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From Neha Narkhede <neha.narkh...@gmail.com>
Subject Re: Most common kafka client comsumer implementations?
Date Wed, 13 Aug 2014 16:31:54 GMT
option1 would take a throughput hit as you are trying to commit one message
at a time. Option 2 is pretty widely used at LinkedIn and am pretty sure at
several other places as well. Option 3 is essentially what the high level
consumer does under the covers already. It prefetches data in batches from
the server to provide high throughput.


On Wed, Aug 13, 2014 at 2:20 AM, Anand Nalya <anand.nalya@gmail.com> wrote:

> Hi Jim,
>
> In one of the applications, we implemented option #1:
>
> messageList = getNext(1000)
> process(messageList)
> commit()
>
> In case of failure, this resulted in duplicate processing for at most 1000
> records per partition.
>
> Regards,
> Anand
>
>
> On 1 August 2014 20:35, Jim <jiminoc@gmail.com> wrote:
>
> > Thanks Guozhang,
> >
> > I was looking for actual real world workflows. I realize you can commit
> > after each message but if you’re using ZK for offsets for instance you’ll
> > put too much write load on the nodes and crush your throughput. So I was
> > interested in batching strategies people have used that balance high/full
> > throughput and fully committed events.
> >
> >
> > On Thu, Jul 31, 2014 at 8:16 AM, Guozhang Wang <wangguoz@gmail.com>
> wrote:
> >
> > > Hi Jim,
> > >
> > > Whether to use high level or simple consumer depends on your use case.
> If
> > > you need to manually manage partition assignments among your consumers,
> > or
> > > you need to commit your offsets elsewhere than ZK, or you do not want
> > auto
> > > rebalancing of consumers upon failures etc, you will use simple
> > consumers;
> > > otherwise you use high level consumer.
> > >
> > > From your description of pulling a batch of messages it seems you are
> > > currently using the simple consumer. Suppose you are using the high
> level
> > > consumer, to achieve at-lease-once basically you can do sth like:
> > >
> > > message = consumer.iter.next()
> > > process(message)
> > > consumer.commit()
> > >
> > > which is effectively the same as option 2 for using a simple consumer.
> Of
> > > course, doing so has a heavy overhead of one-commit-per-message, you
> can
> > > also do option 1, by the cost of duplicates, which is tolerable for
> > > at-least-once.
> > >
> > > Guozhang
> > >
> > >
> > > On Wed, Jul 30, 2014 at 8:25 PM, Jim <jiminoc@gmail.com> wrote:
> > >
> > > > Curious on a couple questions...
> > > >
> > > > Are most people(are you?) using the simple consumer vs the high level
> > > > consumer in production?
> > > >
> > > >
> > > > What is the common processing paradigm for maintaining a full
> pipeline
> > > for
> > > > kafka consumers for at-least-once messaging? E.g. you pull a batch of
> > > 1000
> > > > messages and:
> > > >
> > > > option 1.
> > > > you wait for the slowest worker to finish working on that message,
> when
> > > you
> > > > get back 1000 acks internally you commit your offset and pull another
> > > batch
> > > >
> > > > option 2.
> > > > you feed your workers n msgs at a time in sequence and move your
> offset
> > > up
> > > > as you work through your batch
> > > >
> > > > option 3.
> > > > you maintain a full stream of 1000 messages ideally and as you get
> acks
> > > > back from your workers you see if you can move your offset up in the
> > > stream
> > > > to pull n more messages to fill up your pipeline so you're not
> blocked
> > by
> > > > the slowest consumer (probability wise)
> > > >
> > > >
> > > > any good docs or articles on the subject would be great, thanks!
> > > >
> > >
> > >
> > >
> > > --
> > > -- Guozhang
> > >
> >
>

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