[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

2 files changed, 72 insertions, 4 deletions

diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala
index 7e6d770314..3314e15477 100755
--- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala
+++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala
@@ -22,6 +22,7 @@ import java.sql.{Date, Timestamp}
 import org.apache.spark.sql.catalyst.types.decimal.Decimal
 
 import scala.language.implicitConversions
+import scala.reflect.runtime.universe.{TypeTag, typeTag}
 
 import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
 import org.apache.spark.sql.catalyst.expressions._
@@ -285,4 +286,62 @@ package object dsl {
       def writeToFile(path: String) = WriteToFile(path, logicalPlan)
     }
   }
+
+  case class ScalaUdfBuilder[T: TypeTag](f: AnyRef) {
+    def call(args: Expression*) = ScalaUdf(f, ScalaReflection.schemaFor(typeTag[T]).dataType, args)
+  }
+
+  // scalastyle:off
+  /** functionToUdfBuilder 1-22 were generated by this script
+
+    (1 to 22).map { x =>
+      val argTypes = Seq.fill(x)("_").mkString(", ")
+      s"implicit def functionToUdfBuilder[T: TypeTag](func: Function$x[$argTypes, T]) = ScalaUdfBuilder(func)"
+    }
+  */
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function1[_, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function2[_, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function3[_, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function4[_, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function5[_, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function6[_, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function7[_, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function8[_, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function9[_, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function10[_, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function11[_, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function12[_, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function13[_, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+
+  implicit def functionToUdfBuilder[T: TypeTag](func: Function22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, T]) = ScalaUdfBuilder(func)
+  // scalastyle:on
 }
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala
index 45e58afe9d..e70ad891ee 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DslQuerySuite.scala
@@ -19,14 +19,13 @@ package org.apache.spark.sql
 
 import org.apache.spark.sql.catalyst.analysis._
 import org.apache.spark.sql.catalyst.expressions._
-import org.apache.spark.sql.catalyst.plans._
-import org.apache.spark.sql.test._
 
 /* Implicits */
-import TestSQLContext._
+import org.apache.spark.sql.catalyst.dsl._
+import org.apache.spark.sql.test.TestSQLContext._
 
 class DslQuerySuite extends QueryTest {
-  import TestData._
+  import org.apache.spark.sql.TestData._
 
   test("table scan") {
     checkAnswer(
@@ -216,4 +215,14 @@ class DslQuerySuite extends QueryTest {
       (4, "d") :: Nil)
     checkAnswer(lowerCaseData.intersect(upperCaseData), Nil)
   }
+
+  test("udf") {
+    val foo = (a: Int, b: String) => a.toString + b
+
+    checkAnswer(
+      // SELECT *, foo(key, value) FROM testData
+      testData.select(Star(None), foo.call('key, 'value)).limit(3),
+      (1, "1", "11") :: (2, "2", "22") :: (3, "3", "33") :: Nil
+    )
+  }
 }