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From Erick Erickson <>
Subject Re: replica recovery
Date Thu, 19 Nov 2015 20:14:11 GMT
bq: I would still like to increase the number of transaction logs
retained so that shard recovery (outside of long term failures) is
faster than replicating the entire shard from the leader

That's legitimate, but (you knew that was coming!) nodes having to
recover _should_ be a rare event. Is this happening often or is it a
result of testing? If nodes are going into recovery for no good reason
(i.e. network being unplugged, whatever) I'd put some energy into
understanding that as well. Perhaps there are operational type things
that should be addressed (e.g. stop indexing, wait for commit, _then_
bounce Solr instances).....


On Thu, Nov 19, 2015 at 10:17 AM, Brian Scholl <> wrote:
> Hey Erick,
> Thanks for the reply.
> I plan on rebuilding my cluster soon with more nodes so that the index size (including
tlogs) is under 50% of the available disk at a minimum, ideally we will shoot for under 33%
budget permitting.  I think I now understand the problem that managing this resource will
solve and I appreciate your (and Shawn's) feedback.
> I would still like to increase the number of transaction logs retained so that shard
recovery (outside of long term failures) is faster than replicating the entire shard from
the leader.  I understand that this is an optimization and not a
> solution for replication.  If I'm being thick about this call me out :)
> Cheers,
> Brian
>> On Nov 19, 2015, at 11:30, Erick Erickson <> wrote:
>> First, every time you autocommit there _should_ be a new
>> tlog created. A hard commit truncates the tlog by design.
>> My guess (not based on knowing the code) is that
>> Real Time Get needs file handle open to the tlog files
>> and you'll have a bunch of them. Lots and lots and lots. Thus
>> the too many file handles is just waiting out there for you.
>> However, this entire approach is, IMO, not going to solve
>> anything for you. Or rather other problems will come out
>> of the woodwork.
>> To whit: At some point, you _will_ need to have at least as
>> much free space on your disk as your current index occupies,
>> even without recovery. Background merging of segments can
>> effectively do the same thing as an optimize step, which rewrites
>> the entire index to new segments before deleting the old
>> segments. So far you haven't hit that situation in steady-state,
>> but you will.
>> Simply put, I think you're wasting your time pursuing the tlog
>> option. You must have bigger disks or smaller indexes such
>> that there is at least as much free disk space at all times as
>> your index occupies. In fact if the tlogs are on the same
>> drive as your index, the tlog option you're pursuing is making
>> the situation _worse_ by making running out of disk space
>> during a merge even more likely.
>> So unless there's a compelling reason you can't use bigger
>> disks, IMO you'll waste lots and lots of valuable
>> engineering time before... buying bigger disks.
>> Best,
>> Erick
>> On Thu, Nov 19, 2015 at 6:21 AM, Brian Scholl <> wrote:
>>> I have opted to modify the number and size of transaction logs that I keep to
resolve the original issue I described.  In so doing I think I have created a new problem,
feedback is appreciated.
>>> Here are the new updateLog settings:
>>>    <updateLog>
>>>      <str name="dir">${solr.ulog.dir:}</str>
>>>      <int name="numVersionBuckets">${solr.ulog.numVersionBuckets:65536}</int>
>>>      <int name="numRecordsToKeep">10000000</int>
>>>      <int name="maxNumLogsToKeep">5760</int>
>>>    </updateLog>
>>> First I want to make sure I understand what these settings do:
>>>        numRecordsToKeep: per transaction log file keep this number of documents
>>>        maxNumLogsToKeep: retain this number of transaction log files total
>>> During my testing I thought I observed that a new tlog is created every time
auto-commit is triggered (every 15 seconds in my case) so I set maxNumLogsToKeep high enough
to contain an entire days worth of updates.   Knowing that I could potentially need to bulk
load some data I set numRecordsToKeep higher than my max throughput per replica for 15 seconds.
>>> The problem that I think this has created is I am now running out of file descriptors
on the servers.  After indexing new documents for a couple hours a some servers (not all)
will start logging this error rapidly:
>>> 73021439 WARN  (qtp1476011703-18-acceptor-0@6d5514d9-ServerConnector@6392e703{HTTP/1.1}{})
[   ] o.e.j.s.ServerConnector
>>> Too many open files
>>>        at Method)
>>>        at
>>>        at
>>>        at org.eclipse.jetty.server.ServerConnector.accept(
>>>        at org.eclipse.jetty.server.AbstractConnector$
>>>        at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(
>>>        at org.eclipse.jetty.util.thread.QueuedThreadPool$
>>>        at
>>> The output of ulimit -n for the user running the solr process is 1024.  I am
pretty sure I can prevent this error from occurring  by increasing the limit on each server
but it isn't clear to me how high it should be or if raising the limit will cause new problems.
>>> Any advice you could provide in this situation would be awesome!
>>> Cheers,
>>> Brian
>>>> On Oct 27, 2015, at 20:50, Jeff Wartes <> wrote:
>>>> On the face of it, your scenario seems plausible. I can offer two pieces
>>>> of info that may or may not help you:
>>>> 1. A write request to Solr will not be acknowledged until an attempt has
>>>> been made to write to all relevant replicas. So, B won’t ever be missing
>>>> updates that were applied to A, unless communication with B was disrupted
>>>> somehow at the time of the update request. You can add a min_rf param to
>>>> your write request, in which case the response will tell you how many
>>>> replicas received the update, but it’s still up to your indexer client
>>>> decide what to do if that’s less than your replication factor.
>>>> See
>>>> Tolerance for more info.
>>>> 2. There are two forms of replication. The usual thing is for the leader
>>>> for each shard to write an update to all replicas before acknowledging the
>>>> write itself, as above. If a replica is less than N docs behind the
>>>> leader, the leader can replay those docs to the replica from its
>>>> transaction log. If a replica is more than N docs behind though, it falls
>>>> back to the replication handler recovery mode you mention, and attempts to
>>>> re-sync the whole shard from the leader.
>>>> The default N for this is 100, which is pretty low for a high-update-rate
>>>> index. It can be changed by increasing the size of the transaction log,
>>>> (via numRecordsToKeep) but be aware that a large transaction log size can
>>>> delay node restart.
>>>> See
>>>> ig#UpdateHandlersinSolrConfig-TransactionLog for more info.
>>>> Hope some of that helps, I don’t know a way to say
>>>> delete-first-on-recovery.
>>>> On 10/27/15, 5:21 PM, "Brian Scholl" <> wrote:
>>>>> Whoops, in the description of my setup that should say 2 replicas per
>>>>> shard.  Every server has a replica.
>>>>>> On Oct 27, 2015, at 20:16, Brian Scholl <>
>>>>>> Hello,
>>>>>> I am experiencing a failure mode where a replica is unable to recover
>>>>>> and it will try to do so forever.  In writing this email I want to
>>>>>> sure that I haven't missed anything obvious or missed a configurable
>>>>>> option that could help.  If something about this looks funny, I would
>>>>>> really like to hear from you.
>>>>>> Relevant details:
>>>>>> - solr 5.3.1
>>>>>> - java 1.8
>>>>>> - ubuntu linux 14.04 lts
>>>>>> - the cluster is composed of 1 SolrCloud collection with 100 shards
>>>>>> backed by a 3 node zookeeper ensemble
>>>>>> - there are 200 solr servers in the cluster, 1 replica per shard
>>>>>> - a shard replica is larger than 50% of the available disk
>>>>>> - ~40M docs added per day, total indexing time is 8-10 hours spread
>>>>>> over the day
>>>>>> - autoCommit is set to 15s
>>>>>> - softCommit is not defined
>>>>>> I think I have traced the failure to the following set of events
>>>>>> would appreciate feedback:
>>>>>> 1. new documents are being indexed
>>>>>> 2. the leader of a shard, server A, fails for any reason (java crashes,
>>>>>> times out with zookeeper, etc)
>>>>>> 3. zookeeper promotes the other replica of the shard, server B, to
>>>>>> leader position and indexing resumes
>>>>>> 4. server A comes back online (typically 10s of seconds later) and
>>>>>> reports to zookeeper
>>>>>> 5. zookeeper tells server A that it is no longer the leader and to
>>>>>> with server B
>>>>>> 6. server A checks with server B but finds that server B's index
>>>>>> version is different from its own
>>>>>> 7. server A begins replicating a new copy of the index from server
>>>>>> using the (legacy?) replication handler
>>>>>> 8. the original index on server A was not deleted so it runs out
>>>>>> disk space mid-replication
>>>>>> 9. server A throws an error, deletes the partially replicated index,
>>>>>> and then tries to replicate again
>>>>>> At this point I think steps 6  => 9 will loop forever
>>>>>> If the actual errors from solr.log are useful let me know, not doing
>>>>>> that now for brevity since this email is already pretty long.  In
>>>>>> nutshell and in order, on server A I can find the error that took
>>>>>> down, the post-recovery instruction from ZK to unregister itself
as a
>>>>>> leader, the corrupt index error message, and then the (start - whoops,
>>>>>> out of disk- stop) loop of the replication messages.
>>>>>> I first want to ask if what I described is possible or did I get
>>>>>> somewhere along the way reading the docs?  Is there any reason to
>>>>>> that solr should not do this?
>>>>>> If my version of events is feasible I have a few other questions:
>>>>>> 1. What happens to the docs that were indexed on server A but never
>>>>>> replicated to server B before the failure?  Assuming that the replica
>>>>>> server A were to complete the recovery process would those docs appear
>>>>>> in the index or are they gone for good?
>>>>>> 2. I am guessing that the corrupt replica on server A is not deleted
>>>>>> because it is still viable, if server B had a catastrophic failure
>>>>>> could pick up the pieces from server A.  If so is this a configurable
>>>>>> option somewhere?  I'd rather take my chances on server B going down
>>>>>> before replication finishes than be stuck in this state and have
>>>>>> manually intervene.  Besides, I have disaster recovery backups for
>>>>>> exactly this situation.
>>>>>> 3. Is there anything I can do to prevent this type of failure?  It
>>>>>> seems to me that if server B gets even 1 new document as a leader
>>>>>> shard will enter this state.  My only thought right now is to try
>>>>>> stop sending documents for indexing the instant a leader goes down
>>>>>> on the surface this solution sounds tough to implement perfectly
(and it
>>>>>> would have to be perfect).
>>>>>> If you got this far thanks for sticking with me.
>>>>>> Cheers,
>>>>>> Brian

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