Github user jinxing64 commented on a diff in the pull request: https://github.com/apache/spark/pull/18031#discussion_r117620188 --- Diff: core/src/main/scala/org/apache/spark/scheduler/MapStatus.scala --- @@ -193,8 +219,27 @@ private[spark] object HighlyCompressedMapStatus { } else { 0 } + val threshold1 = Option(SparkEnv.get) + .map(_.conf.get(config.SHUFFLE_ACCURATE_BLOCK_THRESHOLD)) + .getOrElse(config.SHUFFLE_ACCURATE_BLOCK_THRESHOLD.defaultValue.get) + val threshold2 = avgSize * Option(SparkEnv.get) + .map(_.conf.get(config.SHUFFLE_ACCURATE_BLOCK_THRESHOLD_BY_TIMES_AVERAGE)) + .getOrElse(config.SHUFFLE_ACCURATE_BLOCK_THRESHOLD_BY_TIMES_AVERAGE.defaultValue.get) + val threshold = math.max(threshold1, threshold2) + val hugeBlockSizesArray = ArrayBuffer[Tuple2[Int, Byte]]() + if (numNonEmptyBlocks > 0) { + i = 0 + while (i < totalNumBlocks) { + if (uncompressedSizes(i) > threshold) { + hugeBlockSizesArray += Tuple2(i, MapStatus.compressSize(uncompressedSizes(i))) + + } + i += 1 + } + } emptyBlocks.trim() emptyBlocks.runOptimize() - new HighlyCompressedMapStatus(loc, numNonEmptyBlocks, emptyBlocks, avgSize) + new HighlyCompressedMapStatus(loc, numNonEmptyBlocks, emptyBlocks, avgSize, --- End diff -- With the default value (spark.shuffle.accurateBlockThreshold=100M and spark.shuffle.accurateBlockThresholdByTimesAverage=2), Yes. But the user can make it more strict by setting (spark.shuffle.accurateBlockThreshold=0 and spark.shuffle.accurateBlockThresholdByTimesAverage=1).
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