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Posted to commits@beam.apache.org by "Jean-Baptiste Onofré (JIRA)" <ji...@apache.org> on 2017/05/17 01:12:04 UTC
[jira] [Resolved] (BEAM-2308) run beam on spark runner successfully
with small data,but fail with a big data
[ https://issues.apache.org/jira/browse/BEAM-2308?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Jean-Baptiste Onofré resolved BEAM-2308.
----------------------------------------
Resolution: Won't Fix
Assignee: Jean-Baptiste Onofré (was: Amit Sela)
Fix Version/s: Not applicable
{{HDFSFileSource}} has been deleted from Beam 2.0.0 and replaced by filesystem that you can directly use with {{TextIO}}.
> run beam on spark runner successfully with small data,but fail with a big data
> ------------------------------------------------------------------------------
>
> Key: BEAM-2308
> URL: https://issues.apache.org/jira/browse/BEAM-2308
> Project: Beam
> Issue Type: Bug
> Components: runner-spark, sdk-java-core
> Environment: spark jar 1.6.2
> Reporter: liyuntian
> Assignee: Jean-Baptiste Onofré
> Fix For: Not applicable
>
>
> run beam on spark runner successfully with small data,but fail with a big data about 1G.my spark configuration：--num-executors 3 --executor-memory 4G --executor-cores 5.
> this is my code:
> Read.Bounded<KV<LongWritable, Text>> source = Read.from(HDFSFileSource.from(inputPath, TextInputFormat.class, LongWritable.class, Text.class).withConfiguration(config));
> PCollection<KV<LongWritable, Text>> recordsFromHdfs = pipeline.apply(source);
> PCollection<List<String>> recordsList = recordsFromHdfs.apply(ParDo.of(new InputHdfsFileFn(delimit, firstTableColumnsSize)));
> //convert to flow
> String nextOutputTable;
> Map<String, ComponentPara> map = beamTable.row(firstTableName);
> ComponentPara component = (ComponentPara) map.values().toArray()[0];
> PCollection<List<String>> nextPCollection = ComponentConvert.convert(component,recordsList);
> //write result to hdfs
> PCollection<String> recordsToHdfs = nextPCollection.apply(ParDo.of(new OutputHdfsFileFn(delimit)));
> HiveTable.deleteBeamFileOnHdfs(outputPath);
> logger.info("输出文件位置："+outputPath);
> recordsToHdfs.apply(Write.to(HDFSFileSink.<String>toText(outputPath).withConfiguration(config)));
> pipeline.run().waitUntilFinish();
> this is error:
> 17/05/16 21:31:57 WARN scheduler.TaskSetManager: Lost task 3.0 in stage 1.0 (TID 13, etl-dev-02): java.util.NoSuchElementException
> at org.apache.beam.sdk.io.hdfs.HDFSFileSource$HDFSFileReader.getCurrent(HDFSFileSource.java:510)
> at org.apache.beam.runners.spark.io.SourceRDD$Bounded$1.next(SourceRDD.java:142)
> at org.apache.beam.runners.spark.io.SourceRDD$Bounded$1.next(SourceRDD.java:111)
> at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:42)
> at org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43)
> at scala.collection.Iterator$$anon$12.next(Iterator.scala:357)
> at org.apache.spark.InterruptibleIterator.next(InterruptibleIterator.scala:43)
> at scala.collection.convert.Wrappers$IteratorWrapper.next(Wrappers.scala:30)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:165)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at org.apache.beam.runners.spark.translation.SparkProcessContext$ProcCtxtIterator.computeNext(SparkProcessContext.java:162)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.tryToComputeNext(AbstractIterator.java:145)
> at org.apache.beam.spark.repackaged.com.google.common.collect.AbstractIterator.hasNext(AbstractIterator.java:140)
> at scala.collection.convert.Wrappers$JIteratorWrapper.hasNext(Wrappers.scala:41)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927)
> at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:927)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1858)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
> at org.apache.spark.scheduler.Task.run(Task.scala:89)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> 17/05/16 21:31:57 INFO scheduler.TaskSetManager: Starting task 3.1 in stage 1.0 (TID 20, etl-dev-02, partition 3,PROCESS_LOCAL, 42372 bytes)
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