spark的累加器会消耗大量内存吗【黑马大数据培训】

我最近在用spark程序过滤数据，文件大概有700G。但是当我用累加器统计过滤掉多少数据时，程序就会报错。错误如下： WARN scheduler.TaskSetManager: Lost task 22.0 in stage 2.1 (TID 16901, B713): FetchFailed(null, shuffleId=0, mapId=-1, reduceId=22, message= org.apache.spark.shuffle.MetadataFetchFailedException: Missing an output location for shuffle 0         at org.apache.spark.MapOutputTracker$$anonfun$org$apache$spark$MapOutputTracker$$convertMapStatuses$2.apply(MapOutputTracker.scala:542)         at org.apache.spark.MapOutputTracker$$anonfun$org$apache$spark$MapOutputTracker$$convertMapStatuses$2.apply(MapOutputTracker.scala:538)         at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)         at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)         at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)         at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)         at org.apache.spark.MapOutputTracker$.org$apache$spark$MapOutputTracker$$convertMapStatuses(MapOutputTracker.scala:538)         at org.apache.spark.MapOutputTracker.getMapSizesByExecutorId(MapOutputTracker.scala:155)         at org.apache.spark.shuffle.BlockStoreShuffleReader.read(BlockStoreShuffleReader.scala:47)         at org.apache.spark.rdd.ShuffledRDD.compute(ShuffledRDD.scala:98)         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)         at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)         at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)         at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)         at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)         at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)         at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)         at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)         at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)         at org.apache.spark.scheduler.Task.run(Task.scala:89)         at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)         at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)         at java.lang.Thread.run(Thread.java:748)