Regarding the partitions created:
> topic: unittest-test-msg partition: 0 leader: 0
replicas: 0 isr: 0
> topic: unittest-test-msg partition: 1 leader: 1
replicas: 1 isr: 1
> topic: unittest-test-msg partition: 2 leader: 0
replicas: 0 isr: 0
> topic: unittest-test-msg partition: 3 leader: 1
replicas: 1 isr: 1
Is this saying that partitions 1 and 3, both on the same broker, are both
the Leader partitions AND the Replica partitions? I do not understand the
significance of ISR, either. How should this be read?
Keeping in mind that these were auto-created, unsure of the implications, I
will be carefully reading the following, next:
https://cwiki.apache.org/KAFKA/kafka-replication.html.
thanks,
rob
> -----Original Message-----
> From: Rob Withers [mailto:reefedjib@gmail.com]
> Sent: Thursday, May 02, 2013 7:20 AM
> To: 'users@kafka.apache.org'
> Subject: RE: consuming only half the messages produced
>
> Yes, I mean we can only consume half the messages produced. I followed
the
> high-level consumer example here:
> https://cwiki.apache.org/confluence/display/KAFKA/Consumer+Group+Examp
> le.
>
> Let me give a more complete scenario:
>
> - We run 3 zookeepers
> - We run 2 brokers
> - We do not have a topic defined, but we have enabled topic auto-creation
> (with a replication factor of 2? must check this)
> - We connect the producer to both brokers (pocmsg5:9092,pocmsg6:9092)
> - We stuff the topic into the KeyedMessage key with no Partitioner. I was
not
> aware of the use of the key until last night.
> - We generate 10 messages
> - Topic auto-creation results in the following partitions:
> topic: unittest-test-msg partition: 0 leader: 0
replicas: 0 isr: 0
> topic: unittest-test-msg partition: 1 leader: 1
replicas: 1 isr: 1
> topic: unittest-test-msg partition: 2 leader: 0
replicas: 0 isr: 0
> topic: unittest-test-msg partition: 3 leader: 1
replicas: 1 isr: 1
> - We construct a single Kafka stream by calling createStreams with a
> zookeeper (pocmsg5:2181) and one thread
> public <K,V> Map<String, List<KafkaStream<K,V>>>
> createMessageStreams(
> Map<String, Integer> topicCountMap,
> Decoder<K> keyDecoder,
> Decoder<V> valueDecoder)
> - We consume only half the messages
> - It looks as if partitions 0 and 2 are on pocmsg5, while partitions 1 and
3 are
> on pocmsg6.
>
> Is it best to view the situation as 2 partitions, each a leader, with a
replica
> follower for each?
> which partitions are leaders and which are replicas?
> What happened with auto-creation and production and partitioning?
> Which partition(s) is the zookeeper pointing the high-level consumer to
read
> from?
>
> thanks,
> rob
>
> > -----Original Message-----
> > From: Jun Rao [mailto:junrao@gmail.com]
> > Sent: Wednesday, May 01, 2013 11:15 PM
> > To: users@kafka.apache.org
> > Subject: Re: consuming only half the messages produced
> >
> > Partition is different from replicas. A topic can have one or more
> > partitions and each partition can have one or more replicas. A
> > consumer consumes data at partition level. In other words, a consumer
> > gets the same data no matter how many replicas are there.
> >
> > When you say the consumer only gets half of the messages, do you mean
> > that it gets half of the messages that are produced?
> >
> > You may want to take a look at the consumer example in
> > http://kafka.apache.org/08/api.html
> >
> > Thanks,
> >
> > Jun
> >
> >
> > On Wed, May 1, 2013 at 7:14 PM, Rob Withers <reefedjib@gmail.com>
> wrote:
> >
> > > Running a consumer group (createStreams()), pointing to the
> > > zookeeper and with the topic and 1 consumer thread, results in only
> > > half the messages being consumed. The topic was auto-created, with
> > > a replication factor of 2, but the producer was configured to
> > > produce to
> > > 2 brokers and so 4 partitions resulted. Are half getting sent to
> > > one leader, in one broker, and the other half getting sent to
> > > another leader, in the other broker, but the consumer stream is only
> > > reading from one leader from the zk? Shouldn't there only be one
leader?
> > >
> > >
> > >
> > > thanks,
> > >
> > > rob
> > >
> > >
> > >
> > >
|