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https://issues.apache.org/jira/browse/SPARK-25871?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marcelo Vanzin reassigned SPARK-25871:
--------------------------------------
Assignee: Imran Rashid
> Streaming WAL should not use hdfs erasure coding, regardless of FS defaults
> ---------------------------------------------------------------------------
>
> Key: SPARK-25871
> URL: https://issues.apache.org/jira/browse/SPARK-25871
> Project: Spark
> Issue Type: Improvement
> Components: DStreams
> Affects Versions: 2.4.0
> Reporter: Imran Rashid
> Assignee: Imran Rashid
> Priority: Major
> Fix For: 3.0.0
>
>
> The {{FileBasedWriteAheadLogWriter}} expects the output stream for the WAL to
> support {{hflush()}}, but hdfs erasure coded files do not support that.
> https://hadoop.apache.org/docs/r3.0.0/hadoop-project-dist/hadoop-hdfs/HDFSErasureCoding.html#Limitations
> otherwise you get exceptions like:
> {noformat}
> 17/10/17 17:31:34 ERROR executor.Executor: Exception in task 0.2 in stage 6.0
> (TID 85)
> org.apache.spark.SparkException: Could not read data from write ahead log
> record
> FileBasedWriteAheadLogSegment(hdfs://quasar-yxckyb-1.vpc.cloudera.com:8020/tmp/__spark__a10be3a3-85ec-4d4f-8782-a4760df4cc4c/88657/checkpoints/receivedData/0/log-1508286672978-1508286732978,1321921,189000)
> at
> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD.org$apache$spark$streaming$rdd$WriteAheadLogBackedBlockRDD$$getBlockFromWriteAheadLog$1(WriteAheadLogBackedBlockRDD.scala:145)
> at
> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD$$anonfun$compute$1.apply(WriteAheadLogBackedBlockRDD.scala:173)
> at
> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD$$anonfun$compute$1.apply(WriteAheadLogBackedBlockRDD.scala:173)
> at scala.Option.getOrElse(Option.scala:121)
> at
> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD.compute(WriteAheadLogBackedBlockRDD.scala:173)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:108)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.io.EOFException: Cannot seek after EOF
> at
> org.apache.hadoop.hdfs.DFSStripedInputStream.seek(DFSStripedInputStream.java:331)
> at
> org.apache.hadoop.fs.FSDataInputStream.seek(FSDataInputStream.java:65)
> at
> org.apache.spark.streaming.util.FileBasedWriteAheadLogRandomReader.read(FileBasedWriteAheadLogRandomReader.scala:37)
> at
> org.apache.spark.streaming.util.FileBasedWriteAheadLog.read(FileBasedWriteAheadLog.scala:120)
> at
> org.apache.spark.streaming.rdd.WriteAheadLogBackedBlockRDD.org$apache$spark$streaming$rdd$WriteAheadLogBackedBlockRDD$$getBlockFromWriteAheadLog$1(WriteAheadLogBackedBlockRDD.scala:142)
> ... 18 more
> {noformat}
> HDFS allows you to force a file to be replicated, regardless of the FS
> defaults -- we should do that for the WAL.
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