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From Gwen Shapira <g...@confluent.io>
Subject Re: KIP-41: KafkaConsumer Max Records
Date Mon, 04 Jan 2016 19:47:51 GMT
1. Agree that TCP window style scaling will be cool. I'll try to think of a
good excuse to use it ;)

2. I'm very concerned about the challenges of getting the timeouts,
hearbeats and max messages right.

Another option could be to expose "heartbeat" API to consumers. If my app
is still processing data but is still alive, it could initiate a heartbeat
to signal its alive without having to handle additional messages.

I don't know if this improves more than it complicates though :(

On Mon, Jan 4, 2016 at 11:40 AM, Jason Gustafson <jason@confluent.io> wrote:

> Hey Gwen,
>
> I was thinking along the lines of TCP window scaling in order to
> dynamically find a good consumption rate. Basically you'd start off
> consuming say 100 records and you'd let it increase until the consumption
> took longer than half the session timeout (for example). You /might/ be
> able to achieve the same thing using pause/resume, but it would be a lot
> trickier since you have to do it at the granularity of partitions. But
> yeah, database write performance doesn't always scale in a predictable
> enough way to accommodate this, so I'm not sure how useful it would be in
> practice. It might also be more difficult to implement since it wouldn't be
> as clear when to initiate the next fetch. With a static setting, the
> consumer knows exactly how many records will be returned on the next call
> to poll() and can send fetches accordingly.
>
> On the other hand, I do feel a little wary of the need to tune the session
> timeout and max messages though since these settings might depend on the
> environment that the consumer is deployed in. It wouldn't be a big deal if
> the impact was relatively minor, but getting them wrong can cause a lot of
> rebalance churn which could keep the consumer from making any progress.
> It's not a particularly graceful failure.
>
> -Jason
>
> On Mon, Jan 4, 2016 at 10:49 AM, Gwen Shapira <gwen@confluent.io> wrote:
>
> > I can't speak to all use-cases, but for the database one, I think
> > pause-resume will be necessary in any case, and therefore dynamic batch
> > sizes are not needed.
> >
> > Databases are really unexpected regarding response times - load and
> locking
> > can affect this. I'm not sure there's a good way to know you are going
> into
> > rebalance hell before it is too late. So if I were writing code that
> > updates an RDBMS based on Kafka, I'd pick a reasonable batch size (say
> 5000
> > records), and basically pause, batch-insert all records, commit and
> resume.
> >
> > Does that make sense?
> >
> > On Mon, Jan 4, 2016 at 10:37 AM, Jason Gustafson <jason@confluent.io>
> > wrote:
> >
> > > Gwen and Ismael,
> > >
> > > I agree the configuration option is probably the way to go, but I was
> > > wondering whether there would be cases where it made sense to let the
> > > consumer dynamically set max messages to adjust for downstream
> slowness.
> > > For example, if the consumer is writing consumed records to another
> > > database, and that database is experiencing heavier than expected load,
> > > then the consumer could halve its current max messages in order to
> adapt
> > > without risking rebalance hell. It could then increase max messages as
> > the
> > > load on the database decreases. It's basically an easier way to handle
> > flow
> > > control than we provide with pause/resume.
> > >
> > > -Jason
> > >
> > > On Mon, Jan 4, 2016 at 9:46 AM, Gwen Shapira <gwen@confluent.io>
> wrote:
> > >
> > > > The wiki you pointed to is no longer maintained and fell out of sync
> > with
> > > > the code and protocol.
> > > >
> > > > You may want  to refer to:
> > > >
> > > >
> > >
> >
> https://cwiki.apache.org/confluence/display/KAFKA/A+Guide+To+The+Kafka+Protocol
> > > >
> > > > On Mon, Jan 4, 2016 at 4:38 AM, Jens Rantil <jens.rantil@tink.se>
> > wrote:
> > > >
> > > > > Hi guys,
> > > > >
> > > > > I realized I never thanked yall for your input - thanks!
> > > > > Jason: I apologize for assuming your stance on the issue! Feels
> like
> > we
> > > > all
> > > > > agreed on the solution. +1
> > > > >
> > > > > Follow-up: Jason made a point about defining prefetch and fairness
> > > > > behaviour in the KIP. I am now working on putting that down in
> > writing.
> > > > To
> > > > > do be able to do this I think I need to understand the current
> > prefetch
> > > > > behaviour in the new consumer API (0.9) a bit better. Some specific
> > > > > questions:
> > > > >
> > > > >    - How does a specific consumer balance incoming messages from
> > > multiple
> > > > >    partitions? Is the consumer simply issuing Multi-Fetch
> requests[1]
> > > for
> > > > > the
> > > > >    consumed assigned partitions of the relevant topics? Or is the
> > > > consumer
> > > > >    fetching from one partition at a time and balancing between them
> > > > >    internally? That is, is the responsibility of partition
> balancing
> > > (and
> > > > >    fairness) on the broker side or consumer side?
> > > > >    - Is the above documented somewhere?
> > > > >
> > > > > [1]
> > > > >
> > > > >
> > > >
> > >
> >
> https://cwiki.apache.org/confluence/display/KAFKA/Writing+a+Driver+for+Kafka
> > > > > ,
> > > > > see "Multi-Fetch".
> > > > >
> > > > > Thanks,
> > > > > Jens
> > > > >
> > > > > On Wed, Dec 23, 2015 at 2:44 AM, Ismael Juma <ismael@juma.me.uk>
> > > wrote:
> > > > >
> > > > > > On Wed, Dec 23, 2015 at 1:24 AM, Gwen Shapira <gwen@confluent.io
> >
> > > > wrote:
> > > > > >
> > > > > > > Given the background, it sounds like you'll generally want
each
> > > call
> > > > to
> > > > > > > poll() to return the same number of events (which is the
number
> > you
> > > > > > planned
> > > > > > > on having enough memory / time for). It also sounds like
tuning
> > the
> > > > > > number
> > > > > > > of events will be closely tied to tuning the session timeout.
> > That
> > > > is -
> > > > > > if
> > > > > > > I choose to lower the session timeout for some reason,
I will
> > have
> > > to
> > > > > > > modify the number of records returning too.
> > > > > > >
> > > > > > > If those assumptions are correct, I think a configuration
makes
> > > more
> > > > > > sense.
> > > > > > > 1. We are unlikely to want this parameter to be change
at the
> > > > lifetime
> > > > > of
> > > > > > > the consumer
> > > > > > > 2. The correct value is tied to another configuration
> parameter,
> > so
> > > > > they
> > > > > > > will be controlled together.
> > > > > > >
> > > > > >
> > > > > > I was thinking the same thing.
> > > > > >
> > > > > > Ismael
> > > > > >
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > > Jens Rantil
> > > > > Backend engineer
> > > > > Tink AB
> > > > >
> > > > > Email: jens.rantil@tink.se
> > > > > Phone: +46 708 84 18 32
> > > > > Web: www.tink.se
> > > > >
> > > > > Facebook <https://www.facebook.com/#!/tink.se> Linkedin
> > > > > <
> > > > >
> > > >
> > >
> >
> http://www.linkedin.com/company/2735919?trk=vsrp_companies_res_photo&trkInfo=VSRPsearchId%3A1057023381369207406670%2CVSRPtargetId%3A2735919%2CVSRPcmpt%3Aprimary
> > > > > >
> > > > >  Twitter <https://twitter.com/tink>
> > > > >
> > > >
> > >
> >
>

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