GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/14947
[SPARK-17388][SQL] Support for inferring type date/timestamp/decimal for
partition column
## What changes were proposed in this pull request?
Currently, Spark only supports to infer `IntegerType`, `LongType`,
`DoubleType` and `StringType`.
`DecimalType` is being tried but it seems it never infers type as
`DecimalType` as `DoubleType` is being tried first.
Also, `DateType` and `TimestampType` can be inferred. It seems it is a
pretty common to use both for a partition column.
It'd be great if they can be inferred as both rather than just `StringType`.
This PR fixes the incorrect `DecimalType` try and also adds the support for
both `DateType` and `TimestampType` for inferring partition column type.
## How was this patch tested?
Unit tests in `ParquetPartitionDiscoverySuite`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/HyukjinKwon/spark SPARK-17388
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14947.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 #14947
----
commit b7aa3a3ac045ead46d8ecfc1882d54a1f4dd1c37
Author: hyukjinkwon <[email protected]>
Date: 2016-09-03T06:47:57Z
Support for inferring type date/timestamp/decimal for partition column
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