Logstash 5 not working with multiline filter



I have a working configuration with Logstash 2.4.0 like this:

input {
  file {
    path => "/path/*"
    type => "type"
    start_position => "beginning"
filter {
  multiline {
    pattern => "^<group"
    negate => "true"
    what => "previous"

Migrating to Logstash 5 I've noticed that the pipeline crashes due to the multiline{} filter.
I can not use the codec because of the 500 rows limits.

Is this a known issue? What are the alternatives?
Elasticsearch 5 can run with Logstash 2.4.0? I suppose yes from my tests but a confirmation would be appreciated :slight_smile:

(Magnus Bäck) #2

I can not use the codec because of the 500 rows limits.

But that can be increased with the max_lines option, right?

Elasticsearch 5 can run with Logstash 2.4.0?

Yes: https://www.elastic.co/support/matrix#show_compatibility


Hello @magnusbaeck,

Yes, I've tried to adopt the multiline-codec approach setting a greater max_lines parameter.
However, Logstash crashed with the following reason:

java.lang.OutOfMemoryError: Java heap space
Dumping heap to java_pid1.hprof ...
Unable to create java_pid1.hprof: Permission denied
The signal INT is in use by the JVM and will not work correctly on this platform
Error: Your application used more memory than the safety cap of 1G.
Specify -J-Xmx####m to increase it (#### = cap size in MB).
Specify -w for full OutOfMemoryError stack trace

First thing fist: I'm running Logstash on a docker container.

Question 1: according to your opinion, was the OutOfMemoryError caused by a memory leak due to multiline-codec?
Question 2: Is it possible to change something to deal with this problem?

Thank you

(Magnus Bäck) #4

according to your opinion, was the OutOfMemoryError caused by a memory leak due to multiline-codec?

I'd rather suspect a bad configuration that causes Logstash to buffer lines in memory while waiting for that last line that'll "release" the buffered event, but that line never comes.


I don't think so, because using the multiline filter the same set of logs worked correctly (using Logstash 2.4.0).
What would you suggest for analyzing further?

(Magnus Bäck) #6

Is it emitting events correctly?


I've analyzed the /var/log/logstash/logstash_plain.log file.
First of all, since I was on my testing machine, I enabled the DEBUG logging level.
This caused the .log file to grow fairly big, about 1.5 GB. I don't know if it coud have been the cause of the issue here. BTW, is there a way to logrotate these logs? I would like to keep debugging but avoiding these huge files.

However, from the logstash_plain.log AFAICT I see that everything went fine for a number of files, after the discovery of the files I see the pattern:

[2016-11-06T17:17:34,469][DEBUG][logstash.inputs.file     ] Received line
[2016-11-06T17:17:34,469][DEBUG][logstash.codecs.multiline] Multiline

And then periodically

[2016-11-06T17:16:54,711][DEBUG][logstash.instrument.collector] Collector: Sending snapshot to observers

Which I think is the normal behaviour since Elasticsearch correctly received all events.

At a certain point, about 15 minutes before the pipeline stops, I see a first ERROR message

[2016-11-06T18:06:51,369][ERROR][logstash.instrument.periodicpoller.jvm] PeriodicPoller: exception

Followed by a number of the same ERROR and at the very end of the file:

[2016-11-06T18:20:10,297][ERROR][logstash.pipeline ] Exception in pipelineworker, the pipeline stopped processing new events, please check your filter configuration and restart Logstash.

Thanks again!


I'm periodically getting the same error also with logging level = INFO

[2016-11-07T18:21:46,606][ERROR][logstash.instrument.periodicpoller.jvm] PeriodicPoller: exception {:poller=>#<LogStash::Instrument::PeriodicPoller::JVM:0x3faabf8c @task=#<Concurrent::TimerTask:0x2306e195 @observers=#<Concurrent::Collection::CopyOnNotifyObserverSet:0x3d2811a3 @observers={#<LogStash::Instrument::PeriodicPoller::JVM:0x3faabf8c ...>=>:update}>, @timeout_interval=60.0, @running=#<Concurrent::AtomicBoolean:0x73644e85>, @StoppedEvent=#<Concurrent::Event:0x677a0335 @set=false, @iteration=0>, @execution_interval=1.0, @do_nothing_on_deref=true, @run_now=nil, @freeze_on_deref=nil, @executor=#<Concurrent::SafeTaskExecutor:0x1aa2a370 @task=#<Proc:0x24569427@/usr/share/logstash/logstash-core/lib/logstash/instrument/periodic_poller/base.rb:52>, @exception_class=StandardError>, @StopEvent=#<Concurrent::Event:0x7517f64e @set=false, @iteration=0>, @value=nil, @copy_on_deref=nil, @dup_on_deref=nil>, @peak_threads=22, @peak_open_fds=3574, @metric=#<LogStash::Instrument::Metric:0x42c32072 @collector=#<LogStash::Instrument::Collector:0x1c4e64b5 @agent=nil, @metric_store=#<LogStash::Instrument::MetricStore:0x4d75b279 @store=#<Concurrent::Map:0x5d92e05c @default_proc=nil>, @structured_lookup_mutex=#<Mutex:0x177dc826>, @fast_lookup=#<Concurrent::Map:0x4ce6ba0b @default_proc=nil>>, @observer_state=true, @snapshot_task=#<Concurrent::TimerTask:0x2ce02f94 @observers=#<Concurrent::Collection::CopyOnNotifyObserverSet:0x66baaa54 @observers={#<LogStash::Instrument::Collector:0x1c4e64b5 ...>=>:update}>, @timeout_interval=600.0, @running=#<Concurrent::AtomicBoolean:0x6630a55b>, @StoppedEvent=#<Concurrent::Event:0x4b01aa86 @set=false, @iteration=0>, @execution_interval=1.0, @do_nothing_on_deref=true, @run_now=nil, @freeze_on_deref=nil, @executor=#<Concurrent::SafeTaskExecutor:0x785a41b8 @task=#<Proc:0x1c53b964@/usr/share/logstash/logstash-core/lib/logstash/instrument/collector.rb:87>, @exception_class=StandardError>, @StopEvent=#<Concurrent::Event:0x7f2acdc8 @set=false, @iteration=0>, @value=false, @copy_on_deref=nil, @dup_on_deref=nil>>>, @options={:polling_interval=>1, :polling_timeout=>60}>, :result=>nil, :exception=>#<Concurrent::TimeoutError: Concurrent::TimeoutError>, :executed_at=>2016-11-07 18:21:46 +0000}

(Magnus Bäck) #9

What did you set max_lines to? If you have a file output it's easy to see if it stops in the same place each time and, if so, if there's something wrong with the input that follows.


My XML files are like this:

<level1 property1a="x" property1b="x">
  <level2 property2="y" property2b="x">
    <level3 property3="x" property2b="x">

<level1> tag could span over 50000+ rows. My max_lines during the last Logstash runs was 10000.

If needed, I could set the multiline to work on level2 (which is significantly smaller, about 100 rows, but then I'm losing property1 values.

(Magnus Bäck) #11

10k lines shouldn't cause the heap to balloon so there's something fishy here. Have you verified that the XML parser can cope with XML documents containing >50k elements? I'd be more worried about that.


Hi @magnusbaeck, how to check if the XML parser can cope with XML documents containing >50k elements?

Thank you :blush:

(Magnus Bäck) #13

I'm not sure how to go about it. I'd perhaps try writing a small Ruby script that uses the same XML parser to load one of your files. Then you could easily get it to slurp a large file in one bite and you get a chance at checking its memory characteristics.


Hi @magnusbaeck, I hope I'll be able to do what you are suggesting me and I really thank you for your time.

Please consider though that my Logstash configuration involves a split filter also. I don't know at this point if this matters.

While the XML is like my previous example, in my Logstash configuration I'm splitting one of the levels (the huge one) like this:

filter {
  xml {
    source => "message"
    store_xml => "false"
    remove_namespaces => "true"
    xpath => ["level1/level2/level3", "level3"]
  mutate {remove_field => ["message"]}
  if [level3][1] {split {field => "[level3]"}} #this is because I want only one level3 item per event
  xml {
    source => "level3"
    store_xml => "false"
    [...] #the rest of the story

Is the split filter safe in this context (it could generate thousands of events)?
Otherwise the only viable option I see would be to reduce the length of my XML files via a script outside Logstash and then parsing them.

(Magnus Bäck) #15

I don't know the code well enough to be able to say something authoritatively. You'll have you try it out. Over and out.


Indeed :smiley:

May I thank you again for your time!

(system) #17

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