Kafka rebalance takes a long time. Follow asked Dec 12, 2019 at 2:13.

Kafka rebalance takes a long time Deleting obsolete state directory 0_45 for task 0_45 as 601021ms has elapsed (cleanup delay is 600000ms). Commented May 14, 2024 at 23:38. Often I don't see anything for minutes and give up. *Kafka Configuration: * 5 kafka brokers; Kafka Topics - 15 partitions and 3 replication factor. During a rebalance I am using spring cloud stream Kafka sync producer in a spring boot micro service. Although Kafka All I mean is that, say your consumer takes exactly 2 minutes to process its records. Spring Boot Kafka: Commit cannot be completed since the group has already rebalanced. Modified 6 years, 9 months ago. Consumer There's no well-defined scheme to know when rebalance is done. When it does reprocessing of events can occur due to the latest offset not being committed for a given offset. age. Are there any tunables/configs for kafka streams balancing (rebalancing) Questions: What causes application to rebalance endlessly while starting (even though there are no errors/exception, etc). When I run. Introduction. Note: Please note if the max poll increased a lot it will delay a group rebalance because consumer rebalance to join only when poll get called. Which leaves us to the limit of max. kafka. If we slept for the configured 4 minutes, we would exceed the 5 minutes and cause a rebalance; the container will reduce its sleep time to 3 minutes (- 5 seconds to avoid a race). In this article, we’ll explore consumer processing of Kafka messages with delay using Spring Kafka. When consumer was start pulling messages from Kafka topic & it took more time while processing the message. id, takes about 60s until it rebalances to receive messages again. ms was introduced via KIP-62 (part of Kafka 0. During a rebalance The Problem. So when rebalance starts Kafka will wait until your process is finished or 12 hours is passed. I use Kafka 1. But that first poll(), which has the sole purpose of setting the high water mark can take up to 20 seconds to complete, regardless of what Using Kafka as a Job queue for scheduling long running process is not a good idea as Kafka is not a queue in the strictest sense and semantics for failure handling and retries are limited. The rebalancing procedures all take longer, since even basic things like partition revocation/initialization have higher latency This means that the time between subsequent calls to poll() was longer than the configured max. ms: The configuration controls the maximum amount of time the client will wait for the response of a request. 12 Kafka consumer, very long rebalances. I am polling inside a loop. version>Elmhurst. Please note, I am My kafka version is kafka_2. It is used by reputed companies such as LinkedIn, Yahoo, Netflix, Twitter, Uber and many Kafka tries to rebalance partitions every time rolling new code on each machine. Duplicates cannot be avoided if a forced rebalance takes place because your listener took too long to process the records received by the poll(). A longer delay means potentially fewer rebalances, but increases the time until processing begins. 9. How can I load balance the leader? Your observation an reasoning is correct. My $0. Google KIP-62 for more information. The danger in making this lower is if you take too long to process the messages a rebalance might occur because the co-ordinator will think your consumer is dead. Ideally it should become stable after some time. if your processing takes longer that max. kafka Partition Rebalance. Tools like Prometheus, Grafana, and Kafka Manager offer real-time data visualization. CommitFailedException: Commit cannot be completed due to group rebalance. ms time exceeds will it run in the background and rebalancing will be triggered . The consumer leaves the consumer group with successful rd_kafka_consumer_close() and rd_kafka_destroy() and the process terminates. I have a Service that consumes kafka messages and triggers a long process. Add a comment | Kafka consumer, very long rebalances. What I do: running Kafka in Docker locally (broker, zookeeper, schema registry and control center) created a topic with 2 partition kafka-reassign-partitions This command moves topic partitions between replicas. Before KIP-62, there was only session. Assume processing a Analysis of rebalance time in Apache Kafka and partition assignment strategies - mssrinivas/Kafka-Performance-Tuning. so recovering from errors can take a very long time. ms) to process a message, thus that particular consumer is occupied and other new messages will be assigned to other partitions. 6 Kafka Consumer Rebalancing takes too long. During a rebalance Dynamic Partition Assignment: Kafka's default strategy allows for more flexibility by automatically distributing partitions among available consumers in a group. ms-- if poll() is not called before this timeout (e. Kafka Streams (can be) massively stateful: this makes pretty much all aspects of rebalancing more difficult, as discussed in the earlier blog post Don't Panic: The Definitive Guide to Kafka Streams State. ms, rebalancing rearranges partitions. Unsurprisingly, this problem is notorious in Kafka / Kafka’s stream applications world. By trusting it blindly, you will stress your Kafka cluster for nothing. I wouldn't recommend this option. Consumer B, starts and joins the group. The problem I'm facing is the processing of each message in the consumer takes a long time (~20 seconds), since it needs to call a really slow external system. How can I make this a concurrent processing and process messages in parallel? spring-kafka processing the same message multiple times with Now let’s go into the details of how rebalancing takes place. sh --delete --zookeeper localhost:2181 --topic myTopic If your topics were large enough (and you might possibly had a high replication factor as well), then that's something This is confusing coming from Kafka 0. 16. 1 and <spring-cloud. for leader restart) for the entire rolling bounce, which will significantly improves the availability of the MirrorMaker pipeline How can I add 3 more new broker servers and alter topic's partition amount to 6, and end up with a data rebalance result of each of the 6 partitions takes up 500GB disk space on its broker? I think this problem is critical for storing large amount of Given this, the second option is better, since it takes less time. I am using Spring 2. Kafka consumer, very long rebalances. sh tool, you must manually save the JSON file of the reassignment configuration. The logs should tell you which has caused rebalance, but it is usually the former. An awesome blog to know more about it - https: Kafka consumer, very long rebalances. x: there are plenty of fixes in the Apache Kafka client and respective improvement in the Spring for Apache Kafka. Logs attached below, as well as a monitoring screen capture that shows Kafka slowly going through log files, populating disk cache. To do so, I could use OffsetsForTimes to get the desired offset and Commi The processing of a single event takes around 3. By making the Kafka brokers near-stateless, operations like scaling up or down clusters and handling broker failures no longer need expensive rebalance operations. RELEASE' to create a batch consumer and I'm trying to understand how the consumer rebalancing works when my record processing time exceeds max. Ok, thanks for the suggestions. 2. If a consumer stop sending heartbeat for long time and its session will time out (controlled by session. Outdated 1. These tools track metrics such as consumer lag, partition distribution, and network latency. This is called heartbeat. . If the task is pretty long lasting then almost all workers will take the same task and process it completely inhibiting the distributing nature. This triggers the incremental rebalance. So a rebalance should only occur if the listener takes longer than max. configuration metadata required for maintaining the cluster This command looks for zookeeper-server-start file and What happens to the long processing record when max. server:type=group-coordinator-metrics,name=batch-flush-time-ms-max; kafka. 12. Viewed 3k times 1 . Help people to understand your problem better: Try to describe your What version are you using? Since KIP-62 (Kafka 0. Anyone has any idea how to solve rebalancing issue in kafka While Kafka is rebalancing, all involved consumers' processing is blocked (Incremental rebalancing aims to revoke only partitions that need to be transferred to other consumers, and thus, does In this article, we will explore how the use of pause-resume methods in combination with the asynchronous implementation provided by Spring Boot can be a good solution to avoid these problems. 5 milliseconds and the stream is stateless. You only need to set idleBetweenPolls if you want to slow your consumers down Kafka's consumer rebalance protocol was groundbreaking. max. Same goes for bullet #3. kafka. Consumer Group rebalance is a critical part of how Kafka Kafka producers doesn't directly send messages to their consumers, rather they send them to the brokers. Permalink. KIP-62, decouples heartbeats from calls to poll() via a background heartbeat thread, allowing for a longer processing time (ie, time between two consecutive poll()) than heartbeat interval. 0), heartbeats are sent in the background by the kafka-clients. What happens when you start the consumer up with a non existing topic is that the brokers autocreate this topic, but this takes a little bit of time with leader election etc. poll. Figure 2: Incremental Rebalance. 9 is more of a downgrade for this scenario, instead of "just in time" rebalancing, this becomes either high frequency polling with overhead, or low frequency polling with long times before it reacts to new topics/partitions. Currently, adding new topics requires restarting mirror maker with the configuration update. Kafka Rebalance happens when a new consumer is either added (joined) into the consumer group or removed (left). Whether the consumer leaves a group and a rebalance is triggered or not is quite immaterial to the behaviour of the producer. It can take more than 10 min to process one message. There's broker level config called group. This happens even if it is the only consumer. As far delete. ms (ie, Kafka 0. Sometimes, in order to process that batch, it takes longer than max. 2. Note that it will also delay group rebalances since the consumer will only join the rebalance inside the call to poll. ("Paused consumer resumed by Kafka due to rebalance; " + "consumer paused again, so the I'm writing a Go service that works with Kafka. Its due to Kafka's scheduled rebalance delay. When it was first released over a decade ago, dynamic task allocation was something only few advanced systems could benefit from but the Kafka client made it simple to dynamically scale applications reading from Kafka, so long as your application was stateless (which many initial ones were). 0 but after upgrading to 2. ms you can tweak. initial. rebalance. They are essentially read-only services that only read in a state topic and write it to the state store, from where customer requests are served via REST. consumer. setnx(key, val) and see a result that indicates "key does not exist" (at the time each transaction started, the key did not exist); 4. If the processing after the first poll takes long time, the second consumer might fail to send the heartbeat to the groupcoordinator, as sending of heartbeat happens in the poll() method, and that would trigger rebalance, and this will cause a deadlock like situation. The only risk this presents is that if your cache setup takes a long time, Kafka may refuse to accept new messages from the upstream producer at some point. The consumer group rebalance has been redesigned in Kafka 4. The accepted response above (from serejja) was correct in the past. Kafka Consumer Rebalancing takes too long. Now we don’t need to worry about heartbeats since consumers use a separate thread to perform these (see KAFKA-3888) and they are not part of polling anymore. It should be set to a value that is longer than the processing time for all the records fetched during the poll (max. When a new consumer joins or exits a group, Kafka must rebalance the partitions across the available consumers. To minimize this lag, it’s important What if another consumer (c1) leads to rebalance (cannot send heartbeat or didn't poll() for a long time ()). 3. One is user thread from which poll is called; the other is heartbeat thread that specially takes care of heartbeat things. Kafka warns: The use case is that my consumer does some I/O job that takes a long time, occasionally. Session timeout is set to 40s. real-time data streams, Apache Kafka®️, and its Consider this scenario: Kafka topic with 6 partitions. 3 (release date June 2019) and above. so you can interrupt your ongoing work in case the consumer group needs to rebalance. 5. Ask Question Asked 6 years, 9 months ago. plus, I would like to share one more scenario that I encountered: my program customized a ConsumerRebalanceListener, when the first time poll call triggered the rebalance, my program will do a lot of initialize jobs, some of the jobs involves interaction with kafka meta data which takes longer time than 5mins or so, and then it'll give me the Overview. In your case you set max. Back in old days and old Kafka versions there How to reduce kafka's rebalance time ? It takes a lot of time to rebalance each time. sleep(80000) (which I guess is a metaphor for a long running process) is actually breaking the contract that say that at any point in time, there should be only one consumer (alive) per topic partition withing that consumer group. The default is 30 seconds and the co-ordination won't trigger a rebalance until this time has passed E. ms) then group coordinator will If Kafka consumer takes too long to handle a message and subsequent poll() is delayed, Kafka will re-appoint this partition to another consumer and the message will be processed again (and again). If the response is not received before the timeout elapses the client will This mean each poll will happen before the poll-time-out by default it is 5 minutes. This way, you can perform the O&M task in different time periods. ms is the max time between polls from the consumer. So if processing a single message takes longer than the session timeout, the consumer will never be able to progress. So if consumer didn’t contact Kafka in time then let’s assume it is dead, otherwise it is still up and running and is a valid member of its consumer group. 0 or upwards where each consumer instance employs two threads to function. ms" time to detect changement :-/ – Thomas Decaux. 11 1 1 bronze badge. Consumer again takes a lot of time to process and since is unable to finish processing in less than max. There is no real way to tell if a particular message is going to take a long time to process or not. a consumer fails or no response is received for a long time, Kafka starts the rebalance process. Your first bullet probably the most effective way of dealing with this at this point. Therefore, it is essential to close the consumer after usage or to always use the same instance instead of creating new KafkaConsumer object for every message/iteration. For some reasons during rebalance consumer A takes long time to finish onPartitionsRevoked what would happen to B? does B take over all the topics Apache Kafka is a popular distributed event streaming platform used for data pipelines, streaming analytics, data integration, and mission-critical applications. Wondering why this might be happening and what are some possible options to avoid the same? Rebalance timeout is equal to max. sh --describe --zookeeper rhost:2181. ms and/or reduce max. During a rebalance Viewed 411 times 0 . both threads call jedis. I would like to start consuming messages from a given time onwards. This happens even if it is the only We wanted to upgrade to kafka 0. 4. Here are the 2 parameters which can be tuned max. Make the timeout period longer or request smaller batches. g. This communicates to the brokers that the consumer is active and still subscribed to that topic/partition, only taking a long time to process. Follow asked Dec 12, 2019 at 2:13. As far as Kafka is concerned, this is true in your test: consumer 1 is considered dead since it missed its timeout, and the sole [2021-04-07 02:42:22,708] INFO [GroupCoordinator 0]: Preparing to rebalance group PortfolioEnrichmentGroup14 in state PreparingRebalance with old generation 1 (__consumer_offsets-17) (reason: removing member PortfolioEnrichmentConsumer13-9aa71765-2518- 493f-a312-6c1633225015 on heartbeat expiration) What happens to the consumer if Kafka cluster goes down for a long time (couple of hours)? Will it receive messages after Kafka is up again? apache-kafka; kafka-consumer-api; Share. You should see logs like this, while your listener is sleeping It takes time to understand what’s inside these files and what exactly it does. It seems to be trying to recover certain corrupt log entries, takes a looong time, and then hangs up with SIGTERM. This is necessary to ensure all consumers have an up-to-date view of the partition assignments before re-consuming data. NET client version 1. The amount of time the group coordinator will wait for more consumers to join a new group before performing the first rebalance. utils It is better to give the consumers an ID to reduce the rebalance time, right? If the consumers logically are separated and consume different topics, is it better to put them in separate consumer groups? kafka group rebalancing takes a long time. Otherwise, it will await the passed timeout. You can increase max. both threads start a Redis transaction; 3. If you want to monitor the O&M process by using the kafka-reassign-partitions. Figure 3. The restarted consumer, with the same group. delay. This is a potentially recurring rebalance that is used to “probe” the readiness of warmup tasks. less frequent rebalances and longer reaction time to identify dead consumers. We experienced this issue before on Kafka 2. But once you’ll figure that out, life becomes a breeze and you’ll notice the difference it makes to your data. 0, zookeeper 3. If the timeout expires, an empty record set will be returned. Let's get to work! Following the implementation path of the pause-consume pattern, a service has been developed that incorporates key modifications to address the challenges posed by large or highly Failing to do this may see partitions lag briefly since the group coordinator will need to wait for the consumer’s session to time out before permitting a rebalance to occur. ms is for heartbeat thread. The broker expects a When Kafka is managing the group membership, a partition re-assignment will be triggered any time the members of the group change or the subscription of the members changes. servers is not valid (io. ms to 12 hours. Is there any timeout properties for this case in order to let Consumer work for at least 10 minutes and Kafka will not repeat the same message until this time? – A consumer group rebalance occurs when there is a change in the set of consumers or partitions, which causes Kafka to stop processing messages temporarily, reassign partitions, and then resume Another common cause of constant rebalancing is that one or more consumers is taking longer than the timeout period to send a heartbeat. 3. ms to a higher value and max. Let’s say for example that consumer 1 executes a database query which takes a long time(30 minutes) Long processing consumer. properties you can simply delete the topic using ; bin/kafka-topics. Incremental Cooperative Rebalancing. I have observed Kafka re-assigning the partitions on all consumers, and rarely not. Of course, would be better to upgrade to the latest clients at all: they can talk to older brokers anyway. ms, this is where rebalancing occurs and partition is pulled from consumer 1 and assigned to consumer 2. keep repeating in a loop. timeout: From the Kafka documentation for the poll method: This method returns immediately if there are records available. topic. ms, rebalance happened and the same situation will happened to another consumer. up vote 0 down vote favorite 1 I have a Kafka Streams Application which takes data from few topics and joins the data and puts it in another topic. If consumers failed before committing to Kafka, next time Consumers will consume the same records again which reproduce duplicate on the consumer side. I have two brokers in the cluster, 4 topics and each topic has 4 partitions. timeout. First poll--> with 100 records --> process 100 records (took 1 minute) --> consumer submitted offset Thanks. But, like any complex system, it comes with its own set of headaches—especially when it comes to partition rebalancing. Rebalance Process. Improve this question. Closed jfealy opened Once the first consumer leaves the group, the rebalance ends, the second GET request executes & my process unblocks. I am getting commitfailedexcption because of group rebalance, when code try to execute consumer. It does not only occur when the broker is the active controller. 8 where there was true triggering based on zookeper watches, instead of polling. – Based on #673 I am polling quickly on the consumer to set the high water mark once it is created. IMO 0. 2-0. Duplicate processing issue. 7. It becomes dramatic during application service deployment rollout, as The output of the above command keeps on changing - from 0 to some variable number. 0 and earlier). but this takes "consumer. connection. Add a If your Kafka environment is static, that is, new brokers and partitions are not created while your application is running, then consider configuring metadata. processing the batch for a long time" but the configuration advice is for a different problem. Kafka takes partitions 0 to 4 and assigns them to the second instance. The problem is after that we process a unique message from the Kafka partition twice(I check there is no duplicate in Kafka partitions and the message is unique). ms which controls how often the consumer forces a refresh of metadata for a topic. Kafka Connect : "Task already exists in this worker" 1. Message The restarted consumer, with the same group. If you’ve been working with Kafka long enough, you know its power when it comes to real-time data streaming. In this case, Kafka Rebalancing can trigger frequently We have been performing load tests for this processor and the messages in the topic are growing, which is causing the stream processor to take long time (~1 hour) to consume the changelog topics and initialize the state stores when there's a restart/redeployment happens. You can add a ConsumerRebalanceListener to the container properties to log rebalances. session. The initial solution was to set max. OneCricketeer OneCricketeer. records. This sounds like it shouldn’t be highly variable, but it Sarama has MaxProcessingTime as a config parameter similar to the Java client's max. If Consumer A takes too long to process a batch and times out then it is removed from the consumer group triggering a rebalance. max. RELEASE. 11 , we have updated our http services (3 node cluster) to use new Kafka consumer API , but it takes rebalancing of consumer (multiple consumer under Here are some common scenarios that trigger a consumer rebalance in Kafka. This stop-the-world effect is known for a while in the context of Kafka client applications. The version of kafka I'm running is 0. ms to a very long time duration, so the metadata is kept in the cache longer. records to a lower value than default. This can occur when processes die, new process instances are The rebalance process may involve multiple rebalances, depending on the number of tasks and the time it takes for instances to close out tasks. sh kafka-topics. sh tool to split the O&M task. 9 and new java consumer. Partitions 1 and 2 are continuously consumed, and partition 3 is only down for the time it takes to transfer ownership from consumer A to C. Few millions of records are consumed/produced every hour. two separate threads each read a separate, duplicate message from Kafka; 2. I have 8 streaming threads for the topic i want to subscribe to and that topic has 64 partitions. Regular monitoring and consistent configurations across nodes ensure smooth operations. The messages are dealing with calling external programs that could takes seconds or minutes to process. I have a problems with bad commits when broker rebalances. How long should a rebalance take? Roughly the time it takes for all members of the group to rejoin and sync. A pause() takes effect just before the next poll(); a resume() takes effect just after the current poll() returns. As an example, recovering from a broker failure with Tiered Storage takes seconds in comparison to hours or days without. Updating Kafka The most important approach to Kafka Rebalancing is to tune Kafka timeout parameters. There are two causes of a rebalance, too long between polls or too long between heartbeats. By default, state store data is backed by Kafka topics. So, both your consumers I understand a rebalance can occur at any point and time on your stream. The instances have separate applicationIds, so they each replicate the complete input topic for fault-tolerance. Extreme cases it goes on for 9s. To minimize this lag, it’s important . If you get a heartbeat failure because the group is rebalancing, it indicates that your consumer instance took too long to send the next heartbeat and was considered dead and thus a rebalance got triggered. To make things worse, I can no longer consume/produce on the affected topics in their entirety. It is not always the same broker that takes a long time. Kafka group rebalance average time on the microservice #1: a single applicative instance will be started at a given time. When new instance of application appears, there is rebalancing and if there are actaully processing jobs, messages from other partitions are suspended (because partitions/groups are revoked). The idea is that a consumer does Consumer re-balance takes extremely long time (extremely light set up) #611. Note we have set Garbage collection taking very long time, at times. 10. If coordinator fails to get any heartbeat from a consumer before this time interval I am using Confluent. Apache Kafka is a widely popular distributed streaming platform which is used by thousands of companies in order to build scalable, high-throughput, and reliable real-time streaming I think that the first part of Giorgos answer is correct, up to ". 2 Kafka producer not distributing From the perspective of a user that does not own a whole Connect cluster this is unintuitive. In my case, cache setup is very fast The Thread. However, once a stable assignment is produced with no follow-up rebalances, it indicates that the rebalance process is complete and the cluster has converged. Read the documentation. ms = 6000 (basically the default config) Viewed 3k times 0 . In multiple consumers (for different topics) within 1 group, if consumer declear as dead - the whole group will rebalance, it will trigger rebalance for every topic in that group, or only the topic that the consumer is attached? When StreamListener is taking a long time (longer than max. kafka group rebalancing takes a long time. Introduction to Kafka Rebalance. ms from the time of the current rebalance, or 10 minutes by default. Batch flush time sensor - measures how long it takes to write a record batch to the log. Kafka version 0. 2 Random partitioner does not distribute messages between Kafka topic partitions. ms // The maximum amount of time the consumer expects a message takes to // process for the user. You start "produce_n()" in one REPL and consume() in another. No, regarding to Spring Kafka document, when the consumer is paused, it continue to send the poll() request to prevent the rebalance, so you no need other thread to do that by yourself. from around 10 up to 45 seconds. zookeeper tickTime = 2000. heartbeat failed for group because it's rebalancing. server:type=group-coordinator-metrics,name=batch-flush-time-ms-p50 I'm using spring-kafka '2. Since Kafka 2. This happens because the consumer is processing the batch for a long time (and heartbeats are not being sent) and therefore the brokers think that consumer was lost and they start re-balancing. It can happen Kafka rebalancing plays a crucial role in maintaining efficient data distribution and system performance. RELEASE</spring-cloud. A rebalance takes place if you add a consumer to an existing ConsumerGroup. The longer a rebalance takes, the greater the consumer lag could be when all of the consumers eventually come online. To guarantee not to consume duplicate messages the job's execution and the committing offset must be atomic to guarantee exactly-once delivery semantic at the consumer side. In this case, use a scheduled task (not from kafka, use some standard way on your os / language / custom app / whatever) to send the message at the given time This can lead to a domino effect, where multiple JoinGroup requests cause the rebalance to occur multiple times, thus causing the rebalance time to take significantly longer than usual. I have a Kafka consumer that consumes large amounts of data from a Kafka topic with 9 partitions. Here is how the protocol Instead of sitting idle for the entire rebalance, consumer A’s downtime lasts only as long as it takes to revoke one partition. There is nothing that is not in the script. e. At that point consumer c2 is still consuming message. both threads proceed with Heartbeats are the basic mechanism to check if all consumers are still up and running. This can happen when it takes a long time to process one batch of data. Kafka doesn't rebalance; consumer groups do. 1). Kafka . I wrote function test for my system on Java. @param timeout: The maximum time to block (must not be greater than {@link Long#MAX_VALUE} milliseconds) Let's say there are two consumers in the same thread. 0. 4, all stream applications use the incremental cooperative rebalancing protocol to speed up every rebalancing. Even with this option, the consumer may be kicked out of the group if processing a single record takes too long. You want to push a message at a specific time (for example, an event "start job"). 1. After working with Kafka for a while, I encountered an issue of having to add new capacity and balance it several times after that. Currently no new message is consumed until "doSomething()" method finishes. As per my limited understanding the kafka consumer( Spring kafkalistener) service gets halted / restarted and the records get assigned to other consumers in the group during rebalancing Message processing time varies unpredictably. Depending on the amount of data you have, this may take some time. every time we deploy the service the very first call to kafka takes more than 20 seconds to publish the message to Topic. Whenever I take any kafka broker down, it goes into rebalancing and it takes approx. After the time is greater than max. See Kafka Consumer Group Rebalance - The Next-Gen Protocol for more. 4. Kafka Consumer being Starved because of unbalance. no heartbeat for 30 seconds. Another issue seen is the occurrence of these If Consumer A takes too long to process a batch and times out then it is removed from the consumer group triggering a rebalance. 192k 20 20 gold badges 141 141 silver badges 267 267 bronze badges. 6. 7. confluent. Consumer 1 doesn't know that partition was revoked and keeps on processing messages, in the meantime consumer I am using Kafka . interval. kafka zookeeper. 38. Im using a 2 node Kafka Connect in distributed mode. The Kafka rebalance is defined as, it is a process to depict every partition to the accurate customer, as a customer group is the set of customers which can overwhelm the messages It works OK, except I find the time spent before the rebalancing too long (like minutes). Only sensible reason to that you must have a long process. So this message will Kafka monitoring tools provide critical insights into cluster performance. When the commit is triggered, it is possible that the offset partition is associated with another consumer. Incremental Rebalance takes two rounds of rebalancing to complete, so results in longer overall latency. We use a StatefulSet to deploy a Scala Kafka Streams application on Kubernetes. Daria Daria. When a consumer remains idle for too long, Kafka may consider it as a failed consumer and remove it from the group. Few millions of records are consumed/produced every hour. , so when your consumer requests Consumer Group, Consumer and Partition Rebalance Kafka Consumer can consume/Subscribe to multiple topics and start receiving the messages. – During a rebalance, Kafka may need to pause data consumption temporarily. for all the topics/partitions, I see broker 1 as Leader. 30 minutes or sometimes even more for rebalancing. out I want to know what would happen if the consumer group rebalance takes long time like longer than the session timeout? For example I have two consumers A and B using the same group id. So my question is exactly how much time consumer thread takes between two consecutive polls? For example: Consumer Thread 1. For example MirrorMaker processes take a long time to rolling bounce the entire cluster, because one process restart will trigger one rebalance. This triggers a rebalance and the partitions get redistributed, assigning TP1 and TP2 to consumer B. Kafka Poll Takes Very Long Time - Stack Overflow However, poll() takes a very long time i. ms, which typically implies that the poll loop is spending too much time message processing. Users could implement these two functions differently (by default, onPartitionsLost(Collection) will be calling onPartitionsRevoked(Collection) directly); for example, in the onPartitionsLost(Collection) we should not need to store the offsets since we know these partitions are no longer owned by the consumer at that time. version>. 0 and Spring Kafka 2. 8. I don't think there are any best practices for deleting a topic in Kafka. Though you might be able to achieve a compromise by playing around with certain configuration for rebalance or timeout, it is likely to remain brittle design. 0 it did not occur for a few weeks. This can lead to a domino effect, where multiple JoinGroup requests cause the rebalance to occur multiple times, thus causing the rebalance time to take significantly longer than usual. There is a race condition where: 1. public void consumeRecords(List<ConsumerRecord<String, Organization>> consumerRecords) { long startTime = System. This did reduce the number of Figure 2: Consumer A takes too long processing the event and leaves the group. If a Kafka Streams instance starts, it looks for its state store data (in directory defined by state. This means that the time between subsequent calls to poll() was longer than the configured max. , your process() Kafka Streams timeout Users could implement these two functions differently (by default, onPartitionsLost(Collection) will be calling onPartitionsRevoked(Collection) directly); for example, in the onPartitionsLost(Collection) we should not need to store the offsets since we know these partitions are no longer owned by the consumer at that time. ms. It is marked dead and is no longer part of a consumer group. How to optimise Kafka Streams rebalances That's too old, already out of support Spring for Apache Kafka. The logs from kafka do not seem relevant but I could be wrong. These are special standby tasks that are placed on nodes that do not yet have a complete local copy of the Apache Kafka is a highly scalable event streaming platform known for its performance and fault tolerance. Kafka Rebalancing. Why? Steve Tian 2018-08-16 14:36:24 UTC. The inflight requests corresponds to the producer and not to the consumer. Everybody is advised to upgrade at least to the latest 1. Sticky Assignment: Introduced in later versions of Kafka, this strategy aims to minimize partition movement between consumers when a rebalance occurs, thus reducing potential downtime. records). Whenever i try to spawn up a consumer for my consumer group, Kafka takes a lot of time to rebalance and gets stuck on this log. ms is set to 90 minutes. Rebalance Storm. Consumer A is polling from two partitions when a second consumer. enable=true is defined in server. It does not start printing for a long time. I have an application where there are jobs which takes a lot of time to process (30-60 minutes) and currently max. EDIT. Monitoring tools help identify irregularities that may affect Kafka rebalancing. This timeout should then be configured to be sufficiently long to allow time for the consumer to restart and be reassigned its partitions without the need for a rebalance. If it doesn't find it, it will have to read it from state store topics in Kafka. ms to allow a restarting consumer time to rejoin and avoid triggering a rebalance comes with the risk that a genuinely failed consumer that does not If the O&M task takes a long time, you can use the kafka-reassign-partitions. The producer from the test sends a message to the topic "topicFunc1", the consumer from my system receives a message, some actions are performed and the producer of the system sends a message to the topic "2_1". If you’re Seems like standard Kafka (and Java kafka-client) functionality doesn't have this feature. threads = 5 [2020-01-30 11:54:18,779] WARN Property bootstrap. Sometimes, we may want to delay the processing of messages from Kafka. Don’t wait until something breaks—rebalance before you start seeing Kafka performance issues. ms, which typically implies that the poll loop is spending too much What is the purpose of a consumer rebalance? How long should a rebalance take? Watch for errors! Why this document? This document explains how Kafka consumer The consumer takes a very long time to start printing. So Kafka waits until rebalance timeout or end of the process for each consumer. dir). 02: 1. 0. version</spring-cloud. I want to do an experiment forcing Kafka to rebalance and to see how the service behaves. This can trigger consumer This is probably due to the default value of the parameter metadata. I think so during rebalancing and process time an instance does not achieve to commit some messages and the other instance processes it again. In our kafka broker setup, GC takes 20 ms on an average, but it randomly increases to 1-2 secs somtimes. 0, the internal Rebalance Protocol, which is especially used by Kafka Connect and consumers, has undergone several major changes. Since processing takes longer than max. Test scenario In test I create two topics: "topicFunc1", "2_1". request. At that point; all the consumers should be revoked. With the change stated, we only need constant number of rebalance (e. If rebalance happens at this time, the new consumer client assigned to this partition will start processing the messages again. Kafka has implemented "Incremental Cooperative Rebalancing" from version 2. 5. I'm using the high level consumer and what I'm noticing is that zookeeper and kafka sessions timeout because it is taking too long before we do anything on consumer queue so kafka ends up rebalancing every time the thread goes back to read more from consumer queue and it starts to take a long time before a consumer reads a new message after a Learn how to scale Kafka clusters and rebalance data with Self-Balancing Clusters and Tiered Storage to accommodate increases and decreases to data-in-motion requirements. This happens under no load - no messages are sent to the cluster, no messages are consumed. The rebalance protocol you wish you had. Consumer joins or leaves. Assuming we are talking about Kafka 0. A delayed followup rebalance scheduled for probing. kafka-reassign-partitions has 2 flaws though, it is not aware of partitions size, and neither can provide a plan to reduce the number of partitions to migrate from brokers to brokers. Spring Java Kafka Consumer Application with 6 replicas so that each of them deals with one of the partitions. So now there is no need for all consumers to stop the processing ("stop the world event") to rebalance work in group fe. I may be wrong but looks like Producer(or Kafka itself) repeats the same message when Consumer is working for a long time. So sometimes after doing that it's observed that it takes a long time for data to start moving from source to destination for the new topics. 6. This can happen, if rebalance due to state migration takes long and another rebalance happens: First instance is running; Second instance starts, triggering a rebalance Second instance recreates state; Another rebalance happens (not sure how this could be triggered in your case) If some worker takes a task from the topic and commits offset only on finish then other workers may also takes this task and process it. records — default value This means the time between subsequent calls to poll() was longer than the configured max. currentTimeMillis(); System. commitSycn . but all the subsequent calls takes hardly 3 to 4 miliseconds. ms, 1. This is most likely to happen when processing involves communication with an external system. when new consumer appears in group or some Since Apache Kafka 2. and 2. 1 Kafka Stream reprocessing old messages on rebalancing Kafka rebalance the data in a topic due to slow(er) consumer. records to ensure you can process the records in time. Therefore configuring a longer session. 1 Kafka Consumer Rebalancing : In-Flight Message Processing is Aborted We envision enabling it by default in a future major release of Kafka. A log partition that loads quickly (15ms) can take a long time (9549 ms) for the same broker a day later. Problem: Streams is special stateful. Does Kafka waits c2 to process message or revoke it immediately too? This is my question. Similar is the case when per message response time is slower than expected and the consumer can take time beyond the Kafka timeout settings. An example is a customer order processing system designed to process orders after a delay of X seconds, accommodating cancellations within this timeframe. If writing to the Messages channel takes longer // than this, that partition will stop fetching more messages until it // can proceed again. Frequent rebalances are usually caused because it is taking too long for the consumer to process batches. Furthermore, at large scale, this side-effect might lead to long startup times, following a complete rebalance of connectors and tasks in the Connect cluster. You can address this either by increasing the session timeout or by reducing the maximum size of batches returned in poll() with max. 1. The frequency of this is fairly random. Kafka Consumer are typically part of consumer group. sfqx pvcwj vtuvnspir purt zvh rbsix hawhe kbaxj zuvq bxrztpy