[
https://issues.apache.org/jira/browse/KAFKA-3686?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Luca Bruno updated KAFKA-3686:
------------------------------
Description:
*Setup*
I have a cluster of 3 kafka server, a topic with 12 partitions with replica 2,
and a zookeeper cluster of 3 nodes.
Producer config:
{code}
props.put("bootstrap.servers", "k1:9092,k2:9092,k3:9092");
props.put("acks", "1");
props.put("batch.size", 16384);
props.put("retries", 3);
props.put("buffer.memory", 33554432);
props.put("key.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
{code}
Producer code:
{code}
Producer<String, String> producer = new KafkaProducer<>(props);
for(int i = 0; i < 10; i++) {
Future<RecordMetadata> f = producer.send(new ProducerRecord<String,
String>("topic", null, Integer.toString(i)));
f.get();
}
{code}
*Problem*
Cut the network between the producer (p1) and one of the kafka servers (say k1).
The cluster is healthy, hence the kafka bootstrap tells the producer that there
are 3 kafka servers (as I understood it), and the leaders of the partitions of
the topic.
So the producer will send messages to all of the 3 leaders for each partition.
If the leader happens to be k1 for a message, the producer raises the following
exception:
{code}
Exception in thread "main" java.util.concurrent.ExecutionException:
org.apache.kafka.common.errors.TimeoutException: Batch Expired
at
org.apache.kafka.clients.producer.internals.FutureRecordMetadata.valueOrError(FutureRecordMetadata.java:56)
at
org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:43)
at
org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:25)
at Test.main(Test.java:25)
Caused by: org.apache.kafka.common.errors.TimeoutException: Batch Expired
{code}
In theory, the application should handle the failure. In practice, messages are
getting lost, even though there are other 2 leaders available for writing.
I tried with values of acks both 1 and -1.
*What I expected*
Given the client is automatically deciding the hashing / round robin schema for
the partition, I would say it's not very important which partition is the
message being sent to.
I expect the client to handle the failure, and send the message to a partition
of a different leader.
Neither kafka-clients nor rdkafka handle this failure. Given those are the main
client libraries being used for kafka as far as I know, I find it a serious
problem in terms of fault tolerance.
was:
*Setup*
I have a cluster of 3 kafka server, a topic with 12 partitions with replica 2,
and a zookeeper cluster of 3 nodes.
Producer config:
{code}
props.put("bootstrap.servers", "k1:9092,k2:9092,k3:9092");
props.put("acks", "1");
props.put("batch.size", 16384);
props.put("retries", 3);
props.put("buffer.memory", 33554432);
props.put("key.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
{code}
Producer code:
{code}
Producer<String, String> producer = new KafkaProducer<>(props);
for(int i = 0; i < 10; i++) {
Future<RecordMetadata> f = producer.send(new ProducerRecord<String,
String>("topic", null, Integer.toString(i)));
f.get();
}
{code}
*Problem*
Cut the network between the producer (p1) and one of the kafka servers (say k1).
The cluster is healthy, hence the kafka bootstrap tells the producer that there
are 3 kafka servers (as I understood it), and the leaders of the partitions of
the topic.
So the producer will send messages to all of the 3 leaders for each partition.
If the leader happens to be k1 for a message, the producer raises the following
exception:
{code}
Exception in thread "main" java.util.concurrent.ExecutionException:
org.apache.kafka.common.errors.TimeoutException: Batch Expired
at
org.apache.kafka.clients.producer.internals.FutureRecordMetadata.valueOrError(FutureRecordMetadata.java:56)
at
org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:43)
at
org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:25)
at Test.main(Test.java:25)
Caused by: org.apache.kafka.common.errors.TimeoutException: Batch Expired
{code}
In theory, the application should handle the failure. In practice, messages are
getting lost, even though there are other 2 leaders available for writing.
*What I expected*
Given the client is automatically deciding the hashing / round robin schema for
the partition, I would say it's not very important which partition is the
message being sent to.
I expect the client to handle the failure, and send the message to a partition
of a different leader.
Neither kafka-clients nor rdkafka handle this failure. Given those are the main
client libraries being used for kafka as far as I know, I find it a serious
problem in terms of fault tolerance.
> Kafka producer is not fault tolerant
> ------------------------------------
>
> Key: KAFKA-3686
> URL: https://issues.apache.org/jira/browse/KAFKA-3686
> Project: Kafka
> Issue Type: Bug
> Affects Versions: 0.9.0.1
> Reporter: Luca Bruno
>
> *Setup*
> I have a cluster of 3 kafka server, a topic with 12 partitions with replica
> 2, and a zookeeper cluster of 3 nodes.
> Producer config:
> {code}
> props.put("bootstrap.servers", "k1:9092,k2:9092,k3:9092");
> props.put("acks", "1");
> props.put("batch.size", 16384);
> props.put("retries", 3);
> props.put("buffer.memory", 33554432);
> props.put("key.serializer",
> "org.apache.kafka.common.serialization.StringSerializer");
> props.put("value.serializer",
> "org.apache.kafka.common.serialization.StringSerializer");
> {code}
> Producer code:
> {code}
> Producer<String, String> producer = new KafkaProducer<>(props);
> for(int i = 0; i < 10; i++) {
> Future<RecordMetadata> f = producer.send(new ProducerRecord<String,
> String>("topic", null, Integer.toString(i)));
> f.get();
> }
> {code}
> *Problem*
> Cut the network between the producer (p1) and one of the kafka servers (say
> k1).
> The cluster is healthy, hence the kafka bootstrap tells the producer that
> there are 3 kafka servers (as I understood it), and the leaders of the
> partitions of the topic.
> So the producer will send messages to all of the 3 leaders for each
> partition. If the leader happens to be k1 for a message, the producer raises
> the following exception:
> {code}
> Exception in thread "main" java.util.concurrent.ExecutionException:
> org.apache.kafka.common.errors.TimeoutException: Batch Expired
> at
> org.apache.kafka.clients.producer.internals.FutureRecordMetadata.valueOrError(FutureRecordMetadata.java:56)
> at
> org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:43)
> at
> org.apache.kafka.clients.producer.internals.FutureRecordMetadata.get(FutureRecordMetadata.java:25)
> at Test.main(Test.java:25)
> Caused by: org.apache.kafka.common.errors.TimeoutException: Batch Expired
> {code}
> In theory, the application should handle the failure. In practice, messages
> are getting lost, even though there are other 2 leaders available for writing.
> I tried with values of acks both 1 and -1.
> *What I expected*
> Given the client is automatically deciding the hashing / round robin schema
> for the partition, I would say it's not very important which partition is the
> message being sent to.
> I expect the client to handle the failure, and send the message to a
> partition of a different leader.
> Neither kafka-clients nor rdkafka handle this failure. Given those are the
> main client libraries being used for kafka as far as I know, I find it a
> serious problem in terms of fault tolerance.
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