[GitHub] spark pull request #17936: [SPARK-20638][Core]Optimize the CartesianRDD to r...

[srowen <gi...@git.apache.org>]

Github user srowen commented on a diff in the pull request:

    https://github.com/apache/spark/pull/17936#discussion_r116959739
  
    --- Diff: core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala ---
    @@ -71,9 +72,85 @@ class CartesianRDD[T: ClassTag, U: ClassTag](
       }
     
       override def compute(split: Partition, context: TaskContext): Iterator[(T, U)] = {
    +    val blockManager = SparkEnv.get.blockManager
         val currSplit = split.asInstanceOf[CartesianPartition]
    -    for (x <- rdd1.iterator(currSplit.s1, context);
    -         y <- rdd2.iterator(currSplit.s2, context)) yield (x, y)
    +    val blockId2 = RDDBlockId(rdd2.id, currSplit.s2.index)
    +    var cachedInLocal = false
    +    var holdReadLock = false
    +
    +    // Try to get data from the local, otherwise it will be cached to the local.
    +    def getOrElseCache(
    +        rdd: RDD[U],
    +        partition: Partition,
    +        context: TaskContext,
    +        level: StorageLevel): Iterator[U] = {
    +      getLocalValues() match {
    +        case Some(result) =>
    +          return result
    +        case None => // do nothing
    +      }
    +
    +      val iterator = rdd.iterator(partition, context)
    +      // Keep read lock, because next we need read it. And don't tell master.
    +      blockManager.putIterator[U](blockId2, iterator, level, false, true) match {
    +        case true =>
    --- End diff --
    
    BTW I think match is confusing overkill for booleans. Just use if-else


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