[SPARK-23778][CORE] Avoid unneeded shuffle when union gets an empty RDD

## What changes were proposed in this pull request?

When a `union` is invoked on several RDDs of which one is an empty RDD, the result of the operation is a `UnionRDD`. This causes an unneeded extra-shuffle when all the other RDDs have the same partitioning.

The PR ignores incoming empty RDDs in the union method.

## How was this patch tested?

added UT

Author: Marco Gaido <[email protected]>

Closes apache#21333 from mgaido91/SPARK-23778.

Author: mgaido91

core/src/main/scala/org/apache/spark/SparkContext.scala

@@ -1306,11 +1306,12 @@ class SparkContext(config: SparkConf) extends Logging {
 
   /** Build the union of a list of RDDs. */
   def union[T: ClassTag](rdds: Seq[RDD[T]]): RDD[T] = withScope {
-    val partitioners = rdds.flatMap(_.partitioner).toSet
-    if (rdds.forall(_.partitioner.isDefined) && partitioners.size == 1) {
-      new PartitionerAwareUnionRDD(this, rdds)
+    val nonEmptyRdds = rdds.filter(!_.partitions.isEmpty)
+    val partitioners = nonEmptyRdds.flatMap(_.partitioner).toSet
+    if (nonEmptyRdds.forall(_.partitioner.isDefined) && partitioners.size == 1) {
+      new PartitionerAwareUnionRDD(this, nonEmptyRdds)
     } else {
-      new UnionRDD(this, rdds)
+      new UnionRDD(this, nonEmptyRdds)
     }
   }
 

core/src/test/scala/org/apache/spark/rdd/RDDSuite.scala

@@ -154,6 +154,16 @@ class RDDSuite extends SparkFunSuite with SharedSparkContext {
     }
   }
 
+  test("SPARK-23778: empty RDD in union should not produce a UnionRDD") {
+    val rddWithPartitioner = sc.parallelize(Seq(1 -> true)).partitionBy(new HashPartitioner(1))
+    val emptyRDD = sc.emptyRDD[(Int, Boolean)]
+    val unionRDD = sc.union(emptyRDD, rddWithPartitioner)
+    assert(unionRDD.isInstanceOf[PartitionerAwareUnionRDD[_]])
+    val unionAllEmptyRDD = sc.union(emptyRDD, emptyRDD)
+    assert(unionAllEmptyRDD.isInstanceOf[UnionRDD[_]])
+    assert(unionAllEmptyRDD.collect().isEmpty)
+  }
+
   test("partitioner aware union") {
     def makeRDDWithPartitioner(seq: Seq[Int]): RDD[Int] = {
       sc.makeRDD(seq, 1)
@@ -1047,7 +1057,9 @@ class RDDSuite extends SparkFunSuite with SharedSparkContext {
   private class CyclicalDependencyRDD[T: ClassTag] extends RDD[T](sc, Nil) {
     private val mutableDependencies: ArrayBuffer[Dependency[_]] = ArrayBuffer.empty
     override def compute(p: Partition, c: TaskContext): Iterator[T] = Iterator.empty
-    override def getPartitions: Array[Partition] = Array.empty
+    override def getPartitions: Array[Partition] = Array(new Partition {
+      override def index: Int = 0
+    })
     override def getDependencies: Seq[Dependency[_]] = mutableDependencies
     def addDependency(dep: Dependency[_]) {
       mutableDependencies += dep