[SPARK-2053][SQL] Add Catalyst expressions for CASE WHEN.

JIRA ticket: https://issues.apache.org/jira/browse/SPARK-2053

This PR adds support for two types of CASE statements present in Hive. The first type is of the form `CASE WHEN a THEN b [WHEN c THEN d]* [ELSE e] END`, with the semantics like a chain of if statements, which is implemented in `CaseWhen`. The second type is of the form `CASE a WHEN b THEN c [WHEN d THEN e]* [ELSE f] END`, with the semantics like a switch statement on key `a`, which is implemented in `CaseKeyWhen`. 

[This link](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF#LanguageManualUDF-ConditionalFunctions) contains more detailed descriptions on their semantics.

Notes / Open issues:

* Please help look at the two new case classes and check if any implicit contracts / invariants are broken in the implementations. I am not very familiar with them and I currently find them tricky to spot.
* We should decide whether or not a non-boolean condition is allowed in a branch of `CaseWhen`. Hive throws a `SemanticException` for this situation and I think it'd be good to mimic it -- the question is where in the whole Spark SQL pipeline should we signal an exception for such a query.
There isn't a special reason for this. However, the previous `s"CASE($branches)"` would not group the conditions and values together and would just present them in a flattened fashion. So either way we would need some logic to group two adjacent elements. Thoughts?