[
https://issues.apache.org/jira/browse/SPARK-5233?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Saisai Shao updated SPARK-5233:
-------------------------------
Description:
Spark Streaming will write all the event into WAL for driver recovery, the
sequence in the WAL may be like this:
{code}
BlockAdditionEvent ---> BlockAdditionEvent ---> BlockAdditionEvent --->
BatchAllocationEvent ---> BatchCleanupEvent ---> BlockAdditionEvent --->
BlockAdditionEvent ---> 'Driver Down Time' ---> BlockAdditionEvent --->
BlockAdditionEvent ---> BatchAllocationEvent
{code}
When driver recovered from failure, it will replay all the existed metadata WAL
to get the right status, in this situation, two BatchAdditionEvent before down
will put into received block queue. After driver started, new incoming blocking
will also put into this queue and a follow-up BlockAllocationEvent will
allocate an allocatedBlocks with queue draining out. So old, not this batch's
data will also mix into this batch, here is the partial log:
{code}
15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>block store result for batch
1421140750000 ms
....
15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,46704,480)
197757 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,47188,480)
197758 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,47672,480)
197759 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,48156,480)
197760 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,48640,480)
197761 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,49124,480)
197762 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,0,44184)
197763 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,44188,58536)
197764 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,102728,60168)
197765 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,162900,64584)
197766 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,227488,51240)
{code}
The old log
"/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406"
is obviously far older than current batch interval, and will fetch again to
add to process.
This issue is subtle, because in the previous code we never delete the old
received data WAL. This will lead to unwanted result as I know.
Basically because we miss some BlockAllocationEvent when recovered from
failure. I think we need to correctly replay and insert all the events
correctly.
was:
Spark Streaming will write all the event into WAL for driver recovery, the
sequence in the WAL may be like this:
{code}
BlockAdditionEvent ---> BlockAdditionEvent ---> BlockAdditionEvent --->
BatchAllocationEvent ---> BatchCleanupEvent ---> BlockAdditionEvent --->
BlockAdditionEvent ---> 'Driver Down Time' ---> BlockAdditionEvent --->
BlockAdditionEvent ---> BatchAllocationEvent
{code}
When driver recovered from failure, it will replay all the existed metadata WAL
to get the right status, in this situation, two BatchAdditionEvent before down
will put into received block queue. After driver started, new incoming blocking
will also put into this queue and a follow-up BlockAllocationEvent will
allocate an allocatedBlocks with queue draining out. So old, not this batch's
data will also mix into this batch, here is the partial log:
{code}
15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>block store result for batch
1421140750000 ms
....
15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,46704,480)
197757 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,47188,480)
197758 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,47672,480)
197759 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,48156,480)
197760 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,48640,480)
197761 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
53201,49124,480)
197762 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,0,44184)
197763 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,44188,58536)
197764 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,102728,60168)
197765 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,162900,64584)
197766 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
WriteAheadLogFileSegment(file:
/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
07074,227488,51240)
{code}
The old log
"/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406"
is obviously far older than current batch interval, and will fetch again to
add to process.
This issue is implicit, because in the previous code we never delete the old
received data WAL. This will lead to unwanted result as I know.
Basically because we miss some BlockAllocationEvent when recovered from
failure. I think we need to correctly replay and insert all the events
correctly.
> Error replay of WAL when recovered from driver failue
> -----------------------------------------------------
>
> Key: SPARK-5233
> URL: https://issues.apache.org/jira/browse/SPARK-5233
> Project: Spark
> Issue Type: Bug
> Components: Streaming
> Affects Versions: 1.2.0
> Reporter: Saisai Shao
>
> Spark Streaming will write all the event into WAL for driver recovery, the
> sequence in the WAL may be like this:
> {code}
> BlockAdditionEvent ---> BlockAdditionEvent ---> BlockAdditionEvent --->
> BatchAllocationEvent ---> BatchCleanupEvent ---> BlockAdditionEvent --->
> BlockAdditionEvent ---> 'Driver Down Time' ---> BlockAdditionEvent --->
> BlockAdditionEvent ---> BatchAllocationEvent
> {code}
> When driver recovered from failure, it will replay all the existed metadata
> WAL to get the right status, in this situation, two BatchAdditionEvent before
> down will put into received block queue. After driver started, new incoming
> blocking will also put into this queue and a follow-up BlockAllocationEvent
> will allocate an allocatedBlocks with queue draining out. So old, not this
> batch's data will also mix into this batch, here is the partial log:
> {code}
> 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>block store result for
> batch 1421140750000 ms
> ....
> 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
> 53201,46704,480)
> 197757 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
> 53201,47188,480)
> 197758 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
> 53201,47672,480)
> 197759 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
> 53201,48156,480)
>
> 197760 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
> 53201,48640,480)
> 197761 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406
> 53201,49124,480)
> 197762 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
> 07074,0,44184)
> 197763 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
> 07074,44188,58536)
> 197764 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
> 07074,102728,60168)
> 197765 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
> 07074,162900,64584)
> 197766 15/01/13 17:19:10 INFO KafkaInputDStream: >>>>>>>>>>>>>log segment:
> WriteAheadLogFileSegment(file:
> /home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140747074-14211408
> 07074,227488,51240)
> {code}
> The old log
> "/home/jerryshao/project/apache-spark/checkpoint-wal-test/receivedData/0/log-1421140593201-14211406"
> is obviously far older than current batch interval, and will fetch again to
> add to process.
> This issue is subtle, because in the previous code we never delete the old
> received data WAL. This will lead to unwanted result as I know.
> Basically because we miss some BlockAllocationEvent when recovered from
> failure. I think we need to correctly replay and insert all the events
> correctly.
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