Kafka producer resetting the last seen epoch of partition, resulting in timeout - kubernetes

Recently my kafka producer running as a cronjob on a kubernetes cluster has started doing the following when pushing new messages to the queue:
{"#version":1,"source_host":"<job pod name>","message":"[Producer clientId=producer-1] Resetting the last seen epoch of partition <topic name> to 4 since the associated topicId changed from null to JkTOJi-OSzavDEomRvAIOQ","thread_name":"kafka-producer-network-thread | producer-1","#timestamp":"2022-02-11T08:45:40.212+0000","level":"INFO","logger_name":"org.apache.kafka.clients.Metadata"}
This results in the producer running into a timeout:
"exception":{"exception_class":"java.util.concurrent.ExecutionException","exception_message":"org.apache.kafka.common.errors.TimeoutException: Expiring 1 record(s) for <topic name>:120000 ms has passed since batch creation", stacktrace....}
The logs of the kafka consumer pod and kafka cluster pods don't show any out-of-the-ordinary changes.
Has anyone seen this behavior before and if yes, how do I prevent it?

Reason:
the Java API mode generator cannot connect with Kafka
Solution:
On each server Add a sentence to the properties file
host.name = server IP;

Related

KSQL | Consumer lag | confluent cloud |

I am using kafka confluent cloud as a message queue in the eco-system. There are 2 topics, A and B.
Messages in B arrives a little later after messages of A is being published. ( in a delay of 30 secs )
I am joining these 2 topics using ksql, ksql server is deployed in in-premises and is connected to confluent cloud. In the KSQL i am joining these 2 topics as streams based on the common identifier, say requestId and create a new stream C. C is the joined stream.
At a times, C steam shows it has generated a lag it has not processed messages of A & B.
This lag is visible in the confluent cloud UI. When i login to ksql server i could see following error and after restart of ksql server everything works fine. This happens intermittently in 2 - 3 days.
Here is my configuration in the ksql server which is deployed in in-premises.
# A comma separated list of the Confluent Cloud broker endpoints
bootstrap.servers=${bootstrap_servers}
ksql.internal.topic.replicas=3
ksql.streams.replication.factor=3
ksql.logging.processing.topic.replication.factor=3
listeners=http://0.0.0.0:8088
security.protocol=SASL_SSL
sasl.mechanism=PLAIN
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username="${bootstrap_auth_key}" password="${bootstrap_secret_key}";
# Schema Registry specific settings
ksql.schema.registry.basic.auth.credentials.source=USER_INFO
ksql.schema.registry.basic.auth.user.info=${schema_registry_auth_key}:${schema_registry_secret_key}
ksql.schema.registry.url=${schema_registry_url}
#Additinoal settings
ksql.streams.producer.delivery.timeout.ms=2147483647
ksql.streams.producer.max.block.ms=9223372036854775807
ksql.query.pull.enable.standby.reads=false
#ksql.streams.num.standby.replicas=3 // TODO if we need HA 1+1
#num.standby.replicas=3
# Automatically create the processing log topic if it does not already exist:
ksql.logging.processing.topic.auto.create=true
# Automatically create a stream within KSQL for the processing log:
ksql.logging.processing.stream.auto.create=true
compression.type=snappy
ksql.streams.state.dir=${base_storage_directory}/kafka-streams
Error message in the ksql server logs.
[2020-11-25 14:08:49,785] INFO stream-thread [_confluent-ksql-default_query_CSAS_WINYES01QUERY_0-04b1e77c-e2ba-4511-b7fd-1882f63796e5-StreamThread-2] State transition from RUNNING to PARTITIONS_ASSIGNED (org.apache.kafka.streams.processor.internals.StreamThread:220)
[2020-11-25 14:08:49,790] ERROR [Consumer clientId=_confluent-ksql-default_query_CSAS_WINYES01QUERY_0-04b1e77c-e2ba-4511-b7fd-1882f63796e5-StreamThread-3-consumer, groupId=_confluent-ksql-default_query_CSAS_WINYES01QUERY_0] Offset commit failed on partition yes01-0 at offset 32606388: The coordinator is not aware of this member. (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:1185)
[2020-11-25 14:08:49,790] ERROR [Consumer clientId=_confluent-ksql-default_query_CSAS_WINYES01QUERY_0-04b1e77c-e2ba-4511-b7fd-1882f63796e5-StreamThread-3-consumer, groupId=_confluent-ksql-default_query_CSAS_WINYES01QUERY_0] Offset commit failed on partition yes01-0 at offset 32606388: The coordinator is not aware of this member. (org.apache.kafka.clients.consumer.internals.ConsumerCoordinator:1185)
[2020-11-25 14:08:49,790] WARN stream-thread [_confluent-ksql-default_query_CSAS_WINYES01QUERY_0-04b1e77c-e2ba-4511-b7fd-1882f63796e5-StreamThread-3] Detected that the thread is being fenced. This implies that this thread missed a rebalance and dropped out of the consumer group. Will close out all assigned tasks and rejoin the consumer group. (org.apache.kafka.streams.processor.internals.StreamThread:572)
org.apache.kafka.streams.errors.TaskMigratedException: Consumer committing offsets failed, indicating the corresponding thread is no longer part of the group; it means all tasks belonging to this thread should be migrated.
at org.apache.kafka.streams.processor.internals.TaskManager.commitOffsetsOrTransaction(TaskManager.java:1009)
at org.apache.kafka.streams.processor.internals.TaskManager.commit(TaskManager.java:962)
at org.apache.kafka.streams.processor.internals.StreamThread.maybeCommit(StreamThread.java:851)
at org.apache.kafka.streams.processor.internals.StreamThread.runOnce(StreamThread.java:714)
at org.apache.kafka.streams.processor.internals.StreamThread.runLoop(StreamThread.java:551)
at org.apache.kafka.streams.processor.internals.StreamThread.run(StreamThread.java:510)
Caused by: org.apache.kafka.clients.consumer.CommitFailedException: Commit cannot be completed since the group has already rebalanced and assigned the partitions to another member. This means that the time between subsequent calls to poll() was longer than the configured max.poll.interval.ms, which typically implies that the poll loop is spending too much time message processing. You can address this either by increasing max.poll.interval.ms or by reducing the maximum size of batches returned in poll() with max.poll.records.
at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator$OffsetCommitResponseHandler.handle(ConsumerCoordinator.java:1251)
at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator$OffsetCommitResponseHandler.handle(ConsumerCoordinator.java:1158)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:1132)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator$CoordinatorResponseHandler.onSuccess(AbstractCoordinator.java:1107)
at org.apache.kafka.clients.consumer.internals.RequestFuture$1.onSuccess(RequestFuture.java:206)
at org.apache.kafka.clients.consumer.internals.RequestFuture.fireSuccess(RequestFuture.java:169)
at org.apache.kafka.clients.consumer.internals.RequestFuture.complete(RequestFuture.java:129)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient$RequestFutureCompletionHandler.fireCompletion(ConsumerNetworkClient.java:602)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.firePendingCompletedRequests(ConsumerNetworkClient.java:412)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:297)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:236)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:215)
Edit :
During this exception. i have verified the ksql server has enough RAM and CPU

Kafka Consumer left consumer group

I've faced some problem using Kafka. Any help is much appreciated!
I have zookeeper and kafka cluster 3 nodes each in docker swarm. Kafka broker configuration you can see below.
KAFKA_DEFAULT_REPLICATION_FACTOR: 3
KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 3
KAFKA_MIN_INSYNC_REPLICAS: 2
KAFKA_NUM_PARTITIONS: 8
KAFKA_REPLICA_SOCKET_TIMEOUT_MS: 30000
KAFKA_REQUEST_TIMEOUT_MS: 30000
KAFKA_COMPRESSION_TYPE: "gzip"
KAFKA_JVM_PERFORMANCE_OPTS: "-XX:+UseG1GC -XX:MaxGCPauseMillis=20 -XX:InitiatingHeapOccupancyPercent=35 -XX:G1HeapRegionSize=16M -XX:MinMetaspaceFreeRatio=50 -XX:MaxMetaspaceFreeRatio=80"
KAFKA_HEAP_OPTS: "-Xmx768m -Xms768m -XX:MetaspaceSize=96m"
My case:
20x Producers producing messages to kafka topic constantly
1x Consumer reads and log messages
Kill kafka node (docker container stop) so now cluster has 2 nodes of Kafka broker (3rd will start and join cluster automatically)
And Consumer not consuming messages anymore because it left consumer group due to rebalancing
Does exist any mechanism to tell consumer to join group after rebalancing?
Logs:
INFO 1 --- [ | loggingGroup] o.a.k.c.c.internals.AbstractCoordinator : [Consumer clientId=kafka-consumer-0, groupId=loggingGroup] Attempt to heartbeat failed since group is rebalancing
WARN 1 --- [ | loggingGroup] o.a.k.c.c.internals.AbstractCoordinator : [Consumer clientId=kafka-consumer-0, groupId=loggingGroup] This member will leave the group because consumer poll timeout has expired. This means the time between subsequent calls to poll() was longer than the configured max.poll.interval.ms, which typically implies that the poll loop is spending too much time processing messages. You can address this either by increasing max.poll.interval.ms or by reducing the maximum size of batches returned in poll() with max.poll.records.
#Rostyslav Whenever we make a call by consumer to read a message, it does 2 major calls.
Poll
Commit
Poll is basically fetching records from kafka topic and commit tells kafka to save it as a read message , so that it's not read again. While polling few parameters play major role:
max_poll_records
max_poll_interval_ms
FYI: variable names are per python api.
Hence, whenever we try to read message from Consumer, it makes a poll call every max_poll_interval_ms and the same call is made only after the records fetched (as defined in max_poll_records) are processed. So, whenever, max_poll_records are not processed in max_poll_inetrval_ms, we get the error.
In order to overcome this issue, we need to alter one of the two variable. Altering max_poll_interval_ms ccan be hectic as sometime it may take longer time to process certain records, sometime lesser records. I always advice to play with max_poll_records as a fix to the issue. This works for me.

Kafka fails to publish message when any node in a 3 node cluster is down

I have kafka 0.10.2.1 deployed in a 3 node cluster with default configuration for the most part. The Producer config is as follows,
"bootstrap.servers", 3;
"retry.backoff.ms", "1000"
"reconnect.backoff.ms", "1000"
"max.request.size", "5242880"
"key.serializer", "org.apache.kafka.common.serialization.ByteArraySerializer"
"value.serializer", "org.apache.kafka.common.serialization.ByteArraySerializer"
What I am seeing is that when one node in the cluster is down I cannot publish messages to Kafka anymore. I get the following exception when I do so,
05-Apr-2018 22:29:33,362 PDT ERROR [vm18] [KafkaMessageBroker] (default task-43) |default| Failed to publish message for topic deviceConfigRequest: java.util.concurrent.ExecutionException: org.apache.kafka.common.errors.TimeoutException: Expiring 1 record(s) for deviceConfigRequest-1: 30967 ms has passed since batch creation plus linger time
at org.apache.kafka.clients.producer.internals.FutureRecordMetadata.valueOrError(FutureRecordMetadata.java:70) [kafka-clients-0.10.2.1.jar:]
at org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:65) [kafka-clients-0.10.2.1.jar:]
at org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:25) [kafka-clients-0.10.2.1.jar:]
at x.y.x.KafkaMessageBroker.publishMessage(KafkaMessageBroker.java:151) [classes:]
What am I missing?

Batch containing 1 record(s) expired due to timeout while requesting metadata from brokers for test-0

today a message prompt out when I try to send message to consumer console through producer console
[2016-11-02 15:12:58,168] ERROR Error when sending message to topic test with
key: null, value: 5 bytes with error:
(org.apache.kafka.clients.producer.internals.ErrorLoggingCallback)
org.apache.kafka.common.errors.TimeoutException: Batch containing 1 record(s)
expired due to timeout while requesting metadata from brokers for test-0
Why is this happened? Is this consider as Kafka problem or Zookeeper problem?
Seems that client failed to retrieve metadata for test-0 from the kafka brokers.
Either make sure you are able to connect to the kafka brokers or check if 'advertised.listeners' is set if you are running kafka on IaaS machines.
Well after I rebooted the whole server the problem is gone.

Kafka unrecoverable if broker dies

We have a kafka cluster with three brokers (node ids 0,1,2) and a zookeeper setup with three nodes.
We created a topic "test" on this cluster with 20 partitions and replication factor 2. We are using Java producer API to send messages to this topic. One of the kafka broker intermittently goes down after which it is unrecoverable. To simulate the case, we killed one of the broker manually. As per the kafka arch, it is supposed to self recover, but which is not happening. When I describe the topic on the console, I see the number of ISR's reduced to one for few of the partitions as one of the broker killed. Now, whenever we are trying to push messages via the producer API (either Java client or console producer), we are encountering SocketTimeoutException.. One quick look into the logs says, "Unable to fetch the metadata"
WARN [2015-07-01 22:55:07,590] [ReplicaFetcherThread-0-3][] kafka.server.ReplicaFetcherThread - [ReplicaFetcherThread-0-3],
Error in fetch Name: FetchRequest; Version: 0; CorrelationId: 23711; ClientId: ReplicaFetcherThread-0-3;
ReplicaId: 0; MaxWait: 500 ms; MinBytes: 1 bytes; RequestInfo: [zuluDelta,2] -> PartitionFetchInfo(11409,1048576),[zuluDelta,14] -> PartitionFetchInfo(11483,1048576).
Possible cause: java.nio.channels.ClosedChannelException
[2015-07-01 23:37:40,426] WARN Fetching topic metadata with correlation id 0 for topics [Set(test)] from broker [id:1,host:abc-0042.yy.xxx.com,port:9092] failed (kafka.client.ClientUtils$)
java.net.SocketTimeoutException
at sun.nio.ch.SocketAdaptor$SocketInputStream.read(SocketAdaptor.java:201)
at sun.nio.ch.ChannelInputStream.read(ChannelInputStream.java:86)
at java.nio.channels.Channels$ReadableByteChannelImpl.read(Channels.java:221)
at kafka.utils.Utils$.read(Utils.scala:380)
at kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
at kafka.network.Receive$class.readCompletely(Transmission.scala:56)
at kafka.network.BoundedByteBufferReceive.readCompletely(BoundedByteBufferReceive.scala:29)
at kafka.network.BlockingChannel.receive(BlockingChannel.scala:111)
at kafka.producer.SyncProducer.liftedTree1$1(SyncProducer.scala:75)
at kafka.producer.SyncProducer.kafka$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)
Any leads will be appreciated...
From your error Unable to fetch metadata it could mostly be because you could have set the bootstrap.servers in the producer to the broker that has died.
Ideally, you must have more than one broker in the bootstrap.servers list because if one of the broker fails (or is unreachable) then the other could give you the metadata.
FYI: Metadata is the information about a particular topic that tells how many number of partitions it has, their leader brokers, follower brokers etc.
So, when a key is produced to a partition, its corresponding leader broker will be the one to whom the messages will be sent to.
From your question, your ISR set has only one broker. You could try setting the bootstrap.server to this broker.