[SPARK-3580][CORE] Add Consistent Method To Get Number of RDD Partitions Across Different Languages

I have tried to address all the comments in pull request #2447.

Note that the second commit (using the new method in all internal code of all components) is quite intrusive and could be omitted.

Author: Jeroen Schot <[email protected]>

Closes #9767 from schot/master.

(cherry picked from commit 128c290)
Signed-off-by: Sean Owen <[email protected]>

Author: Jeroen Schot

core/src/main/scala/org/apache/spark/api/java/JavaRDDLike.scala

@@ -28,6 +28,7 @@ import com.google.common.base.Optional
 import org.apache.hadoop.io.compress.CompressionCodec
 
 import org.apache.spark._
+import org.apache.spark.annotation.Since
 import org.apache.spark.api.java.JavaPairRDD._
 import org.apache.spark.api.java.JavaSparkContext.fakeClassTag
 import org.apache.spark.api.java.JavaUtils.mapAsSerializableJavaMap
@@ -62,6 +63,10 @@ trait JavaRDDLike[T, This <: JavaRDDLike[T, This]] extends Serializable {
   /** Set of partitions in this RDD. */
   def partitions: JList[Partition] = rdd.partitions.toSeq.asJava
 
+  /** Return the number of partitions in this RDD. */
+  @Since("1.6.0")
+  def getNumPartitions: Int = rdd.getNumPartitions
+
   /** The partitioner of this RDD. */
   def partitioner: Optional[Partitioner] = JavaUtils.optionToOptional(rdd.partitioner)
 

core/src/main/scala/org/apache/spark/rdd/RDD.scala

@@ -31,7 +31,7 @@ import org.apache.hadoop.mapred.TextOutputFormat
 
 import org.apache.spark._
 import org.apache.spark.Partitioner._
-import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.annotation.{Since, DeveloperApi}
 import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.partial.BoundedDouble
 import org.apache.spark.partial.CountEvaluator
@@ -242,6 +242,12 @@ abstract class RDD[T: ClassTag](
     }
   }
 
+  /**
+    * Returns the number of partitions of this RDD.
+    */
+  @Since("1.6.0")
+  final def getNumPartitions: Int = partitions.length
+
   /**
    * Get the preferred locations of a partition, taking into account whether the
    * RDD is checkpointed.

core/src/test/java/org/apache/spark/JavaAPISuite.java

@@ -973,6 +973,19 @@ public Iterator<Integer> call(Integer index, Iterator<Integer> iter) {
     Assert.assertEquals("[3, 7]", partitionSums.collect().toString());
   }
 
+  @Test
+  public void getNumPartitions(){
+    JavaRDD<Integer> rdd1 = sc.parallelize(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8), 3);
+    JavaDoubleRDD rdd2 = sc.parallelizeDoubles(Arrays.asList(1.0, 2.0, 3.0, 4.0), 2);
+    JavaPairRDD<String, Integer> rdd3 = sc.parallelizePairs(Arrays.asList(
+            new Tuple2<>("a", 1),
+            new Tuple2<>("aa", 2),
+            new Tuple2<>("aaa", 3)
+    ), 2);
+    Assert.assertEquals(3, rdd1.getNumPartitions());
+    Assert.assertEquals(2, rdd2.getNumPartitions());
+    Assert.assertEquals(2, rdd3.getNumPartitions());
+  }
 
   @Test
   public void repartition() {

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

@@ -34,6 +34,7 @@ class RDDSuite extends SparkFunSuite with SharedSparkContext {
 
   test("basic operations") {
     val nums = sc.makeRDD(Array(1, 2, 3, 4), 2)
+    assert(nums.getNumPartitions === 2)
     assert(nums.collect().toList === List(1, 2, 3, 4))
     assert(nums.toLocalIterator.toList === List(1, 2, 3, 4))
     val dups = sc.makeRDD(Array(1, 1, 2, 2, 3, 3, 4, 4), 2)

project/MimaExcludes.scala

@@ -155,6 +155,10 @@ object MimaExcludes {
           "org.apache.spark.storage.BlockManagerMessages$GetRpcHostPortForExecutor"),
         ProblemFilters.exclude[MissingClassProblem](
           "org.apache.spark.storage.BlockManagerMessages$GetRpcHostPortForExecutor$")
+      ) ++ Seq(
+        // SPARK-3580 Add getNumPartitions method to JavaRDD
+        ProblemFilters.exclude[MissingMethodProblem](
+          "org.apache.spark.api.java.JavaRDDLike.getNumPartitions")
       )
     case v if v.startsWith("1.5") =>
       Seq(