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From "Aggarwal, Ajay" <Ajay.Aggar...@netapp.com>
Subject Re: stream of large objects
Date Fri, 08 Feb 2019 14:57:08 GMT
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 <chesnay@apache.org>
Date: Friday, February 8, 2019 at 8:45 AM
To: "Aggarwal, Ajay" <Ajay.Aggarwal@netapp.com>, "user@flink.apache.org" <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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