GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/14217
[SPARK-16562][SQL] Do not allow downcast in INT32 based types for normal
Parquet reader
## What changes were proposed in this pull request?
Currently, INT32 based types, (`ShortType`, `ByteType`, `IntegerType`) can
be downcasted in any combination. For example, the codes below:
```scala
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()
```
works fine. This should not be allowed.
This only happens when vectorized reader is disabled.
## How was this patch tested?
Unit test in `ParquetIOSuite`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/HyukjinKwon/spark SPARK-16562
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14217.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #14217
----
commit 97303c97e990c12abebf309fe3ab9dd0fc31e515
Author: hyukjinkwon <[email protected]>
Date: 2016-07-15T04:51:44Z
Do not allow downcast in INT32 based types for non-vectorized Parquet reader
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