[SPARK-4211][Build] Fixes hive.version in Maven profile hive-0.13.1

instead of `hive.version=0.13.1`.
e.g. mvn -Phive -Phive=0.13.1

Note: `hive.version=0.13.1a` is the default property value. However, when explicitly specifying the `hive-0.13.1` maven profile, the wrong one would be selected.
References:  PR #2685, which resolved a package incompatibility issue with Hive-0.13.1 by introducing a special version Hive-0.13.1a

Author: fi <coderfi@gmail.com>

Closes #3072 from coderfi/master and squashes the following commits:

7ca4b1e [fi] Fixes the `hive-0.13.1` maven profile referencing `hive.version=0.13.1` instead of the Spark compatible `hive.version=0.13.1a` Note: `hive.version=0.13.1a` is the default version. However, when explicitly specifying the `hive-0.13.1` maven profile, the wrong one would be selected. e.g. mvn -Phive -Phive=0.13.1 See PR #2685
[SPARK-4207][SQL] Query which has syntax like 'not like' is not working in Spark SQL

Queries which has 'not like' is not working spark sql.

sql("SELECT * FROM records where value not like 'val%'")
 same query works in Spark HiveQL

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #3075 from ravipesala/SPARK-4207 and squashes the following commits:

35c11e7 [ravipesala] Supported 'not like' syntax in sql
[SPARK-3594] [PySpark] [SQL] take more rows to infer schema or sampling

This patch will try to infer schema for RDD which has empty value (None, [], {}) in the first row. It will try first 100 rows and merge the types into schema, also merge fields of StructType together. If there is still NullType in schema, then it will show an warning, tell user to try with sampling.

If sampling is presented, it will infer schema from all the rows after sampling.

Also, add samplingRatio for jsonFile() and jsonRDD()

Author: Davies Liu <davies.liu@gmail.com>
Author: Davies Liu <davies@databricks.com>

Closes #2716 from davies/infer and squashes the following commits:

e678f6d [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
34b5c63 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
567dc60 [Davies Liu] update docs
9767b27 [Davies Liu] Merge branch 'master' into infer
e48d7fb [Davies Liu] fix tests
29e94d5 [Davies Liu] let NullType inherit from PrimitiveType
ee5d524 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
540d1d5 [Davies Liu] merge fields for StructType
f93fd84 [Davies Liu] add more tests
3603e00 [Davies Liu] take more rows to infer schema, or infer the schema by sampling the RDD
[SPARK-4202][SQL] Simple DSL support for Scala UDF

This feature is based on an offline discussion with mengxr, hopefully can be useful for the new MLlib pipeline API.

For the following test snippet

```scala
case class KeyValue(key: Int, value: String)
val testData = sc.parallelize(1 to 10).map(i => KeyValue(i, i.toString)).toSchemaRDD
def foo(a: Int, b: String) => a.toString + b
```

the newly introduced DSL enables the following syntax

```scala
import org.apache.spark.sql.catalyst.dsl._
testData.select(Star(None), foo.call('key, 'value) as 'result)
```

which is equivalent to

```scala
testData.registerTempTable("testData")
sqlContext.registerFunction("foo", foo)
sql("SELECT *, foo(key, value) AS result FROM testData")
```

Author: Cheng Lian <lian@databricks.com>

Closes #3067 from liancheng/udf-dsl and squashes the following commits:

f132818 [Cheng Lian] Adds DSL support for Scala UDF