reader
> ----------------------------------------------------------------------------
>
> Key: SPARK-16562
> URL: https://issues.apache.org/jira/browse/SPARK-16562
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 2.0.0
> Reporter: Hyukjin Kwon
> Priority: Minor
>
> Currently, INT32 based types, ({{ShortType}}, {{ByteType}}, {{IntegerType}}
> can be downcasted in any combination. For example, the codes below:
> {code}
> val path = "/tmp/test.parquet"
> val data = (1 to 4).map(Tuple1(_.toInt))
> data.toDF("a").write.parquet(path)
> val schema = StructType(StructField("a", ShortType, true) :: Nil)
> spark.read.schema(schema).parquet(path).show()
> {code}
> work fine.
> This should not be allowed.
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