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From Dmitry Golubets <dgolub...@gmail.com>
Subject Re: Performance tuning
Date Fri, 17 Feb 2017 20:17:16 GMT
Hi Daniel,

I've implemented a macro that generates message pack serializers in our
codebase.
Resulting code is basically a series of writes\reads like in hand-written
structured serialization.

E.g. given
case class Data1(str: String, subdata: Data2)
case class Data2(num: Int)

serialization code for Data1 will be like:
packer.packString(str)
packer.packInt(num)

The data structures in our project are quite big (2-4kb in json) and
contain nested classes with many fields.
So custom serialization helps us to avoid reflection and reduces data size
to send over the network.

However, it worth mentioning, I see that on small case classes Flink
default serialization works faster.


Best regards,
Dmitry

On Fri, Feb 17, 2017 at 6:01 PM, Daniel Santos <dsantos@cryptolab.net>
wrote:

> Hello Dimitry,
>
> Could you please elaborate on your tuning on -> environment.addDefaultKryoSerializer(..)
> .
>
> I'm interested on knowing what have you done there for a boost of about
> 50% .
>
> Some small or simple example would be very nice.
>
> Thank you very much in advance.
>
> Kind Regards,
>
> Daniel Santos
>
> On 02/17/2017 12:43 PM, Dmitry Golubets wrote:
>
> Hi,
>
> My streaming job cannot benefit much from parallelization unfortunately.
> So I'm looking for things I can tune in Flink, to make it process
> sequential stream faster.
>
> So far in our current engine based on Akka Streams (non distributed ofc)
> we have 20k msg/sec.
> Ported to Flink I'm getting 14k so far.
>
> My observations are following:
>
>    - if I chain operations together they execute all in sequence, so I
>    basically sum up the time required to process one data item across all my
>    stream operators, not good
>    - if I split chains, they execute asynchronously to each other, but
>    there is serialization and network overhead
>
> Second approach gives me better results, considering that I have a server
> with more than enough memory and cores to do all side work for
> serialization. But I want to reduce this serialization\data transfer
> overhead to a minimum.
>
> So what I have now:
>
> environment.getConfig.enableObjectReuse() // cos it's Scala we don't need
> unnecessary serialization
> environment.getConfig.disableAutoTypeRegistration() // it works faster
> with it, I'm not sure why
> environment.addDefaultKryoSerializer(..) // custom Message Pack
> serialization for all message types, gives about 50% boost
>
> But that's it, I don't know what else to do.
> I didn't find any interesting network\buffer settings in docs.
>
> Best regards,
> Dmitry
>
>
>

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