ivoson commented on code in PR #39459: URL: https://github.com/apache/spark/pull/39459#discussion_r1111226349
########## core/src/main/scala/org/apache/spark/storage/BlockManager.scala: ########## @@ -1325,31 +1328,71 @@ private[spark] class BlockManager( blockInfoManager.releaseAllLocksForTask(taskAttemptId) } + /** + * Retrieve the given rdd block if it exists and is visible, otherwise call the provided + * `makeIterator` method to compute the block, persist it, and return its values. + * + * @return either a BlockResult if the block was successfully cached, or an iterator if the block + * could not be cached. + */ + def getOrElseUpdateRDDBlock[T]( + taskId: Long, + blockId: RDDBlockId, + level: StorageLevel, + classTag: ClassTag[T], + makeIterator: () => Iterator[T]): Either[BlockResult, Iterator[T]] = { + val isCacheVisible = isRDDBlockVisible(blockId) + val res = getOrElseUpdate(blockId, level, classTag, makeIterator, isCacheVisible) + if (res.isLeft && !isCacheVisible) { + // Block exists but not visible, report taskId -> blockId info to master. + master.updateRDDBlockTaskInfo(blockId, taskId) + } + + res + } + /** * Retrieve the given block if it exists, otherwise call the provided `makeIterator` method * to compute the block, persist it, and return its values. * * @return either a BlockResult if the block was successfully cached, or an iterator if the block * could not be cached. */ - def getOrElseUpdate[T]( + private def getOrElseUpdate[T]( blockId: BlockId, level: StorageLevel, classTag: ClassTag[T], - makeIterator: () => Iterator[T]): Either[BlockResult, Iterator[T]] = { - // Attempt to read the block from local or remote storage. If it's present, then we don't need - // to go through the local-get-or-put path. - get[T](blockId)(classTag) match { - case Some(block) => - return Left(block) - case _ => - // Need to compute the block. + makeIterator: () => Iterator[T], + isCacheVisible: Boolean = true): Either[BlockResult, Iterator[T]] = { + // Track whether the data is computed or not, force to do the computation later if need to. + // The reason we push the force computing later is that once the executor is decommissioned we + // will have a better chance to replicate the cache block because of the `checkShouldStore` + // validation when putting a new block. + var computed: Boolean = false + val iterator = () => { + computed = true + makeIterator() + } + if (isCacheVisible) { + // Attempt to read the block from local or remote storage. If it's present, then we don't need + // to go through the local-get-or-put path. + get[T](blockId)(classTag) match { + case Some(block) => + return Left(block) + case _ => + // Need to compute the block. + } } + // Initially we hold no locks on this block. - doPutIterator(blockId, makeIterator, level, classTag, keepReadLock = true) match { + doPutIterator(blockId, iterator, level, classTag, keepReadLock = true) match { case None => // doPut() didn't hand work back to us, so the block already existed or was successfully // stored. Therefore, we now hold a read lock on the block. + if (!isCacheVisible && !computed) { + // Force compute to report accumulator updates. + makeIterator() Review Comment: Thanks for pointing this out. Updated and added a UT for this. ########## core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala: ########## @@ -1787,6 +1792,12 @@ private[spark] class DAGScheduler( case _: ExceptionFailure | _: TaskKilled => updateAccumulators(event) case _ => } + if (trackingCacheVisibility) { + // Update rdd blocks' visibility status. + blockManagerMaster.updateRDDBlockVisibility( Review Comment: Updated -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org