Sachin Pasalkar created SPARK-30460:
---------------------------------------
Summary: Spark checkpoint failing after some run with S3 path
Key: SPARK-30460
URL: https://issues.apache.org/jira/browse/SPARK-30460
Project: Spark
Issue Type: Bug
Components: DStreams
Affects Versions: 2.4.4
Reporter: Sachin Pasalkar
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
{code:java}
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)
{code}
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
{code:java}
if (dfs.getScheme.toLowerCase.contains("s3")){ dfs.create(dfsPath) }
{code}
as below
{code:java}
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
}
{code}
OR
Adding the check as assuming with S3 we enabled
{noformat}
WriteAheadLogUtils.RECEIVER_WAL_ENABLE_CONF_KEY{noformat}
{code:java}
if (conf.getBoolean(WriteAheadLogUtils.RECEIVER_WAL_ENABLE_CONF_KEY,false)){
dfs.create(dfsPath) }
{code}
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
