When does kafka change leader? - apache-kafka

I was running my services that work with kafka already for a year and no spontaneous changes of leader happens.
But for the last 2 weeks that started happens quite often.
Kafka log on that:
[2015-09-27 15:35:14,826] INFO [ReplicaFetcherManager on broker 2]
Removed fetcher for partitions [myTopic] (kafka.server.ReplicaFetcherManager)
[2015-09-27 15:35:14,830] INFO Truncating log myTopic-0 to offset 11520979. (kafka.log.Log)
[2015-09-27 15:35:14,845] WARN [Replica Manager on Broker 2]: Fetch request with correlation id 713276 from client ReplicaFetcherThread-0-2 on partition [myTopic,0] failed due to Leader not local for partition [myTopic,0] on broker 2 (kafka.server.ReplicaManager)
[2015-09-27 15:35:14,857] WARN [Replica Manager on Broker 2]: Fetch request with correlation id 256685 from client mirrormaker-1 on partition [myTopic,0] failed due to Leader not local for partition [myTopic,0] on broker 2 (kafka.server.ReplicaManager)
[2015-09-27 15:35:20,171] INFO [ReplicaFetcherManager on broker 2] Removed fetcher for partitions [myTopic,0] (kafka.server.ReplicaFetcherManager)
What can cause switching leader? If there is info in some kafka documentation - please - just point the link. I've failed to find.
System configuration
kafka version: kafka_2.10-0.8.2.1
os: Red Hat Enterprise Linux Server release 6.5 (Santiago)
server.properties (differs from default):
broker.id=001
socket.send.buffer.bytes=1048576
socket.receive.buffer.bytes=1048576
socket.request.max.bytes=104857600
log.flush.interval.messages=10000
log.flush.interval.ms=1000
log.retention.bytes=-1
controlled.shutdown.enable=true
auto.create.topics.enable=false

It appears like lead broker is down for that partition. It might be that data directroy(log.dirs) configured in server.properties is out of space and broker is not able to accommodate.
Also, what is replication factor of topic and cluster size of brokers?

I am assuming you have one topic and one partition with a replication factor of 2. Which is not a good configuration for optimal Kafka performance and consumers.
Your Logs are not clear enough for leader switch. Major issue in your topic may be having the only one leader due to the only partition. Now the single file in your logs is getting bigger in size day by day. Kafka internally does rebalancing at some level(details are not confirmed). That can be the reason for your leader switch. But i am not sure.
Also in your 2nd log line its says some of the logs are truncated. Can you please go though the logs in details and check is this happening only after truncation?
As you already mentioned you already checked your Kafka log directory files and their size. Please run the describe when you got this issue. The leader switch will reflect here as well. Or if you can setup some dashboard that will display the leader for past time. Then it will be easy for you to find the root cause.
bin/kafka-topics.sh --describe --zookeeper Zookeeperhost:Port --topic TopicName
Suggestion: i will suggest you to create a new topic with more partitions(read Kafka documentation to get a good idea about optimum number of partitions) and start writing to it. Or you can check, how to change partitions for current topic.
Last Thing: Is leader switch causing some issues in your Clients or you are worried only about warnings?

Related

Troubleshooting for kafka offline partitions

After unexpected shutdown of brokers, some of the topic partitions remain offline even if all the brokers are back up and running. Does anyone know the solution for this issue ?
2019-05-17T10:40:32,379 [myid:] - INFO [controller-event-thread:Logging$class#70] - [Controller 3]: Starting preferred replica leader election for partitions [topic,9]
2019-05-17T10:40:32,379 [myid:] - INFO [controller-event-thread:Logging$class#70] - [Partition state machine on Controller 3]: Invoking state change to OnlinePartition for partitions [topic,9]
2019-05-17T10:40:32,380 [myid:] - INFO [controller-event-thread:Logging$class#70] - [PreferredReplicaPartitionLeaderSelector]: Current leader -1 for partition [topic,9] is not the preferred replica. Triggering preferred replica leader election
2019-05-17T10:40:32,380 [myid:] - WARN [controller-event-thread:Logging$class#85] - [Controller 3]: Partition [topic,9] failed to complete preferred replica leader election. Leader is -1
My colleague and I just ran into a similar problem, however, we were trying to delete a topic that had offline partitions. The key to your problem is that your leader is -1.
The way we fixed this was by manually editing the znode in Zookeeper to point the leader to a broker that was online and doing a rolling restart of the cluster. Using the Zookeeper cli get the following znode:
/brokers/topics/<my-topic>/partitions/0/state.
In our case it returned:
{"controller_epoch":52,"leader":-1,"version":1,"leader_epoch":35,"isr":[5]}
Notice that the leader is -1. You might try updating the znode, setting the leader to a broker that is up and running.

Subset of stream's changelog and repartition partitions not available as broker is down - how stream should behave?

My setup consists of 3 kafka brokers (2.11-1.1.1), a single ZK and a java service that is using the Streams API.
The java service is consuming from topic A, performs a persistent stream operation (backed up by a changelog and a repartition streams topic) and writes to topic B. EOS semantics are enabled.
Given that the changelog and repartition topics have replication factor of 1, how should the streams java app behave in case one of my brokers is down (e.g. in my DEV env the disk is full only for one broker). Will the stream continue to consume even if 1/3 of the changelog and repartition partitions are not reachable?
EDIT: Also given that topics A, B and __consumer_offsets have RF=3.
In my java service logs I see:
2019-01-04 09:14:38,787 UTC WARN kafka-producer-network-thread | trsb-app-
nonprod.snapshot-14fa12b2-ac15-4ecc-8729-8f6c4a0034a7-StreamThread-2-0_4-
producer org.apache.kafka.clients.NetworkClient warn | [Producer
clientId=trsb-app-nonprod.snapshot-14fa12b2-ac15-4ecc-8729-8f6c4a0034a7-
StreamThread-2-0_4-producer, transactionalId=trsb-app-nonprod.snapshot-0_4]
Connection to node 1 could not be established. Broker may not be available.
2019-01-04 09:14:38,797 UTC WARN kafka-producer-network-thread | trsb-app-
nonprod.snapshot-14fa12b2-ac15-4ecc-8729-8f6c4a0034a7-StreamThread-2-1_10-
producer org.apache.kafka.clients.NetworkClient warn | [Producer
clientId=trsb-app-nonprod.snapshot-14fa12b2-ac15-4ecc-8729-8f6c4a0034a7-
StreamThread-2-1_10-producer, transactionalId=trsb-app-nonprod.snapshot-
1_10] Connection to node 1 could not be established. Broker may not be
available.
And nothing is consumed.
In both working broker logs I see:
[2019-01-04 13:56:56,449] WARN Resetting first dirty offset of trsb-app-
nonprod.snapshot-store.invoices-changelog-43 to log start offset 99 since
the checkpointed offset 95 is invalid. (kafka.log.LogCleanerManager$)
[2019-01-04 13:56:56,449] WARN Resetting first dirty offset of trsb-app-
nonprod.snapshot-store.invoices-changelog-40 to log start offset 103 since
the checkpointed offset 100 is invalid. (kafka.log.LogCleanerManager$)
Since you are using exactly once semantics, a minimum of 3 brokers are needed to continue processing, so your app would not continue to process if one of the brokers went down. Read here (see processing.guarantee section) for more info regarding this:
https://kafka.apache.org/10/documentation/streams/developer-guide/config-streams.html#id25
The stream continues to consume, but as the state store, depending on the message key, may no be pushable to its corresponding changelog partition, some keys may fail and these transactions will fail and be rollbacked. As a result, the first key on topic A that once consumed will cause the state store push to fail, will block its partition till the broker is up again. This is because the state store push is part of the EOS transaction.

Kafka mirror maker duplicates when DCs are isolated

We have 5 kafka 1.0.0 clusters:
4 of them are made of 3 nodes and are in different regions in the world
the last one is made of 5 nodes and is an aggregate only cluster.
We are using MirrorMaker (later referenced as MM) to read from the regional clusters and copy the data in the aggregate cluster in our HQ datacenter.
And not sure about where to run it we have currently 2 cases in our prod environment:
MM in the region: reading locally and pushing to aggregate cluster in remote data-center (DC), before committing offsets locally. I tend to call this the push mode (pushing the data)
MM in the DC of the aggregate cluster: reading remotely the data, writing it locally before committing the offsets on remote DC.
What happened is that we got the entire DC where we have our aggregate server totally isolated from a network point of view. And in both cases, we got duplicated records in our aggregate cluster.
Push mode = MM local to the regional cluster, pushing data to remote aggregate cluster
MM started to throw errors like this:
WARN [Producer clientId=producer-1] Got error produce response with correlation id 674364 on topic-partition <topic>-4, retrying (2147483646 attempts left). Error: NETWORK_EXCEPTION (org.apache.kafka.clients.producer.internals.Sender)
then:
WARN [Producer clientId=producer-1] Connection to node 1 could not be established. Broker may not be available. (org.apache.kafka.clients.NetworkClient)
which is ok so far because of idempotence.
But finally we got errors like:
ERROR Error when sending message to topic debug_sip_callback-delivery with key: null, value: 1640 bytes with error: (org.apache.kafka.clients.producer.internals.ErrorLoggingCallback)
org.apache.kafka.common.errors.TimeoutException: Expiring 1 record(s) for <topic>-4: 30032 ms has passed since batch creation plus linger time
ERROR Error when sending message to topic <topic> with key: null, value: 1242 bytes with error: (org.apache.kafka.clients.producer.internals.ErrorLoggingCallback)
java.lang.IllegalStateException: Producer is closed forcefully.
causing MM to stop and I think this is the problem causing duplicates (I need to dig the code, but could be that it lost information about idempotence and on restart it resumed from previously committed offsets).
Pull mode = MM local to the aggregate cluster, pulling data from remote regional cluster
MM instances (with logs at INFO level in this case) started seeing the broker as dead:
INFO [Consumer clientId=mirror-maker-region1-agg-0, groupId=mirror-maker-region1-agg] Marking the coordinator kafka1.region1.internal:9092 (id: 2147483646 rack: null) dead (org.apache.kafka.clients.consumer.internals.AbstractCoordinator)
At the same time on the broker side, we got:
INFO [GroupCoordinator 1]: Member mirror-maker-region1-agg-0-de2af312-befb-4af7-b7b0-908ca8ecb0ed in group mirror-maker-region1-agg has failed, removing it from the group (kafka.coordinator.group.GroupCoordinator)
...
INFO [GroupCoordinator 1]: Group mirror-maker-region1-agg with generation 42 is now empty (__consumer_offsets-2) (kafka.coordinator.group.GroupCoordinator)
Later on MM side, a lot of:
WARN [Consumer clientId=mirror-maker-region1-agg-0, groupId=mirror-maker-region1-agg] Connection to node 2 could not be established. Broker may not be available. (org.apache.kafka.clients.NetworkClient)
and finally when network came back:
ERROR [Consumer clientId=mirror-maker-region1-agg-0, groupId=mirror-maker-region1-agg] Offset commit failed on partition <topic>-dr-8 at offset 382424879: The coordinator is not aware of this member. (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator)
i.e., it could not commit in region1 the offsets written on agg because of the rebalancing. And it resumed after rebalance from previously successfully committed offset causing duplicates.
Configuration
Our MM instances are configured like this:
For our consumer:
bootstrap.servers=kafka1.region1.intenal:9092,kafka2.region1.internal:9092,kafka3.region1.internal:9092
group.id=mirror-maker-region-agg
auto.offset.reset=earliest
isolation.level=read_committed
For our producer:
bootstrap.servers=kafka1.agg.internal:9092,kafka2.agg.internal:9092,kafka3.agg.internal:9092,kafka4.agg.internal:9092,kafka5.agg.internal:9092
compression.type=none
request.timeout.ms=30000
max.block.ms=60000
linger.ms=15000
max.request.size=1048576
batch.size=32768
buffer.memory=134217728
retries=2147483647
max.in.flight.requests.per.connection=1
acks=all
enable.idempotence=true
Any idea how we can get the "only once" delivery on top of exactly once in case of 30 min isolated DCs?

Kafka broker constantly ISR shrinking and expanding?

We have a cluster of 4 nodes in production. We observed that one of the
nodes ran into a situation where it constantly shrunk and expanded ISR for
more than 1 hours and unable to recover until the broker was bounced.
[2017-02-21 14:52:16,518] INFO Partition [skynet-large-stage,5] on broker 0: Shrinking ISR for partition [skynet-large-stage,5] from 2,0 to 0 (kafka.cluster.Partition)
[2017-02-21 14:52:16,543] INFO Partition [skynet-large-stage,37] on broker 0: Shrinking ISR for partition [skynet-large-stage,37] from 1,0 to 0 (kafka.cluster.Partition)
[2017-02-21 14:52:16,544] INFO Partition [skynet-large-stage,13] on broker 0: Shrinking ISR for partition [skynet-large-stage,13] from 1,0 to 0 (kafka.cluster.Partition)
[2017-02-21 14:52:16,545] INFO Partition [__consumer_offsets,46] on broker 0: Shrinking ISR for partition [__consumer_offsets,46] from 3,2,0 to 3,0 (kafka.cluster.Partition)
.
.
I'd like to know what would cause this issue and why the broken broker was not kicked out of ISR.
Kafka version is 0.10.1.0
There was that bug in KAFKA-4477 that got fixed, but in general, I've seen this same problem when Kafka brokers time out when talking to a zookeeper node (default is 6000ms timeout), for some transient network blip, at which point they get kicked out of the cluster, partition leadership changes, clients have to rebalance, etc. For high volume clusters, it's a pain.
Simply increasing this timeout has helped me several times before:
zookeeper.session.timeout.ms
The default value according to the official docs is 6000ms. I found simply increasing it to 15000ms caused the cluster to be rock solid.
Documentation for 0.11.0 Kafka version: https://kafka.apache.org/0110/documentation.html

Why isn't kafka continuing to work on fail of one of the brokers?

I am under the impression that with two brokers with sync turned on my kafka setup should keep on working even on fail of one of the broker.
To test it I made a new topic named topicname. Its description is as follows:
Topic:topicname PartitionCount:1 ReplicationFactor:1 Configs:
Topic: topicname Partition: 0 Leader: 0 Replicas: 0 Isr: 0
Then I ran producer.sh and consumer.sh in the following way:
bin/kafka-console-producer.sh --broker-list localhost:9092,localhost:9095 sync --topic topicname
bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic topicname --from-beginning
Till both the brokers were working I saw that messages were being received properly by the consumer, but when I killed one of the instance of the brokers through kill command then the consumer stopped showing me any new messages. Instead it showed me the following error message:
WARN [ConsumerFetcherThread-console-consumer-57116_ip-<internalipvalue>-1438604886831-603de65b-0-0], Error in fetch Name: FetchRequest; Version: 0; CorrelationId: 865; ClientId: console-consumer-57116; ReplicaId: -1; MaxWait: 100 ms; MinBytes: 1 bytes; RequestInfo: [topicname,0] -> PartitionFetchInfo(9,1048576). Possible cause: java.nio.channels.ClosedChannelException (kafka.consumer.ConsumerFetcherThread)
[2015-08-03 12:29:36,341] WARN Fetching topic metadata with correlation id 1 for topics [Set(topicname)] from broker [id:0,host:<hostname>,port:9092] failed (kafka.client.ClientUtils$)
java.nio.channels.ClosedChannelException
at kafka.network.BlockingChannel.send(BlockingChannel.scala:100)
at kafka.producer.SyncProducer.liftedTree1$1(SyncProducer.scala:73)
at kafka.producer.SyncProducer.kafka$producer$SyncProducer$$doSend(SyncProducer.scala:72)
at kafka.producer.SyncProducer.send(SyncProducer.scala:113)
at kafka.client.ClientUtils$.fetchTopicMetadata(ClientUtils.scala:58)
at kafka.client.ClientUtils$.fetchTopicMetadata(ClientUtils.scala:93)
at kafka.consumer.ConsumerFetcherManager$LeaderFinderThread.doWork(ConsumerFetcherManager.scala:66)
at kafka.utils.ShutdownableThread.run(ShutdownableThread.scala:60)
I had this similar problem, setting the producer config "topic.metadata.refresh.interval.ms" to -1 (or whatever value is suitable for you) solved the issue for me.
So in my case , I had 3 broker (multi broker set up on my local machine) and created the topic with 3 partitions and replication factor 2.
Test set up:
Before the producer config:
Tried 3 brokers running , killed one of the brokers after producer started, the local Zookeeper updated the ISR and topic metadata info (removed down broker as leader) but the producer did not pick it up (may be due to default 10 mins refresh time).So messages end up failing. I get send exceptions.
After the producer config (-1 in my case):
Tried 3 brokers running , killed one of the brokers after producer started, the local Zookeeper updated the ISR info (removed down broker as leader), the producer refreshed the new ISR/topic metadata info and messages send did not fail.
-1 makes it refresh topic metadata on each failed attempt so may be you want to reduce the refresh time to something reasonable instead.
I think there are two things can make your consumer not work after a broker down for kafka HA cluster:
--replication-factor should bigger than 1 for your topic. so every topic partition can have at least one backup.
replication factor for internal topics for kafka configuration should also bigger than 1:
offsets.topic.replication.factor = 3
transaction.state.log.replication.factor = 3
transaction.state.log.min.isr = 2
This two modification make my producer and consumer still work after broker shutdown (5 broker and every broker goes down once) .
You can see in the topic description that you posted that your topic has only a single replica.
With a single replica there is no fault tolerance and if broker 0 (the broker that contains the replica) goes away, the topic will be unavailable.
Create a topic with more replicas (with --replication-factor 3) to have fault tolerance in case of crashes.
I had run into into the same problem even when using a topic with replication factor of 2.
Setting the following property on the producer worked for me.
"metadata.max.age.ms". (Kafka-0.8.2.1)
Else, my Producer was waiting for 1 minute by default to fetch the new leader and start contacting it
For a topic with replication factor N, Kafka tolerate up to N-1 server failures. E.g. having a replication factor 3 will allow you to handle upto 2 server failure.