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

    https://github.com/apache/spark/pull/17936#discussion_r117424810
  
    --- Diff: core/src/main/scala/org/apache/spark/rdd/CartesianRDD.scala ---
    @@ -71,9 +72,92 @@ 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 => if (holdReadLock) {
    +          throw new SparkException(s"get() failed for block $blockId2 even 
though we held a lock")
    +        }
    +      }
    +
    +      val iterator = rdd.iterator(partition, context)
    +      if (rdd.getStorageLevel != StorageLevel.NONE || 
rdd.isCheckpointedAndMaterialized) {
    +        // If the block is cached in local, wo shouldn't cache it again.
    --- End diff --
    
    `getOrElseUpdate` doesn't guarantee the block can be successfully cached. 
It can be failed to cache it. In this case, it simply returns 


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