The broker with broker id 4759750 is just restart，and there are 500+ replica partitions shrink and expand frequently，and there leader partition is distributed in the other 5 brokers. the log is pulled from one broker，and extract logs related to 1 partition.
> 在 2017年11月10日，下午12:06，Hu Xi <huxi...@hotmail.com> 写道： > > Seems broker `4759750` was always removed for partition [Yelp, 5] every round > of ISR shrinking. Did you check if everything works alright for this broker? > > > 发件人: Json Tu <kafka...@126.com> > 发送时间: 2017年11月10日 11:08 > 收件人: users@kafka.apache.org > 抄送: d...@kafka.apache.org; Guozhang Wang > 主题: Re: Kafka 0.9.0.1 partitions shrink and expand frequently after restart > the broker > > I‘m so sorry for my poor english. > > what I really means is my broker machine is configured as 8 core 16G. but my > jvm configure is as below. > java -Xmx1G -Xms1G -server -XX:+UseG1GC -XX:MaxGCPauseMillis=20 > -XX:InitiatingHeapOccupancyPercent=35 -XX:+DisableExplicitGC > -Djava.awt.headless=true -Xloggc:/xx/yy/kafkaServer-gc.log -verbose:gc > -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCTimeStamps > -XX:+UseGCLogFileRotation -XX:NumberOfGCLogFiles=32 -XX:GCLogFileSize=10M > -XX:+HeapDumpOnOutOfMemoryError. > > we have 30+ clusters with this jvm configure, and are deployed on the machine > which configured as 8 core 16G. compare to other clusters, the current > cluster have more than 5 times partitions than other clusters. > when we restart other clusters, there is no such phenomenon. > > may be some metrics or logs can leads to find root cause of this phenomenon. > Looking forward to more suggestions. > > > > 在 2017年11月9日，下午9:59，John Yost <hokiege...@gmail.com> 写道： > > > > I've seen this before and it was due to long GC pauses due in large part to > > a memory heap > 8 GB. > > > > --John > > > > On Thu, Nov 9, 2017 at 8:17 AM, Json Tu <kafka...@126.com> wrote: > > > >> Hi, > >> we have a kafka cluster which is made of 6 brokers, with 8 cpu and > >> 16G memory on each broker’s machine, and we have about 1600 topics in the > >> cluster，about 1700 partitions’ leader and 1600 partitions' replica on each > >> broker. > >> when we restart a normal broke, we find that there are 500+ > >> partitions shrink and expand frequently when restart the broker， > >> there are many logs as below. > >> > >> [2017-11-09 17:05:51,173] INFO Partition [Yelp,5] on broker 4759726: > >> Expanding ISR for partition [Yelp,5] from 4759726 to 4759726,4759750 > >> (kafka.cluster.Partition) > >> [2017-11-09 17:06:22,047] INFO Partition [Yelp,5] on broker 4759726: > >> Shrinking ISR for partition [Yelp,5] from 4759726,4759750 to 4759726 > >> (kafka.cluster.Partition) > >> [2017-11-09 17:06:28,634] INFO Partition [Yelp,5] on broker 4759726: > >> Expanding ISR for partition [Yelp,5] from 4759726 to 4759726,4759750 > >> (kafka.cluster.Partition) > >> [2017-11-09 17:06:44,658] INFO Partition [Yelp,5] on broker 4759726: > >> Shrinking ISR for partition [Yelp,5] from 4759726,4759750 to 4759726 > >> (kafka.cluster.Partition) > >> [2017-11-09 17:06:47,611] INFO Partition [Yelp,5] on broker 4759726: > >> Expanding ISR for partition [Yelp,5] from 4759726 to 4759726,4759750 > >> (kafka.cluster.Partition) > >> [2017-11-09 17:07:19,703] INFO Partition [Yelp,5] on broker 4759726: > >> Shrinking ISR for partition [Yelp,5] from 4759726,4759750 to 4759726 > >> (kafka.cluster.Partition) > >> [2017-11-09 17:07:26,811] INFO Partition [Yelp,5] on broker 4759726: > >> Expanding ISR for partition [Yelp,5] from 4759726 to 4759726,4759750 > >> (kafka.cluster.Partition) > >> … > >> > >> > >> and repeat shrink and expand after 30 minutes which is the default > >> value of leader.imbalance.check.interval.seconds, and at that time > >> we can find the log of controller’s auto rebalance，which can leads some > >> partition’s leader change to this restarted broker. > >> we have no shrink and expand when our cluster is running except when > >> we restart it，so replica.fetch.thread.num is 1，and it seems enough. > >> > >> we can reproduce it at each restart，can someone give some suggestions. > >> thanks before. > >> > >> > >> > >> > >> > >> > >> > >>
