Spark UI中Shuffle dataSize 和shuffle bytes written 指标区别

背景

本文基于Spark 3.1.1
目前在做一些知识回顾的时候,发现了一些很有意思的事情,就是Spark UI中ShuffleExchangeExec 的dataSize和shuffle bytes written指标是不一样的,
那么在AQE阶段的时候,是以哪个指标来作为每个Task分区大小的参考呢

结论

先说结论 dataSzie指标是 是存在内存中的UnsafeRow 的大小的总和,AQE阶段(规则OptimizeSkewedJoin/CoalesceShufflePartitions)用到判断分区是否倾斜或者合并分区的依据是来自于这个值,
shuffle bytes written指的是写入文件的字节数,会区分压缩和非压缩,如果在开启了压缩(也就是spark.shuffle.compress true)和未开启压缩的情况下,该值的大小是不一样的。
开启压缩如下:
Spark UI中Shuffle dataSize 和shuffle bytes written 指标区别_第1张图片
未开启压缩如下:
Spark UI中Shuffle dataSize 和shuffle bytes written 指标区别_第2张图片

先说杂谈

这两个指标的值都在 ShuffleExchangeExec中:

case class ShuffleExchangeExec(
    override val outputPartitioning: Partitioning,
    child: SparkPlan,
    shuffleOrigin: ShuffleOrigin = ENSURE_REQUIREMENTS)
  extends ShuffleExchangeLike {

  private lazy val writeMetrics =
    SQLShuffleWriteMetricsReporter.createShuffleWriteMetrics(sparkContext)
  private[sql] lazy val readMetrics =
    SQLShuffleReadMetricsReporter.createShuffleReadMetrics(sparkContext)
  override lazy val metrics = Map(
    "dataSize" -> SQLMetrics.createSizeMetric(sparkContext, "data size")
  ) ++ readMetrics ++ writeMetrics

dataSize指标来自于哪里

涉及到datasize的数据流是怎么样的如下,一切还是得从ShuffleMapTask这个shuffle的起始操作讲起:

ShuffleMapTask
   ||
   \/
runTask
   ||
   \/
dep.shuffleWriterProcessor.write //这里的shuffleWriterProcessor是来自于 ShuffleExchangeExec中的createShuffleWriteProcessor
   ||
   \/
writer.write()  //这里是writer 是 UnsafeShuffleWriter类型的实例
   ||
   \/
insertRecordIntoSorter
   ||
   \/
UnsafeRowSerializerInstance.writeValue
   ||
   \/
dataSize.add(row.getSizeInBytes)

这里的 rowUnsafeRow的实例,这样就获取到了实际内存中的每个分区的大小,
而ShuffleMapTask runTask 方法最终返回的是MapStatus,而该MapStatus最终是在UnsafeShuffleWriter的closeAndWriteOutput方法中被赋值的:

void closeAndWriteOutput() throws IOException {
    assert(sorter != null);
    updatePeakMemoryUsed();
    serBuffer = null;
    serOutputStream = null;
    final SpillInfo[] spills = sorter.closeAndGetSpills();
    sorter = null;
    final long[] partitionLengths;
    try {
      partitionLengths = mergeSpills(spills);
    } finally {
      for (SpillInfo spill : spills) {
        if (spill.file.exists() && !spill.file.delete()) {
          logger.error("Error while deleting spill file {}", spill.file.getPath());
        }
      }
    }
    mapStatus = MapStatus$.MODULE$.apply(
      blockManager.shuffleServerId(), partitionLengths, mapId);
  }

shuffle bytes written指标来自哪里

基本流程和dataSize 一样,还是来自于ShuffleMapTask

ShuffleMapTask
   ||
   \/
runTask
   ||
   \/
dep.shuffleWriterProcessor.write //这里的shuffleWriterProcessor是来自于 ShuffleExchangeExec中的createShuffleWriteProcessor
   ||
   \/
writer.write()  //这里是writer 是 UnsafeShuffleWriter类型的实例
   ||
   \/
closeAndWriteOutput
   ||
   \/
sorter.closeAndGetSpills() ->  writeSortedFile -> writer.commitAndGet -> writeMetrics.incBytesWritten(committedPosition - reportedPosition) -> serializerManager.wrapStream(blockId, mcs) // 这里进行了压缩
   ||
   \/
mergeSpills
   ||
   \/
mergeSpillsUsingStandardWriter
   ||
   \/
mergeSpillsWithFileStream -> writeMetrics.incBytesWritten(numBytesWritten)
   ||
   \/
writeMetrics.decBytesWritten(spills[spills.length - 1].file.length())

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