学院网站怎么做的经典软文广告案例

背景

最近从数据仓库小组那边反馈了一个问题,一个SQL任务出来的结果不正确，重新运行一次之后就没问题了，具体的SQL如下：

select col1,count(1) as cnt
from table1
where dt = '20230202' 
group by col1
having count(1) > 1

这个问题是偶发的，在其运行的日志中会发现如下三类日志：

FetchFailed 
TaskKilled (another attempt succeeded)
ERROR (org.apache.spark.network.shuffle.RetryingBlockFetcher:231) - Failed to fetch block shuffle_4865_2481
283_286, and will not retry (3 retries)

最终在各种同事的努力下，找到了一个Jira:SPARK-34534

分析

直接切入主题，找到对应的类OneForOneBlockFetcher,该类会被NettyBlockTransferService（没开启ESS）和ExternalBlockStoreClient（开启ESS）调用,其中start方法：

public void start() {client.sendRpc(message.toByteBuffer(), new RpcResponseCallback() {@Overridepublic void onSuccess(ByteBuffer response) {try {streamHandle = (StreamHandle) BlockTransferMessage.Decoder.fromByteBuffer(response);logger.trace("Successfully opened blocks {}, preparing to fetch chunks.", streamHandle);// Immediately request all chunks -- we expect that the total size of the request is// reasonable due to higher level chunking in [[ShuffleBlockFetcherIterator]].for (int i = 0; i < streamHandle.numChunks; i++) {if (downloadFileManager != null) {client.stream(OneForOneStreamManager.genStreamChunkId(streamHandle.streamId, i),new DownloadCallback(i));} else {client.fetchChunk(streamHandle.streamId, i, chunkCallback);}}} catch (Exception e) {logger.error("Failed while starting block fetches after success", e);failRemainingBlocks(blockIds, e);}}@Overridepublic void onFailure(Throwable e) {logger.error("Failed while starting block fetches", e);failRemainingBlocks(blockIds, e);}});}

其中的message的初始化在构造方法中：

 if (!transportConf.useOldFetchProtocol() && isShuffleBlocks(blockIds)) {this.message = createFetchShuffleBlocksMsg(appId, execId, blockIds);} else {this.message = new OpenBlocks(appId, execId, blockIds);}

其中transportConf.useOldFetchProtocol 也就是 spark.shuffle.useOldFetchProtocol配置（默认是false），如果是shuffle block的话，就会运行到：createFetchShuffleBlocksMsg方法，对于为什么存在这么一个判断，具体参考SPARK-27665
关键的就是 createFetchShuffleBlocksMsg 方法：
这个方法的作用就是： 构建一个FetchShuffleBlocks(appId, execId, shuffleId, mapIds, reduceIdArr, batchFetchEnabled) 对象，其中里面的值
如图：

其中这里有一点需要注意：

 long[] mapIds = Longs.toArray(mapIdToReduceIds.keySet());reduceIdArr[i] = Ints.toArray(mapIdToReduceIds.get(mapIds[i]));

这里面对MapId和ReduceId 进行了重组（在获得streamHandle的时候内部会根据reduceIdArr构建blocks索引，下文中会说到）会导致和成员变量blockIds的顺序不一致，为什么两者不一致会导致问题呢？
原因在于任务的fetch失败会导致重新进行fetch,如下：

  client.fetchChunk(streamHandle.streamId, i, chunkCallback);

chunkCallback的代码如下：

private class ChunkCallback implements ChunkReceivedCallback {@Overridepublic void onSuccess(int chunkIndex, ManagedBuffer buffer) {// On receipt of a chunk, pass it upwards as a block.listener.onBlockFetchSuccess(blockIds[chunkIndex], buffer);}@Overridepublic void onFailure(int chunkIndex, Throwable e) {// On receipt of a failure, fail every block from chunkIndex onwards.String[] remainingBlockIds = Arrays.copyOfRange(blockIds, chunkIndex, blockIds.length);failRemainingBlocks(remainingBlockIds, e);}}

String[] remainingBlockIds = Arrays.copyOfRange(blockIds, chunkIndex, blockIds.length)，此处的chunckIndex就是shuffle blocks的索引下标，也就是下文中numBlockIds组成的数组下标,
但是这个和createFetchShuffleBlocksMsg输出的顺序是不一致的，所以如果发生问题重新fetch的时候，数据有错位，具体可以看：
ShuffleBlockFetcherIterator中的

    if (req.size > maxReqSizeShuffleToMem) {shuffleClient.fetchBlocks(address.host, address.port, address.executorId, blockIds.toArray,blockFetchingListener, this)} else {shuffleClient.fetchBlocks(address.host, address.port, address.executorId, blockIds.toArray,blockFetchingListener, null)}

其中blockFetchingListener回调方法onBlockFetchSuccess会把fetch的block数据和shuffleBlockId一一对应上

ESS端构建blocks的信息

在start方法中，client.sendRpc向对应的ESS发送对应的请求shuffle数据信息，ESS会重新构建blocks的信息，组成StreamHandle(streamId, numBlockIds)返回给请求端：
具体为ExternalBlockHandler的handleMessage方法：

if (msgObj instanceof FetchShuffleBlocks) {FetchShuffleBlocks msg = (FetchShuffleBlocks) msgObj;checkAuth(client, msg.appId);numBlockIds = 0;if (msg.batchFetchEnabled) {numBlockIds = msg.mapIds.length;} else {for (int[] ids: msg.reduceIds) {numBlockIds += ids.length;}}streamId = streamManager.registerStream(client.getClientId(),new ShuffleManagedBufferIterator(msg), client.getChannel());
。。。
callback.onSuccess(new StreamHandle(streamId, numBlockIds).toByteBuffer());

这里的numBlockIds就是OneForOneBlockFetcher中的streamHandle.numChunks
如图：

没有开启ESS端的构建blocks的信息

这里和上面的一样，只不过对应的方法为NettyBlockRpcServer的receive:

      case fetchShuffleBlocks: FetchShuffleBlocks =>val blocks = fetchShuffleBlocks.mapIds.zipWithIndex.flatMap { case (mapId, index) =>if (!fetchShuffleBlocks.batchFetchEnabled) {fetchShuffleBlocks.reduceIds(index).map { reduceId =>blockManager.getLocalBlockData(ShuffleBlockId(fetchShuffleBlocks.shuffleId, mapId, reduceId))}} else {val startAndEndId = fetchShuffleBlocks.reduceIds(index)if (startAndEndId.length != 2) {throw new IllegalStateException(s"Invalid shuffle fetch request when batch mode " +s"is enabled: $fetchShuffleBlocks")}Array(blockManager.getLocalBlockData(ShuffleBlockBatchId(fetchShuffleBlocks.shuffleId, mapId, startAndEndId(0), startAndEndId(1))))}}val numBlockIds = if (fetchShuffleBlocks.batchFetchEnabled) {fetchShuffleBlocks.mapIds.length} else {fetchShuffleBlocks.reduceIds.map(_.length).sum}val streamId = streamManager.registerStream(appId, blocks.iterator.asJava,client.getChannel)logTrace(s"Registered streamId $streamId with $numBlockIds buffers")responseContext.onSuccess(new StreamHandle(streamId, numBlockIds).toByteBuffer)

这里的numBlockIds就是OneForOneBlockFetcher中的streamHandle.numChunks
如图：

所以在以上两种情况下，只要有重新fetch数据的操作，就会存在数据的错位，导致数据的不准确

解决

直接git cherry-pick对应的commit就行：

git cherry-pick 4e438196114eff2e1fc4dd726fdc1bda1af267da