GitHub user dongjoon-hyun opened a pull request:
https://github.com/apache/spark/pull/15987
[SPARK-18515][SQL] AlterTableDropPartitions fails for non-string columns
## What changes were proposed in this pull request?
While [SPARK-17732](https://issues.apache.org/jira/browse/SPARK-17732)
improved `PARTITION` specification as a expression, it introduce a regression
which `AlterTableDropPartitions` fails for non-string partitioning columns.
This PR fixes that to use a correct type casting.
```scala
scala> sql("create table tbl_x (a int) partitioned by (p int)")
scala> sql("alter table tbl_x add partition (p=10)")
scala> sql("alter table tbl_x drop partition (p=10)")
scala> sql("alter table tbl_x drop partition (p=10)")
scala.MatchError: (cast(p#8 as double) = 10.0) (of class
org.apache.spark.sql.catalyst.expressions.EqualTo)
```
## How was this patch tested?
Pass the Jenkins tests with new test case.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/dongjoon-hyun/spark SPARK-18515
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/15987.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 #15987
----
commit 970a904c5efc1ff2089162c0ca0acbef3f2ca9db
Author: Dongjoon Hyun <[email protected]>
Date: 2016-11-23T01:34:52Z
[SPARK-18515][SQL] AlterTableDropPartitions fails for non-string columns
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