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https://issues.apache.org/jira/browse/KAFKA-3919?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15362604#comment-15362604
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Andy Coates commented on KAFKA-3919:
------------------------------------
Hi [~junrao], thanks for taking the time to look at this.
First off, we have unclean leadership elections disable. (We did later enable
them to help get around some other issues we were having, but this was several
hours after this issue manifested).
We did look through data logs that were causing the brokers to not start. What
we found before the incident was a monotonically increasing offset, where each
compressed batch normally contained one or two records. Then the is a batch
that contains many records, whose first records has an offset below the
previous batch and whose last record has an offset above the previous batch.
Following on from this there continues a period of large batches, with
monotonically increasing offsets, and then the log returns to batches with one
or two records.
Our working assumption here is that the period before the offset dip is
pre-outage normal operation. The period of larger batches is from just after
the outage, where producers have a back log to processes when the partition
becomes available, and then things return to normal batch sizes again once the
back log clears.
We did also look through the Kafka's application logs to try and piece together
the series of events leading up to this:
Here’s what I know happened, with regards to one partition that has issues,
from the logs:
Prior to outage:
Replicas for the partition are brokers 2011, 2012, 2024, with 2024 being the
preferred leader.
Producers using acks=1, compression=gzip
Brokers configured with unclean.elections=false, zk.session-timeout=36s
Post outage:
2011 comes up first, (also as the Controller), recovers unflushed log segment
1239444214, completes load with offset 1239740602, and becomes leader of the
partition.
2012 comes up next, recovers its log, recovers unflushed log segment
1239444214, truncates to offset 1239742830, (thats 2,228 records ahead of the
recovered offset of the current leader), and starts following.
2024 comes up quickly after 2012. recovers unflushed log segment 1239444214,
truncates to offset 1239742250, (thats 1,648 records ahead of the recovered
offset of the current leader), and starts following.
The Controller adds 2024 to the replica set just before 2024 halts due to
another partition having an offset greater than the leader.
The Controller adds 2012 to the replica set just before 2012 halts due to
another partition having an offset greater than the leader.
When 2012 is next restarted, it fails to fully start as its complaining of
invalid offsets in the log.
You’ll notice that the offset the brokers truncate to are different for each of
the three brokers.
Given that I can write to the partition with only one broker available, and
that I can then take this broker down and bring up a different one from the
replica set and write to that one, how does Kafka currently look to reconcile
these different histories when the first node is brought back online? I know
that if the first node has a greater offset it will halt when it tries to
follow the second, but what happens if the first node has a lower offset?
Maybe the above scenario is correctly handled and I’m off down a tangent! (I’d
appreciate any info to improve my understanding of Kafka and help me figure out
what is happening here.). I’m just trying to reconcile the data I’m seeing in
the logs and your response to my post.
I’m going to extract the pertinent entries from our app logs, obfuscate and add
them in here.
(I’ll also add some of that I’ve written here to the description above for the
benefit of anyone new to the ticket)
Thanks,
Andy
> Broker faills to start after ungraceful shutdown due to non-monotonically
> incrementing offsets in logs
> ------------------------------------------------------------------------------------------------------
>
> Key: KAFKA-3919
> URL: https://issues.apache.org/jira/browse/KAFKA-3919
> Project: Kafka
> Issue Type: Bug
> Components: core
> Affects Versions: 0.9.0.1
> Reporter: Andy Coates
>
> Hi All,
> I encountered an issue with Kafka following a power outage that saw a
> proportion of our cluster disappear. When the power came back on several
> brokers halted on start up with the error:
> {noformat}
> Fatal error during KafkaServerStartable startup. Prepare to shutdown”
> kafka.common.InvalidOffsetException: Attempt to append an offset
> (1239742691) to position 35728 no larger than the last offset appended
> (1239742822) to
> /data3/kafka/mt_xp_its_music_main_itsevent-20/00000000001239444214.index.
> at
> kafka.log.OffsetIndex$$anonfun$append$1.apply$mcV$sp(OffsetIndex.scala:207)
> at kafka.log.OffsetIndex$$anonfun$append$1.apply(OffsetIndex.scala:197)
> at kafka.log.OffsetIndex$$anonfun$append$1.apply(OffsetIndex.scala:197)
> at kafka.utils.CoreUtils$.inLock(CoreUtils.scala:262)
> at kafka.log.OffsetIndex.append(OffsetIndex.scala:197)
> at kafka.log.LogSegment.recover(LogSegment.scala:188)
> at kafka.log.Log$$anonfun$loadSegments$4.apply(Log.scala:188)
> at kafka.log.Log$$anonfun$loadSegments$4.apply(Log.scala:160)
> at
> scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at
> scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
> at kafka.log.Log.loadSegments(Log.scala:160)
> at kafka.log.Log.<init>(Log.scala:90)
> at
> kafka.log.LogManager$$anonfun$loadLogs$2$$anonfun$3$$anonfun$apply$10$$anonfun$apply$1.apply$mcV$sp(LogManager.scala:150)
> at kafka.utils.CoreUtils$$anon$1.run(CoreUtils.scala:60)
> at
> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> 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)
> {noformat}
> The only way to recover the brokers was to delete the log files that
> contained non monotonically incrementing offsets.
> I’ve spent some time digging through the logs and I feel I may have worked
> out the sequence of events leading to this issue, (though this is based on
> some assumptions I've made about the way Kafka is working, which may be
> wrong).
> Given:
> * A topic that is produced to using acks = 1
> * A topic that is produced to using gzip compression
> * A topic that has min.isr set to less than the number of replicas, (i.e.
> min.isr=2, #replicas=3)
> * Following ISRs are lagging behind the leader by some small number of
> messages, (which is normal with acks=1)
> * brokers are configured with fairly large zk session timeout e.g. 30s.
> * brokers are configured so that unclean leader elections are disabled.
> Then:
> When something like a power outage take out all three replicas, its possible
> to get into a state such that the indexes won’t rebuild on a restart and a
> broker fails to start. This can happen when:
> * Enough brokers, but not the pre-outage leader, come on-line for the
> partition to be writeable
> * Producers produce enough records to the partition that the head offset is
> now greater than the pre-outage leader head offset.
> * The pre-outage leader comes back online.
> At this point the logs on the pre-outage leader have diverged from the other
> replicas. It has some messages that are not in the other replicas, and the
> other replicas have some records not in the pre-outage leader's log - at the
> same offsets.
> I’m assuming that because the current leader has at higher offset than the
> pre-outage leader, the pre-outage leader just starts following the leader and
> requesting the records it thinks its missing.
> I’m also assuming that because the producers were using gzip, so each record
> is actual a compressed message set, that iwhen the pre-outage leader requests
> records from the leader, the offset it requests could just happened to be in
> the middle of a compressed batch, but the leader returns the full batch.
> When the pre-outage leader appends this batch to its own log it thinks all is
> OK. But what has happened is that the offsets in the log are no longer
> monotonically incrementing. Instead they actually dip by the number of
> records in the compressed batch that were before the requested offset. If
> and when this broker restarts this dip may be at the 4K boundary the indexer
> checks. If it is, the broker won’t start.
> Several of our brokers were unlucky enough to hit that 4K boundary, causing a
> protracted outage. We’ve written a little utility that shows several more
> brokers have a dip outside of the 4K boundary.
> There are some assumptions in there, which I’ve not got around to confirming
> / denying. (A quick attempt to recreate this failed and I've not found the
> time to invest more).
> Of course I'd really appreciate the community / experts stepping in and
> commenting on whether my assumptions are right or wrong, or if there is
> another explanation to the problem.
> But assuming I’m mostly right, then the fact the broker won’t start is
> obviously a bug, and one I’d like to fix. A Kafka broker should not corrupt
> its own log during normal operation to the point that it can’t restart!
> A secondary issue is if we think the divergent logs are acceptable? This may
> be deemed acceptable given the producers have chosen availability over
> consistency when they produced with acks = 1? Though personally, the system
> having diverging replicas of an immutable commit log just doesn't sit right.
> I see us having a few options here:
> * Have the replicas detect the divergence of their logs e.g. a follower
> compares the checksum of its last record with the same offset on the leader.
> The follower can then workout that its log has diverged from the leader. At
> which point it could either halt, stop replicating that partition or search
> backwards to find the point of divergence, truncate and recover. (possibly
> saving the truncated part somewhere). This would be a protocol change for
> Kafka. This solution trades availability, (you’ve got less ISRs during the
> extended re-sync process), for consistency.
> * Leave the logs as they are and have the indexing of offsets in the log on
> start up handle such a situation gracefully. This leaves logs in a divergent
> state between replicas, (meaning replays would yield different messages if
> the leader was up to down), but gives better availability, (no time spent not
> being an ISR while it repairs any divergence).
> * Support multiple options and allow it be tuned, ideally by topic.
> * Something else...
> I’m happy/keen to contribute here. But I’d like to first discuss which option
> should be investigated.
> Andy
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