完整報錯如下： Adding annotator tokenize TokenizerAnnotator: No tokenizer type provided. Defaulting to PTBTokenizer. Adding annotator ssplit edu.stanford.nlp.pipeline.AnnotatorImplementations: Adding annotator pos Reading POS tagger model from edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger ... done [1.9 sec]. Adding annotator lemma Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.lang.RuntimeException: bytes consumed error!at edu.umd.cloud9.collection.XMLInputFormat$XMLRecordReader.nextKeyValue(XMLInputFormat.java:170)at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:214)at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:191)at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:63)at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)at org.apache.spark.scheduler.Task.run(Task.scala:109)at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)at java.lang.Thread.run(Thread.java:748)Driver stacktrace:at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)at scala.Option.foreach(Option.scala:257)at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)at org.apache.spark.rdd.RDD.count(RDD.scala:1162)at org.apache.spark.ml.feature.CountVectorizer.fit(CountVectorizer.scala:176)at AssembleDocumentTermMatrix.documentTermMatrix(AssembleDocumentTermMatrix.scala:133)at RunLSA$.main(RunLSA.scala:48)at RunLSA.main(RunLSA.scala) Caused by: java.lang.RuntimeException: bytes consumed error!at edu.umd.cloud9.collection.XMLInputFormat$XMLRecordReader.nextKeyValue(XMLInputFormat.java:170)at org.apache.spark.rdd.NewHadoopRDD$$anon$1.hasNext(NewHadoopRDD.scala:214)at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:191)at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:63)at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)at org.apache.spark.scheduler.Task.run(Task.scala:109)at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)at java.lang.Thread.run(Thread.java:748) Adding annotator tokenize Adding annotator ssplit Adding annotator pos Adding annotator lemmaProcess finished with exit code 1

?

?

以上問題是出現(xiàn)在《Spark高級數據分析》第六章，Spark進行LDA的時候出現(xiàn)的問題。

解決方案：

其實就是我們使用的xml文件的標簽數量不一致，

例如<page>是６個，</page>是7個，就會導致上面報錯，改過來就好了。

之所以會出現(xiàn)這個問題，是因為代碼調試需要，所以我們截取了原先大數據集中的一小部分，但是忘記截取原先的xml中的尾巴部分了，所以導致新的xml文件在格式上是不完整（也就是所有標簽沒有剛好成對）

總結

以上是生活随笔為你收集整理的spark出现bytes consumed error的问题的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。