Thanks Konstantin. And when serialization of events does become an issue 
because of size (say 100s MBs or GBs) how does it manifest itself? Is it mostly 
latency or something else?

Ajay

From: Konstantin Knauf <konstan...@ververica.com>
Date: Tuesday, February 12, 2019 at 3:41 AM
To: "Aggarwal, Ajay" <ajay.aggar...@netapp.com>
Cc: Chesnay Schepler <ches...@apache.org>, "user@flink.apache.org" 
<user@flink.apache.org>
Subject: Re: stream of large objects

Hi Ajay,

when repartitioning the stream the events need to transferred between 
Taskmanagers (processes/nodes). Just passing a reference there won't work.

If it is serialization you are worried about and you don't need access to the 
List of messages inside the job, you might as well store this list of String as 
a byte[]. This will make serialization cheaper. Generally, events of a few MBs 
should not be a problem by itself.

Cheers,

Konstantin

On Mon, Feb 11, 2019 at 6:39 PM Aggarwal, Ajay 
<ajay.aggar...@netapp.com<mailto:ajay.aggar...@netapp.com>> wrote:
I looked a little into broadcast state and while its interesting I don’t think 
it will help me. Since broadcast state is kept all in-memory, I am worried 
about memory requirement if I make all these LargeMessages part of broadcast 
state. Furthermore these LargeMessages need to be processed in a Keyed context, 
so sharing all of these across all downstream tasks does not seem efficient.


From: Chesnay Schepler <ches...@apache.org<mailto:ches...@apache.org>>
Date: Sunday, February 10, 2019 at 4:57 AM
To: "Aggarwal, Ajay" 
<ajay.aggar...@netapp.com<mailto:ajay.aggar...@netapp.com>>, 
"user@flink.apache.org<mailto:user@flink.apache.org>" 
<user@flink.apache.org<mailto:user@flink.apache.org>>
Subject: Re: stream of large objects

NetApp Security WARNING: This is an external email. Do not click links or open 
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The Broadcast 
State<https://ci.apache.org/projects/flink/flink-docs-master/dev/stream/state/broadcast_state.html#the-broadcast-state-pattern>
 may be interesting to you.

On 08.02.2019 15:57, Aggarwal, Ajay wrote:
Yes, another KeyBy will be used. The “small size” messages will be strings of 
length 500 to 1000.

Is there a concept of “global” state in flink? Is it possible to keep these 
lists in global state and only pass the list reference (by name?) in the 
LargeMessage?


From: Chesnay Schepler <ches...@apache.org><mailto:ches...@apache.org>
Date: Friday, February 8, 2019 at 8:45 AM
To: "Aggarwal, Ajay" 
<ajay.aggar...@netapp.com><mailto:ajay.aggar...@netapp.com>, 
"user@flink.apache.org"<mailto:user@flink.apache.org> 
<user@flink.apache.org><mailto:user@flink.apache.org>
Subject: Re: stream of large objects

Whether a LargeMessage is serialized depends on how the job is structured.
For example, if you were to only apply map/filter functions after the 
aggregation it is likely they wouldn't be serialized.
If you were to apply another keyBy they will be serialized again.

When you say "small size" messages, what are we talking about here?

On 07.02.2019 20:37, Aggarwal, Ajay wrote:
In my use case my source stream contain small size messages, but as part of 
flink processing I will be aggregating them into large messages and further 
processing will happen on these large messages. The structure of this large 
message will be something like this:

   Class LargeMessage {
        String key
       List <String> messages; // this is where the aggregation of smaller 
messages happen
   }

In some cases this list field of LargeMessage can get very large (1000’s of 
messages). Is it ok to create an intermediate stream of these LargeMessages? 
What should I be concerned about while designing the flink job? Specifically 
with parallelism in mind. As these LargeMessages flow from one flink subtask to 
another, do they get serialized/deserialized ?

Thanks.







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Konstantin Knauf | Solutions Architect

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