GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/14786
[SPARK-17212][SQL] TypeCoercion supports widening conversion between
DateType and TimestampType
## What changes were proposed in this pull request?
Currently, type-widening does not work between `TimestampType` and
`DateType`.
This applies to `SetOperation`, `Union`, `In`, `CaseWhen`, `Greatest`,
`Leatest`, `CreateArray`, `CreateMap` and `Coalesce`.
For a simple example,
```
Seq(Tuple2(new Timestamp(0), new Date(0))).toDF("a",
"b").selectExpr("greatest(a, b)").show()
```
shows below:
```
cannot resolve 'greatest(`a`, `b`)' due to data type mismatch: The
expressions should all have the same type, got GREATEST(timestamp, date)
```
or union as below:
```scala
val a = Seq(Tuple1(new Timestamp(0))).toDF()
val b = Seq(Tuple1(new Date(0))).toDF()
a.union(b).show()
```
shows below:
```
Union can only be performed on tables with the compatible column types.
DateType <> TimestampType at the first column of the second table;
```
This PR adds the support for widening `DateType` to `TimestampType`.
## How was this patch tested?
Unit tests in `TypeCoercionSuite`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/HyukjinKwon/spark SPARK-17212
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14786.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 #14786
----
commit d49fbdbacd6b3ced5801ff62afc7ec12a8831028
Author: hyukjinkwon <gurwls...@gmail.com>
Date: 2016-08-24T10:52:20Z
TypeCoercion supports widening conversion between DateType and TimestampType
----
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