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  1. Spark
  2. SPARK-30460

Spark checkpoint failing after some run with S3 path

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    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Major
    • Resolution: Incomplete
    • Affects Version/s: 2.4.4
    • Fix Version/s: None
    • Component/s: DStreams
    • Labels:

      Description

      We are using EMR with the SQS as source of stream. However it is failing, after 4-6 hours of run, with below exception. Application shows its running but stops the processing the messages

      2020-01-06 13:04:10,548 WARN [BatchedWriteAheadLog Writer] org.apache.spark.streaming.util.BatchedWriteAheadLog:BatchedWriteAheadLog Writer failed to write ArrayBuffer(Record(java.nio.HeapByteBuffer[pos=0 lim=1226 cap=1226],1578315850302,Future(<not completed>)))
      java.lang.UnsupportedOperationException
      	at com.amazon.ws.emr.hadoop.fs.s3n2.S3NativeFileSystem2.append(S3NativeFileSystem2.java:150)
      	at org.apache.hadoop.fs.FileSystem.append(FileSystem.java:1181)
      	at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.append(EmrFileSystem.java:295)
      	at org.apache.spark.streaming.util.HdfsUtils$.getOutputStream(HdfsUtils.scala:35)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter.stream$lzycompute(FileBasedWriteAheadLogWriter.scala:32)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter.stream(FileBasedWriteAheadLogWriter.scala:32)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter.<init>(FileBasedWriteAheadLogWriter.scala:35)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLog.getLogWriter(FileBasedWriteAheadLog.scala:229)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLog.write(FileBasedWriteAheadLog.scala:94)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLog.write(FileBasedWriteAheadLog.scala:50)
      	at org.apache.spark.streaming.util.BatchedWriteAheadLog.org$apache$spark$streaming$util$BatchedWriteAheadLog$$flushRecords(BatchedWriteAheadLog.scala:175)
      	at org.apache.spark.streaming.util.BatchedWriteAheadLog$$anon$1.run(BatchedWriteAheadLog.scala:142)
      	at java.lang.Thread.run(Thread.java:748)
      2020-01-06 13:04:10,554 WARN [wal-batching-thread-pool-0] org.apache.spark.streaming.scheduler.ReceivedBlockTracker:Exception thrown while writing record: BlockAdditionEvent(ReceivedBlockInfo(0,Some(3),None,WriteAheadLogBasedStoreResult(input-0-1578315849800,Some(3),FileBasedWriteAheadLogSegment(s3://mss-prod-us-east-1-ueba-bucket/streaming/checkpoint/receivedData/0/log-1578315850001-1578315910001,0,5175)))) to the WriteAheadLog.
      org.apache.spark.SparkException: Exception thrown in awaitResult: 
      	at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226)
      	at org.apache.spark.streaming.util.BatchedWriteAheadLog.write(BatchedWriteAheadLog.scala:84)
      	at org.apache.spark.streaming.scheduler.ReceivedBlockTracker.writeToLog(ReceivedBlockTracker.scala:242)
      	at org.apache.spark.streaming.scheduler.ReceivedBlockTracker.addBlock(ReceivedBlockTracker.scala:89)
      	at org.apache.spark.streaming.scheduler.ReceiverTracker.org$apache$spark$streaming$scheduler$ReceiverTracker$$addBlock(ReceiverTracker.scala:347)
      	at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$receiveAndReply$1$$anon$1$$anonfun$run$1.apply$mcV$sp(ReceiverTracker.scala:522)
      	at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1340)
      	at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverTrackerEndpoint$$anonfun$receiveAndReply$1$$anon$1.run(ReceiverTracker.scala:520)
      	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
      	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
      	at java.lang.Thread.run(Thread.java:748)
      Caused by: java.lang.UnsupportedOperationException
      	at com.amazon.ws.emr.hadoop.fs.s3n2.S3NativeFileSystem2.append(S3NativeFileSystem2.java:150)
      	at org.apache.hadoop.fs.FileSystem.append(FileSystem.java:1181)
      	at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.append(EmrFileSystem.java:295)
      	at org.apache.spark.streaming.util.HdfsUtils$.getOutputStream(HdfsUtils.scala:35)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter.stream$lzycompute(FileBasedWriteAheadLogWriter.scala:32)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter.stream(FileBasedWriteAheadLogWriter.scala:32)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLogWriter.<init>(FileBasedWriteAheadLogWriter.scala:35)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLog.getLogWriter(FileBasedWriteAheadLog.scala:229)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLog.write(FileBasedWriteAheadLog.scala:94)
      	at org.apache.spark.streaming.util.FileBasedWriteAheadLog.write(FileBasedWriteAheadLog.scala:50)
      	at org.apache.spark.streaming.util.BatchedWriteAheadLog.org$apache$spark$streaming$util$BatchedWriteAheadLog$$flushRecords(BatchedWriteAheadLog.scala:175)
      	at org.apache.spark.streaming.util.BatchedWriteAheadLog$$anon$1.run(BatchedWriteAheadLog.scala:142)
      	... 1 more
      2020-01-06 13:04:10,568 WARN [dispatcher-event-loop-1] org.apache.spark.streaming.scheduler.ReceiverTracker:Error reported by receiver for stream 0: Error in block pushing thread - org.apache.spark.SparkException: Failed to add block to receiver tracker.
      	at org.apache.spark.streaming.receiver.ReceiverSupervisorImpl.pushAndReportBlock(ReceiverSupervisorImpl.scala:163)
      	at org.apache.spark.streaming.receiver.ReceiverSupervisorImpl.pushArrayBuffer(ReceiverSupervisorImpl.scala:129)
      	at org.apache.spark.streaming.receiver.ReceiverSupervisorImpl$$anon$2.onPushBlock(ReceiverSupervisorImpl.scala:110)
      	at org.apache.spark.streaming.receiver.BlockGenerator.pushBlock(BlockGenerator.scala:297)
      	at org.apache.spark.streaming.receiver.BlockGenerator.org$apache$spark$streaming$receiver$BlockGenerator$$keepPushingBlocks(BlockGenerator.scala:269)
      	at org.apache.spark.streaming.receiver.BlockGenerator$$anon$1.run(BlockGenerator.scala:110)
      
      
      
      

      We have enabled the spark streaming with checkpoint using below code, we have removed the business logic in it. https://stackoverflow.com/questions/59222815/spark-streaming-sqs-with-checkpoint-enable

      When I looked at the code of HdfsUtils.scala I don't see a case where it has handled the case for S3 filesystem as it do not support append

      I am suggesting below change either to add 

      if (dfs.getScheme.toLowerCase.contains("s3")){ dfs.create(dfsPath) }
      

      as below

      def getOutputStream(path: String, conf: Configuration): FSDataOutputStream = {
        val dfsPath = new Path(path)
        val dfs = getFileSystemForPath(dfsPath, conf)
        // If the file exists and we have append support, append instead of creating a new file
        val stream: FSDataOutputStream = {
          if (dfs.isFile(dfsPath)) {
            if (dfs.getScheme.toLowerCase.contains("s3")){
              dfs.create(dfsPath)
            } else if (conf.getBoolean("dfs.support.append", true) || conf.getBoolean("hdfs.append.support", false) || dfs.isInstanceOf[RawLocalFileSystem]) {
              dfs.append(dfsPath)
            } else {
              throw new IllegalStateException("File exists and there is no append support!")
            }
          } else {
            dfs.create(dfsPath)
          }
        }
        stream
      }
      

      OR

      Adding the check as assuming with S3 we enabled

      WriteAheadLogUtils.RECEIVER_WAL_ENABLE_CONF_KEY
      if (conf.getBoolean(WriteAheadLogUtils.RECEIVER_WAL_ENABLE_CONF_KEY,false)){ dfs.create(dfsPath) }
      

       

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            • Assignee:
              Unassigned
              Reporter:
              Sachin Sachin Pasalkar

              Dates

              • Created:
                Updated:
                Resolved:

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