Connectivity problem with controller breaks cluster
Hi, We are using kafka 0.10.1.0. We have three brokers and three zookeeper. Today broker 1 and 2 lost connectivity with broker 3, and I saw the broker 3 was the controller. I saw lot of messages "[rw_campaign_broadcast_nextel_734fae3d46d4da63ee36d2b6fd25a77f3f7c3ef5,9] on broker 3: Shrinking ISR for partition [rw_campaign_broadcast_nextel_734fae3d46d4da63ee36d2b6fd25a77f3f7c3ef5,9] from 1,2,3 to 3" On the broker 2 and 1: [2016-12-27 08:10:05,501] WARN [ReplicaFetcherThread-0-3], Error in fetch kafka.server.ReplicaFetcherThread$FetchRequest@108fd1b0 (kafka.server.ReplicaFetcherThread) java.io.IOException: Connection to 3 was disconnected before the response was read at kafka.utils.NetworkClientBlockingOps$$anonfun$blockingSendAndReceive$extension$1$$anonfun$apply$1.apply(NetworkClientBlockingOps.scala:115) at kafka.utils.NetworkClientBlockingOps$$anonfun$blockingSendAndReceive$extension$1$$anonfun$apply$1.apply(NetworkClientBlockingOps.scala:112) at scala.Option.foreach(Option.scala:257) at kafka.utils.NetworkClientBlockingOps$$anonfun$blockingSendAndReceive$extension$1.apply(NetworkClientBlockingOps.scala:112) at kafka.utils.NetworkClientBlockingOps$$anonfun$blockingSendAndReceive$extension$1.apply(NetworkClientBlockingOps.scala:108) at kafka.utils.NetworkClientBlockingOps$.recursivePoll$1(NetworkClientBlockingOps.scala:137) at kafka.utils.NetworkClientBlockingOps$.kafka$utils$NetworkClientBlockingOps$$pollContinuously$extension(NetworkClientBlockingOps.scala:143) at kafka.utils.NetworkClientBlockingOps$.blockingSendAndReceive$extension(NetworkClientBlockingOps.scala:108) at kafka.server.ReplicaFetcherThread.sendRequest(ReplicaFetcherThread.scala:253) at kafka.server.ReplicaFetcherThread.fetch(ReplicaFetcherThread.scala:238) at kafka.server.ReplicaFetcherThread.fetch(ReplicaFetcherThread.scala:42) at kafka.server.AbstractFetcherThread.processFetchRequest(AbstractFetcherThread.scala:118) at kafka.server.AbstractFetcherThread.doWork(AbstractFetcherThread.scala:103) at kafka.utils.ShutdownableThread.run(ShutdownableThread.scala:63) All my consumers and producers went down. I try to consume and produce with kafka-console-producer/consumer.sh and it fails. The only solution was restart broker 3, after that it correct the problem. Any tips? -- Felipe Santos
Null Pointer Kafka Client
I am using kafka 0.10.1.0 some times on the client I've got null pointer exception: " java.lang.NullPointerException at org.apache.kafka.common.record.ByteBufferInputStream.read(org/apache/kafka/common/record/ByteBufferInputStream.java:34) at java.util.zip.CheckedInputStream.read(java/util/zip/CheckedInputStream.java:59) at java.util.zip.GZIPInputStream.readUByte(java/util/zip/GZIPInputStream.java:266) at java.util.zip.GZIPInputStream.readUShort(java/util/zip/GZIPInputStream.java:258) at java.util.zip.GZIPInputStream.readHeader(java/util/zip/GZIPInputStream.java:164) at java.util.zip.GZIPInputStream.(java/util/zip/GZIPInputStream.java:79) at java.util.zip.GZIPInputStream.(java/util/zip/GZIPInputStream.java:91) at org.apache.kafka.common.record.Compressor.wrapForInput(org/apache/kafka/common/record/Compressor.java:280) at org.apache.kafka.common.record.MemoryRecords$RecordsIterator.(org/apache/kafka/common/record/MemoryRecords.java:247) at org.apache.kafka.common.record.MemoryRecords$RecordsIterator.makeNext(org/apache/kafka/common/record/MemoryRecords.java:316) at org.apache.kafka.common.record.MemoryRecords$RecordsIterator.makeNext(org/apache/kafka/common/record/MemoryRecords.java:222) at org.apache.kafka.common.utils.AbstractIterator.maybeComputeNext(org/apache/kafka/common/utils/AbstractIterator.java:79) at org.apache.kafka.common.utils.AbstractIterator.hasNext(org/apache/kafka/common/utils/AbstractIterator.java:45) at org.apache.kafka.clients.consumer.internals.Fetcher.parseFetchedData(org/apache/kafka/clients/consumer/internals/Fetcher.java:679) at org.apache.kafka.clients.consumer.internals.Fetcher.fetchedRecords(org/apache/kafka/clients/consumer/internals/Fetcher.java:425) at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(org/apache/kafka/clients/consumer/KafkaConsumer.java:1021) at org.apache.kafka.clients.consumer.KafkaConsumer.poll(org/apache/kafka/clients/consumer/KafkaConsumer.java:979) at java.lang.reflect.Method.invoke(java/lang/reflect/Method.java:498) at RUBY.thread_runner(/opt/logstash/vendor/local_gems/90fefca7/logstash-input-kafka-6.2.0/lib/logstash/inputs/kafka.rb:246) at java.lang.Thread.run(java/lang/Thread.java:745) -- Felipe Santos
Re: Oversized Message 40k
Thanks guys, for your information, I will do some performance tests Em qua, 23 de nov de 2016 às 05:14, Ignacio Solis <iso...@igso.net> escreveu: > At LinkedIn we have a number of use cases for large messages. We stick to > the 1MB message limit at the high end though. > > Nacho > > On Tue, Nov 22, 2016 at 6:11 PM, Gwen Shapira <g...@confluent.io> wrote: > > > This has been our experience as well. I think the largest we've seen > > in production is 50MB. > > > > If you have performance numbers you can share for the large messages, > > I think we'll all appreciate :) > > > > On Tue, Nov 22, 2016 at 1:04 PM, Tauzell, Dave > > <dave.tauz...@surescripts.com> wrote: > > > I ran tests with a mix of messages, some as large as 20MB. These > large > > messages do slow down processing, but it still works. > > > > > > -Dave > > > > > > -Original Message- > > > From: h...@confluent.io [mailto:h...@confluent.io] > > > Sent: Tuesday, November 22, 2016 1:41 PM > > > To: users@kafka.apache.org > > > Subject: Re: Oversized Message 40k > > > > > > The default config handles messages up to 1MB so you should be fine. > > > > > > -hans > > > > > >> On Nov 22, 2016, at 4:00 AM, Felipe Santos <felip...@gmail.com> > wrote: > > >> > > >> I read on documentation that kafka is not optimized for big messages, > > >> what is considered a big message? > > >> > > >> For us the messages will be on average from 20k ~ 40k? Is this a real > > >> problem? > > >> > > >> Thanks > > >> -- > > >> Felipe Santos > > > This e-mail and any files transmitted with it are confidential, may > > contain sensitive information, and are intended solely for the use of the > > individual or entity to whom they are addressed. If you have received > this > > e-mail in error, please notify the sender by reply e-mail immediately and > > destroy all copies of the e-mail and any attachments. > > > > > > > > -- > > Gwen Shapira > > Product Manager | Confluent > > 650.450.2760 | @gwenshap > > Follow us: Twitter | blog > > > > > > -- > Nacho - Ignacio Solis - iso...@igso.net >
Oversized Message 40k
I read on documentation that kafka is not optimized for big messages, what is considered a big message? For us the messages will be on average from 20k ~ 40k? Is this a real problem? Thanks -- Felipe Santos
Re: Stream processing meetup at LinkedIn (Mountain View) on Tuesday, August 23 at 6pm
Hi, The event will be broadcast live? On 13 August 2016 at 08:21, Prabhjot Bharaj <prabhbha...@gmail.com> wrote: > Hi, > > Thanks for the response. Wishing you the best for making all the > arrangements. > > Looking forward to it > > Regards, > Prabhjot > > On Aug 12, 2016 5:58 PM, "Ed Yakabosky" <eyakabo...@linkedin.com.invalid> > wrote: > > > Hello, > > > > We will be sharing a live-stream as well as recording after the meetup. > > Thanks for asking! > > > > Ed > > > > On Fri, Aug 12, 2016 at 2:56 PM, Prabhjot Bharaj <prabhbha...@gmail.com> > > wrote: > > > > > Hi, > > > > > > Thanks for the invitation. I won't be able to make it this soon. > > > However, it'll be great if you could arrange to share the video > > recordings. > > > > > > Thanks, > > > Prabhjot > > > > > > On Aug 12, 2016 4:33 PM, "Joel Koshy" <jjkosh...@gmail.com> wrote: > > > > > > > Hi everyone, > > > > > > > > We would like to invite you to a Stream Processing Meetup at > > > > LinkedIn’s *Mountain > > > > View campus on Tuesday, August 23 at 6pm*. Please RSVP here (only if > > you > > > > intend to attend in person): > > > > https://www.meetup.com/Stream-Processing-Meetup-LinkedIn/ > > > events/232864129 > > > > > > > > We have three great talks lined up with speakers from Confluent, > > LinkedIn > > > > and TripAdvisor. > > > > > > > > Hope to see you there! > > > > > > > > Joel > > > > > > > > > > > > > > > -- > > Thanks, > > Ed Yakabosky > > > -- Felipe Santos
