Re: Flink task node shut it self off.
Hi, so far it seems stable. On Mon, 6 Jan 2020 at 14:16, John Smith wrote: > So I increased all the jobs to 1 minute checkpoint... I let you know how > it goes... Or of need to rethink gluster lol > > On Sat., Jan. 4, 2020, 9:27 p.m. John Smith, > wrote: > >> It seems to have happened again... Here is a screen shot of the system >> metrics for that day on that particular node >> >> https://www.dropbox.com/s/iudn7z2fvvy7vb8/flink-node.png?dl=0 >> >> >> On Fri, 3 Jan 2020 at 12:19, John Smith wrote: >> >>> Well there was this huge IO wait like over 140% spike. IO wait rose >>> slowly for couple hours then at some time it spiked at 140% and then after >>> IO wait dropped back to "normal" the CPU 1min 5min 15min spiked to like 3 >>> times the number of cores for a bit. >>> >>> We where at "peek" operation. I.e we where running a batch job when this >>> hapenned. On average operation the "business" requests per second from our >>> services is about 15 RPS when we do batches we can hit 600 RPS for a few >>> hours and then back down. Each business request underneath does a few round >>> trips back and forth between Kafka, cache systems Flink, DBs etc... So >>> Flink jobs are a subset of some parts of that 600 RPS. >>> >>> On Flink side we 3 task managers of 4 cores 8GB which are configured as >>> 8 slots, 5.4GB JVM, 3.77GB flink managed mem per task manager. We have 8 >>> jobs and 9 slots free. So the cluster isn't full yet. But we do see one >>> node is full. >>> >>> We use disk FS state (backed by GlusterFS) not rocks DB. We had enabled >>> 5 second checkpointing for 6 of the jobs... So just wondering if that was >>> possibly the reason for the IO wait... But regardless of the RPS mentioned >>> above the jobs will always checkpoint every 5 seconds... I had the chance >>> to increase checkpointing for a few of the jobs before the holidays. I am >>> back on Monday... >>> >>> On Fri., Jan. 3, 2020, 11:16 a.m. Chesnay Schepler, >>> wrote: >>> >>>> The logs show 2 interesting pieces of information: >>>> >>>> >>>> ... >>>> 2019-12-19 18:33:23,278 INFO >>>> org.apache.kafka.clients.FetchSessionHandler - [Consumer >>>> clientId=consumer-4, groupId=ccdb-prod-import] Error sending fetch >>>> request (sessionId=INVALID, epoch=INITIAL) to node 0: >>>> org.apache.kafka.common.errors.DisconnectException. >>>> ... >>>> 2019-12-19 19:37:06,732 INFO >>>> org.apache.flink.runtime.taskexecutor.TaskExecutor- Could not >>>> resolve ResourceManager address >>>> akka.tcp://flink@xx-job-0002:36835/user/resourcemanager, >>>> retrying in 1 ms: Ask timed out on >>>> [ActorSelection[Anchor(akka.tcp://flink@xx-job-0002:36835/), >>>> Path(/user/resourcemanager)]] after [1 ms]. Sender[null] sent message >>>> of type "akka.actor.Identify".. >>>> >>>> This reads like the machine lost network connectivity for some reason. >>>> The tasks start failing because kafka cannot be reached, and the TM then >>>> shuts down because it can neither reach the ResourceManager. >>>> >>>> On 25/12/2019 04:34, Zhijiang wrote: >>>> >>>> If you use rocksDB state backend, it might consume extra native memory. >>>> Some resource framework cluster like yarn would kill the container if >>>> the memory usage exceeds some threshold. You can also double check whether >>>> it exists in your case. >>>> >>>> -- >>>> From:John Smith >>>> Send Time:2019 Dec. 25 (Wed.) 03:40 >>>> To:Zhijiang >>>> Cc:user >>>> Subject:Re: Flink task node shut it self off. >>>> >>>> The shutdown happened after the massive IO wait. I don't use any state >>>> Checkpoints are disk based... >>>> >>>> On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, >>>> wrote: >>>> Hi John, >>>> >>>> Thanks for the positive comments of Flink usage. No matter >>>> at least-once or exactly-once you used for checkpoint, it would never lose >>>> one message during failure recovery. >>>> >>>> Unfortunatelly I can not visit the logs you
Re: Flink task node shut it self off.
So I increased all the jobs to 1 minute checkpoint... I let you know how it goes... Or of need to rethink gluster lol On Sat., Jan. 4, 2020, 9:27 p.m. John Smith, wrote: > It seems to have happened again... Here is a screen shot of the system > metrics for that day on that particular node > > https://www.dropbox.com/s/iudn7z2fvvy7vb8/flink-node.png?dl=0 > > > On Fri, 3 Jan 2020 at 12:19, John Smith wrote: > >> Well there was this huge IO wait like over 140% spike. IO wait rose >> slowly for couple hours then at some time it spiked at 140% and then after >> IO wait dropped back to "normal" the CPU 1min 5min 15min spiked to like 3 >> times the number of cores for a bit. >> >> We where at "peek" operation. I.e we where running a batch job when this >> hapenned. On average operation the "business" requests per second from our >> services is about 15 RPS when we do batches we can hit 600 RPS for a few >> hours and then back down. Each business request underneath does a few round >> trips back and forth between Kafka, cache systems Flink, DBs etc... So >> Flink jobs are a subset of some parts of that 600 RPS. >> >> On Flink side we 3 task managers of 4 cores 8GB which are configured as 8 >> slots, 5.4GB JVM, 3.77GB flink managed mem per task manager. We have 8 jobs >> and 9 slots free. So the cluster isn't full yet. But we do see one node is >> full. >> >> We use disk FS state (backed by GlusterFS) not rocks DB. We had enabled 5 >> second checkpointing for 6 of the jobs... So just wondering if that was >> possibly the reason for the IO wait... But regardless of the RPS mentioned >> above the jobs will always checkpoint every 5 seconds... I had the chance >> to increase checkpointing for a few of the jobs before the holidays. I am >> back on Monday... >> >> On Fri., Jan. 3, 2020, 11:16 a.m. Chesnay Schepler, >> wrote: >> >>> The logs show 2 interesting pieces of information: >>> >>> >>> ... >>> 2019-12-19 18:33:23,278 INFO >>> org.apache.kafka.clients.FetchSessionHandler - [Consumer >>> clientId=consumer-4, groupId=ccdb-prod-import] Error sending fetch >>> request (sessionId=INVALID, epoch=INITIAL) to node 0: >>> org.apache.kafka.common.errors.DisconnectException. >>> ... >>> 2019-12-19 19:37:06,732 INFO >>> org.apache.flink.runtime.taskexecutor.TaskExecutor- Could not >>> resolve ResourceManager address >>> akka.tcp://flink@xx-job-0002:36835/user/resourcemanager, >>> retrying in 1 ms: Ask timed out on >>> [ActorSelection[Anchor(akka.tcp://flink@xx-job-0002:36835/), >>> Path(/user/resourcemanager)]] after [1 ms]. Sender[null] sent message >>> of type "akka.actor.Identify".. >>> >>> This reads like the machine lost network connectivity for some reason. >>> The tasks start failing because kafka cannot be reached, and the TM then >>> shuts down because it can neither reach the ResourceManager. >>> >>> On 25/12/2019 04:34, Zhijiang wrote: >>> >>> If you use rocksDB state backend, it might consume extra native memory. >>> Some resource framework cluster like yarn would kill the container if >>> the memory usage exceeds some threshold. You can also double check whether >>> it exists in your case. >>> >>> -- >>> From:John Smith >>> Send Time:2019 Dec. 25 (Wed.) 03:40 >>> To:Zhijiang >>> Cc:user >>> Subject:Re: Flink task node shut it self off. >>> >>> The shutdown happened after the massive IO wait. I don't use any state >>> Checkpoints are disk based... >>> >>> On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, >>> wrote: >>> Hi John, >>> >>> Thanks for the positive comments of Flink usage. No matter at least-once >>> or exactly-once you used for checkpoint, it would never lose one message >>> during failure recovery. >>> >>> Unfortunatelly I can not visit the logs you posted. Generally speaking the >>> longer internal checkpoint would mean replaying more source data after >>> failure recovery. >>> In my experience the 5 seconds interval for checkpoint is too >>> frequently in my experience, and you might increase it to 1 minute or so. >>> You can also monitor how long will the checkpoint finish in your >>> application, then you can adjust the interval accordingly. >>> >>
Re: Flink task node shut it self off.
It seems to have happened again... Here is a screen shot of the system metrics for that day on that particular node https://www.dropbox.com/s/iudn7z2fvvy7vb8/flink-node.png?dl=0 On Fri, 3 Jan 2020 at 12:19, John Smith wrote: > Well there was this huge IO wait like over 140% spike. IO wait rose slowly > for couple hours then at some time it spiked at 140% and then after IO wait > dropped back to "normal" the CPU 1min 5min 15min spiked to like 3 times the > number of cores for a bit. > > We where at "peek" operation. I.e we where running a batch job when this > hapenned. On average operation the "business" requests per second from our > services is about 15 RPS when we do batches we can hit 600 RPS for a few > hours and then back down. Each business request underneath does a few round > trips back and forth between Kafka, cache systems Flink, DBs etc... So > Flink jobs are a subset of some parts of that 600 RPS. > > On Flink side we 3 task managers of 4 cores 8GB which are configured as 8 > slots, 5.4GB JVM, 3.77GB flink managed mem per task manager. We have 8 jobs > and 9 slots free. So the cluster isn't full yet. But we do see one node is > full. > > We use disk FS state (backed by GlusterFS) not rocks DB. We had enabled 5 > second checkpointing for 6 of the jobs... So just wondering if that was > possibly the reason for the IO wait... But regardless of the RPS mentioned > above the jobs will always checkpoint every 5 seconds... I had the chance > to increase checkpointing for a few of the jobs before the holidays. I am > back on Monday... > > On Fri., Jan. 3, 2020, 11:16 a.m. Chesnay Schepler, > wrote: > >> The logs show 2 interesting pieces of information: >> >> >> ... >> 2019-12-19 18:33:23,278 INFO >> org.apache.kafka.clients.FetchSessionHandler - [Consumer >> clientId=consumer-4, groupId=ccdb-prod-import] Error sending fetch >> request (sessionId=INVALID, epoch=INITIAL) to node 0: >> org.apache.kafka.common.errors.DisconnectException. >> ... >> 2019-12-19 19:37:06,732 INFO >> org.apache.flink.runtime.taskexecutor.TaskExecutor- Could not >> resolve ResourceManager address >> akka.tcp://flink@xx-job-0002:36835/user/resourcemanager, >> retrying in 1 ms: Ask timed out on >> [ActorSelection[Anchor(akka.tcp://flink@xx-job-0002:36835/), >> Path(/user/resourcemanager)]] after [1 ms]. Sender[null] sent message >> of type "akka.actor.Identify".. >> >> This reads like the machine lost network connectivity for some reason. >> The tasks start failing because kafka cannot be reached, and the TM then >> shuts down because it can neither reach the ResourceManager. >> >> On 25/12/2019 04:34, Zhijiang wrote: >> >> If you use rocksDB state backend, it might consume extra native memory. >> Some resource framework cluster like yarn would kill the container if the >> memory usage exceeds some threshold. You can also double check whether it >> exists in your case. >> >> -- >> From:John Smith >> Send Time:2019 Dec. 25 (Wed.) 03:40 >> To:Zhijiang >> Cc:user >> Subject:Re: Flink task node shut it self off. >> >> The shutdown happened after the massive IO wait. I don't use any state >> Checkpoints are disk based... >> >> On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, >> wrote: >> Hi John, >> >> Thanks for the positive comments of Flink usage. No matter at least-once >> or exactly-once you used for checkpoint, it would never lose one message >> during failure recovery. >> >> Unfortunatelly I can not visit the logs you posted. Generally speaking the >> longer internal checkpoint would mean replaying more source data after >> failure recovery. >> In my experience the 5 seconds interval for checkpoint is too frequently >> in my experience, and you might increase it to 1 minute or so. You can also >> monitor how long will the checkpoint finish in your application, then you >> can adjust the interval accordingly. >> >> Concerning of the node shutdown you mentioned, I am not quite sure >> whether it is relevant to your short checkpoint interval. Do you config to >> use heap state backend? The hs_err file really indicated that you job >> had encountered the memory issue, then it is better to somehow increase >> your task manager memory. But if you can analyze the dump hs_err file via >> some profiler tool for checking the memory usage, it might be more helpful >> to find the root cause. >> >> Best, >
Re: Flink task node shut it self off.
Well there was this huge IO wait like over 140% spike. IO wait rose slowly for couple hours then at some time it spiked at 140% and then after IO wait dropped back to "normal" the CPU 1min 5min 15min spiked to like 3 times the number of cores for a bit. We where at "peek" operation. I.e we where running a batch job when this hapenned. On average operation the "business" requests per second from our services is about 15 RPS when we do batches we can hit 600 RPS for a few hours and then back down. Each business request underneath does a few round trips back and forth between Kafka, cache systems Flink, DBs etc... So Flink jobs are a subset of some parts of that 600 RPS. On Flink side we 3 task managers of 4 cores 8GB which are configured as 8 slots, 5.4GB JVM, 3.77GB flink managed mem per task manager. We have 8 jobs and 9 slots free. So the cluster isn't full yet. But we do see one node is full. We use disk FS state (backed by GlusterFS) not rocks DB. We had enabled 5 second checkpointing for 6 of the jobs... So just wondering if that was possibly the reason for the IO wait... But regardless of the RPS mentioned above the jobs will always checkpoint every 5 seconds... I had the chance to increase checkpointing for a few of the jobs before the holidays. I am back on Monday... On Fri., Jan. 3, 2020, 11:16 a.m. Chesnay Schepler, wrote: > The logs show 2 interesting pieces of information: > > > ... > 2019-12-19 18:33:23,278 INFO > org.apache.kafka.clients.FetchSessionHandler - [Consumer > clientId=consumer-4, groupId=ccdb-prod-import] Error sending fetch > request (sessionId=INVALID, epoch=INITIAL) to node 0: > org.apache.kafka.common.errors.DisconnectException. > ... > 2019-12-19 19:37:06,732 INFO > org.apache.flink.runtime.taskexecutor.TaskExecutor- Could not > resolve ResourceManager address > akka.tcp://flink@xx-job-0002:36835/user/resourcemanager, > retrying in 1 ms: Ask timed out on > [ActorSelection[Anchor(akka.tcp://flink@xx-job-0002:36835/), > Path(/user/resourcemanager)]] after [1 ms]. Sender[null] sent message > of type "akka.actor.Identify".. > > This reads like the machine lost network connectivity for some reason. The > tasks start failing because kafka cannot be reached, and the TM then shuts > down because it can neither reach the ResourceManager. > > On 25/12/2019 04:34, Zhijiang wrote: > > If you use rocksDB state backend, it might consume extra native memory. > Some resource framework cluster like yarn would kill the container if the > memory usage exceeds some threshold. You can also double check whether it > exists in your case. > > ---------- > From:John Smith > Send Time:2019 Dec. 25 (Wed.) 03:40 > To:Zhijiang > Cc:user > Subject:Re: Flink task node shut it self off. > > The shutdown happened after the massive IO wait. I don't use any state > Checkpoints are disk based... > > On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, > wrote: > Hi John, > > Thanks for the positive comments of Flink usage. No matter at least-once > or exactly-once you used for checkpoint, it would never lose one message > during failure recovery. > > Unfortunatelly I can not visit the logs you posted. Generally speaking the > longer internal checkpoint would mean replaying more source data after > failure recovery. > In my experience the 5 seconds interval for checkpoint is too frequently > in my experience, and you might increase it to 1 minute or so. You can also > monitor how long will the checkpoint finish in your application, then you > can adjust the interval accordingly. > > Concerning of the node shutdown you mentioned, I am not quite sure whether > it is relevant to your short checkpoint interval. Do you config to use heap > state backend? The hs_err file really indicated that you job had > encountered the memory issue, then it is better to somehow increase your > task manager memory. But if you can analyze the dump hs_err file via some > profiler tool for checking the memory usage, it might be more helpful to > find the root cause. > > Best, > Zhijiang > > -- > From:John Smith > Send Time:2019 Dec. 21 (Sat.) 05:26 > To:user > Subject:Flink task node shut it self off. > > Hi, using Flink 1.8.0 > > 1st off I must say Flink resiliency is very impressive, we lost a node and > never lost one message by using checkpoints and Kafka. Thanks! > > The cluster is a self hosted cluster and we use our own zookeeper cluster. > We have... > 3 zookeepers: 4 cpu, 8GB (each) > 3 job nodes: 4 cpu, 8GB (each) > 3 task nodes: 4 cpu, 8GB (each) > The nod
Re: Flink task node shut it self off.
The logs show 2 interesting pieces of information: ... 2019-12-19 18:33:23,278 INFO org.apache.kafka.clients.FetchSessionHandler - [Consumer clientId=consumer-4, groupId=ccdb-prod-import] Error sending fetch request (sessionId=INVALID, epoch=INITIAL) to node 0: org.apache.kafka.common.errors.DisconnectException. ... 2019-12-19 19:37:06,732 INFO org.apache.flink.runtime.taskexecutor.TaskExecutor - Could not resolve ResourceManager address akka.tcp://flink@xx-job-0002:36835/user/resourcemanager, retrying in 1 ms: Ask timed out on [ActorSelection[Anchor(akka.tcp://flink@xx-job-0002:36835/), Path(/user/resourcemanager)]] after [1 ms]. Sender[null] sent message of type "akka.actor.Identify".. This reads like the machine lost network connectivity for some reason. The tasks start failing because kafka cannot be reached, and the TM then shuts down because it can neither reach the ResourceManager. On 25/12/2019 04:34, Zhijiang wrote: If you use rocksDB state backend, it might consume extra native memory. Some resource framework cluster like yarn would kill the container if the memory usage exceeds some threshold. You can also double check whether it exists in your case. -- From:John Smith Send Time:2019 Dec. 25 (Wed.) 03:40 To:Zhijiang Cc:user Subject:Re: Flink task node shut it self off. The shutdown happened after the massive IO wait. I don't use any state Checkpoints are disk based... On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, mailto:wangzhijiang...@aliyun.com>> wrote: Hi John, Thanks for the positive comments of Flink usage. No matter at least-once or exactly-once you used for checkpoint, it would never lose one message during failure recovery. Unfortunatelly I can not visit the logs you posted. Generally speaking the longer internal checkpoint would mean replaying more source data after failure recovery. In my experience the 5 seconds interval for checkpoint is too frequently in my experience, and you might increase it to 1 minute or so. You can also monitor how long will the checkpoint finish in your application, then you can adjust the interval accordingly. Concerning of the node shutdown you mentioned, I am not quite sure whether it is relevant to your short checkpoint interval. Do you config to use heap state backend? The hs_err file really indicated that you job had encountered the memory issue, then it is better to somehow increase your task manager memory. But if you can analyze the dump hs_err file via some profiler tool for checking the memory usage, it might be more helpful to find the root cause. Best, Zhijiang -- From:John Smith mailto:java.dev@gmail.com>> Send Time:2019 Dec. 21 (Sat.) 05:26 To:user mailto:user@flink.apache.org>> Subject:Flink task node shut it self off. Hi, using Flink 1.8.0 1st off I must say Flink resiliency is very impressive, we lost a node and never lost one message by using checkpoints and Kafka. Thanks! The cluster is a self hosted cluster and we use our own zookeeper cluster. We have... 3 zookeepers: 4 cpu, 8GB (each) 3 job nodes: 4 cpu, 8GB (each) 3 task nodes: 4 cpu, 8GB (each) The nodes also share GlusterFS for storing savepoints and checkpoints, GlusterFS is running on the same machines. Yesterday a node shut itself off we the following log messages... - Stopping TaskExecutor akka.tcp://fl...@xxx.xxx.xxx.73:34697/user/taskmanager_0. - Stop job leader service. - Stopping ZooKeeperLeaderRetrievalService /leader/resource_manager_lock. - Shutting down TaskExecutorLocalStateStoresManager. - Shutting down BLOB cache - Shutting down BLOB cache - removed file cache directory /tmp/flink-dist-cache-4b60d79b-1cef-4ffb-8837-3a9c9a205000 - I/O manager removed spill file directory /tmp/flink-io-c9d01b92-2809-4a55-8ab3-6920487da0ed - Shutting down the network environment and its components. Prior to the node shutting off we noticed massive IOWAIT of 140% and CPU load 1minute of 15. And we also got an hs_err file which sais we should increase the memory. I'm attaching the logs here: https://www.dropbox.com/sh/vp1ytpguimiayw7/AADviCPED47QEy_4rHsGI1Nya?dl=0 I wonder if my 5 second checkpointing is too much for gluster. Any thoughts?
Re: Flink task node shut it self off.
If you use rocksDB state backend, it might consume extra native memory. Some resource framework cluster like yarn would kill the container if the memory usage exceeds some threshold. You can also double check whether it exists in your case. -- From:John Smith Send Time:2019 Dec. 25 (Wed.) 03:40 To:Zhijiang Cc:user Subject:Re: Flink task node shut it self off. The shutdown happened after the massive IO wait. I don't use any state Checkpoints are disk based... On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, wrote: Hi John, Thanks for the positive comments of Flink usage. No matter at least-once or exactly-once you used for checkpoint, it would never lose one message during failure recovery. Unfortunatelly I can not visit the logs you posted. Generally speaking the longer internal checkpoint would mean replaying more source data after failure recovery. In my experience the 5 seconds interval for checkpoint is too frequently in my experience, and you might increase it to 1 minute or so. You can also monitor how long will the checkpoint finish in your application, then you can adjust the interval accordingly. Concerning of the node shutdown you mentioned, I am not quite sure whether it is relevant to your short checkpoint interval. Do you config to use heap state backend? The hs_err file really indicated that you job had encountered the memory issue, then it is better to somehow increase your task manager memory. But if you can analyze the dump hs_err file via some profiler tool for checking the memory usage, it might be more helpful to find the root cause. Best, Zhijiang -- From:John Smith Send Time:2019 Dec. 21 (Sat.) 05:26 To:user Subject:Flink task node shut it self off. Hi, using Flink 1.8.0 1st off I must say Flink resiliency is very impressive, we lost a node and never lost one message by using checkpoints and Kafka. Thanks! The cluster is a self hosted cluster and we use our own zookeeper cluster. We have... 3 zookeepers: 4 cpu, 8GB (each) 3 job nodes: 4 cpu, 8GB (each) 3 task nodes: 4 cpu, 8GB (each) The nodes also share GlusterFS for storing savepoints and checkpoints, GlusterFS is running on the same machines. Yesterday a node shut itself off we the following log messages... - Stopping TaskExecutor akka.tcp://fl...@xxx.xxx.xxx.73:34697/user/taskmanager_0. - Stop job leader service. - Stopping ZooKeeperLeaderRetrievalService /leader/resource_manager_lock. - Shutting down TaskExecutorLocalStateStoresManager. - Shutting down BLOB cache - Shutting down BLOB cache - removed file cache directory /tmp/flink-dist-cache-4b60d79b-1cef-4ffb-8837-3a9c9a205000 - I/O manager removed spill file directory /tmp/flink-io-c9d01b92-2809-4a55-8ab3-6920487da0ed - Shutting down the network environment and its components. Prior to the node shutting off we noticed massive IOWAIT of 140% and CPU load 1minute of 15. And we also got an hs_err file which sais we should increase the memory. I'm attaching the logs here: https://www.dropbox.com/sh/vp1ytpguimiayw7/AADviCPED47QEy_4rHsGI1Nya?dl=0 I wonder if my 5 second checkpointing is too much for gluster. Any thoughts?
Re: Flink task node shut it self off.
The shutdown happened after the massive IO wait. I don't use any state Checkpoints are disk based... On Mon., Dec. 23, 2019, 1:42 a.m. Zhijiang, wrote: > Hi John, > > Thanks for the positive comments of Flink usage. No matter at least-once > or exactly-once you used for checkpoint, it would never lose one message > during failure recovery. > > Unfortunatelly I can not visit the logs you posted. Generally speaking the > longer internal checkpoint would mean replaying more source data after > failure recovery. > In my experience the 5 seconds interval for checkpoint is too frequently > in my experience, and you might increase it to 1 minute or so. You can also > monitor how long will the checkpoint finish in your application, then you > can adjust the interval accordingly. > > Concerning of the node shutdown you mentioned, I am not quite sure whether > it is relevant to your short checkpoint interval. Do you config to use heap > state backend? The hs_err file really indicated that you job had > encountered the memory issue, then it is better to somehow increase your > task manager memory. But if you can analyze the dump hs_err file via some > profiler tool for checking the memory usage, it might be more helpful to > find the root cause. > > Best, > Zhijiang > > -- > From:John Smith > Send Time:2019 Dec. 21 (Sat.) 05:26 > To:user > Subject:Flink task node shut it self off. > > Hi, using Flink 1.8.0 > > 1st off I must say Flink resiliency is very impressive, we lost a node and > never lost one message by using checkpoints and Kafka. Thanks! > > The cluster is a self hosted cluster and we use our own zookeeper cluster. > We have... > 3 zookeepers: 4 cpu, 8GB (each) > 3 job nodes: 4 cpu, 8GB (each) > 3 task nodes: 4 cpu, 8GB (each) > The nodes also share GlusterFS for storing savepoints and checkpoints, > GlusterFS is running on the same machines. > > Yesterday a node shut itself off we the following log messages... > - Stopping TaskExecutor akka.tcp://fl...@xxx.xxx.xxx.73 > :34697/user/taskmanager_0. > - Stop job leader service. > - Stopping ZooKeeperLeaderRetrievalService /leader/resource_manager_lock. > - Shutting down TaskExecutorLocalStateStoresManager. > - Shutting down BLOB cache > - Shutting down BLOB cache > - removed file cache directory > /tmp/flink-dist-cache-4b60d79b-1cef-4ffb-8837-3a9c9a205000 > - I/O manager removed spill file directory > /tmp/flink-io-c9d01b92-2809-4a55-8ab3-6920487da0ed > - Shutting down the network environment and its components. > > Prior to the node shutting off we noticed massive IOWAIT of 140% and CPU > load 1minute of 15. And we also got an hs_err file which sais we should > increase the memory. > > I'm attaching the logs here: > https://www.dropbox.com/sh/vp1ytpguimiayw7/AADviCPED47QEy_4rHsGI1Nya?dl=0 > > I wonder if my 5 second checkpointing is too much for gluster. > > Any thoughts? > > > > > >
Re: Flink task node shut it self off.
Hi John, Thanks for the positive comments of Flink usage. No matter at least-once or exactly-once you used for checkpoint, it would never lose one message during failure recovery. Unfortunatelly I can not visit the logs you posted. Generally speaking the longer internal checkpoint would mean replaying more source data after failure recovery. In my experience the 5 seconds interval for checkpoint is too frequently in my experience, and you might increase it to 1 minute or so. You can also monitor how long will the checkpoint finish in your application, then you can adjust the interval accordingly. Concerning of the node shutdown you mentioned, I am not quite sure whether it is relevant to your short checkpoint interval. Do you config to use heap state backend? The hs_err file really indicated that you job had encountered the memory issue, then it is better to somehow increase your task manager memory. But if you can analyze the dump hs_err file via some profiler tool for checking the memory usage, it might be more helpful to find the root cause. Best, Zhijiang -- From:John Smith Send Time:2019 Dec. 21 (Sat.) 05:26 To:user Subject:Flink task node shut it self off. Hi, using Flink 1.8.0 1st off I must say Flink resiliency is very impressive, we lost a node and never lost one message by using checkpoints and Kafka. Thanks! The cluster is a self hosted cluster and we use our own zookeeper cluster. We have... 3 zookeepers: 4 cpu, 8GB (each) 3 job nodes: 4 cpu, 8GB (each) 3 task nodes: 4 cpu, 8GB (each) The nodes also share GlusterFS for storing savepoints and checkpoints, GlusterFS is running on the same machines. Yesterday a node shut itself off we the following log messages... - Stopping TaskExecutor akka.tcp://fl...@xxx.xxx.xxx.73:34697/user/taskmanager_0. - Stop job leader service. - Stopping ZooKeeperLeaderRetrievalService /leader/resource_manager_lock. - Shutting down TaskExecutorLocalStateStoresManager. - Shutting down BLOB cache - Shutting down BLOB cache - removed file cache directory /tmp/flink-dist-cache-4b60d79b-1cef-4ffb-8837-3a9c9a205000 - I/O manager removed spill file directory /tmp/flink-io-c9d01b92-2809-4a55-8ab3-6920487da0ed - Shutting down the network environment and its components. Prior to the node shutting off we noticed massive IOWAIT of 140% and CPU load 1minute of 15. And we also got an hs_err file which sais we should increase the memory. I'm attaching the logs here: https://www.dropbox.com/sh/vp1ytpguimiayw7/AADviCPED47QEy_4rHsGI1Nya?dl=0 I wonder if my 5 second checkpointing is too much for gluster. Any thoughts?
Re: Flink task node shut it self off.
hi john in our experience , the checkpoint interval we set interval 1-10 minute and timeout usurally 5*interval . mostly we set 2 or 5 minute and 10 or 20timeout. it depend on u data bulk per second and which window used. John Smith 于2019年12月21日周六 上午5:26写道： > Hi, using Flink 1.8.0 > > 1st off I must say Flink resiliency is very impressive, we lost a node and > never lost one message by using checkpoints and Kafka. Thanks! > > The cluster is a self hosted cluster and we use our own zookeeper cluster. > We have... > 3 zookeepers: 4 cpu, 8GB (each) > 3 job nodes: 4 cpu, 8GB (each) > 3 task nodes: 4 cpu, 8GB (each) > The nodes also share GlusterFS for storing savepoints and checkpoints, > GlusterFS is running on the same machines. > > Yesterday a node shut itself off we the following log messages... > - Stopping TaskExecutor akka.tcp://fl...@xxx.xxx.xxx.73 > :34697/user/taskmanager_0. > - Stop job leader service. > - Stopping ZooKeeperLeaderRetrievalService /leader/resource_manager_lock. > - Shutting down TaskExecutorLocalStateStoresManager. > - Shutting down BLOB cache > - Shutting down BLOB cache > - removed file cache directory > /tmp/flink-dist-cache-4b60d79b-1cef-4ffb-8837-3a9c9a205000 > - I/O manager removed spill file directory > /tmp/flink-io-c9d01b92-2809-4a55-8ab3-6920487da0ed > - Shutting down the network environment and its components. > > Prior to the node shutting off we noticed massive IOWAIT of 140% and CPU > load 1minute of 15. And we also got an hs_err file which sais we should > increase the memory. > > I'm attaching the logs here: > https://www.dropbox.com/sh/vp1ytpguimiayw7/AADviCPED47QEy_4rHsGI1Nya?dl=0 > > I wonder if my 5 second checkpointing is too much for gluster. > > Any thoughts? > > > > >
Flink task node shut it self off.
Hi, using Flink 1.8.0 1st off I must say Flink resiliency is very impressive, we lost a node and never lost one message by using checkpoints and Kafka. Thanks! The cluster is a self hosted cluster and we use our own zookeeper cluster. We have... 3 zookeepers: 4 cpu, 8GB (each) 3 job nodes: 4 cpu, 8GB (each) 3 task nodes: 4 cpu, 8GB (each) The nodes also share GlusterFS for storing savepoints and checkpoints, GlusterFS is running on the same machines. Yesterday a node shut itself off we the following log messages... - Stopping TaskExecutor akka.tcp://fl...@xxx.xxx.xxx.73 :34697/user/taskmanager_0. - Stop job leader service. - Stopping ZooKeeperLeaderRetrievalService /leader/resource_manager_lock. - Shutting down TaskExecutorLocalStateStoresManager. - Shutting down BLOB cache - Shutting down BLOB cache - removed file cache directory /tmp/flink-dist-cache-4b60d79b-1cef-4ffb-8837-3a9c9a205000 - I/O manager removed spill file directory /tmp/flink-io-c9d01b92-2809-4a55-8ab3-6920487da0ed - Shutting down the network environment and its components. Prior to the node shutting off we noticed massive IOWAIT of 140% and CPU load 1minute of 15. And we also got an hs_err file which sais we should increase the memory. I'm attaching the logs here: https://www.dropbox.com/sh/vp1ytpguimiayw7/AADviCPED47QEy_4rHsGI1Nya?dl=0 I wonder if my 5 second checkpointing is too much for gluster. Any thoughts?
