Hi Fabian,

thanks for the reply. I increased the TM heap to 20GB (on a 32GB machine) and 
indeed got a performance boost of more than a minute (about 20%).

Cheers,
Viktor

> Am 14.02.2015 um 14:23 schrieb Fabian Hueske-2 [via Apache Flink (Incubator) 
> User Mailing List archive.] <ml-node+s2336050n731...@n4.nabble.com>:
> 
> Hi,
> 
> Flink uses only the memory which is configured to the JobManager and 
> TaskManager JVMs.
> By default this is 256MB for the JM and 512MB for the TM (see [1] for 
> details).
> The TM memory is split into equally large chunks for each configured slot of 
> the TM.
> 
> You should definitely configure the TM JVM memory for your setup! See common 
> options in [1] for other important configuration parameters such as 
> numberOfTaskSlots.
> 
> In Yarn setups the TM memory is automatically sized with respect to the Yarn 
> container size, if I remember correctly.
> 
> [1] http://flink.apache.org/docs/0.8/config.html 
> <http://flink.apache.org/docs/0.8/config.html>
> 
> 2015-02-14 13:58 GMT+01:00 Viktor Rosenfeld <[hidden email] 
> <x-msg://43/user/SendEmail.jtp?type=node&node=731&i=0>>:
> Hi,
> 
> does the default configuration of Flink use all of the available memory? I
> mean the physical memory installed in the computer, not whatever amount of
> memory the JVM allocates by default.
> 
> Cheers,
> Viktor
> 
> 
> 
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