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From Flavio Pompermaier <pomperma...@okkam.it>
Subject Re: OutOfMemoryException: unable to create native thread
Date Wed, 01 Jul 2015 08:13:03 GMT
+1 :)

On Wed, Jul 1, 2015 at 10:08 AM, chan fentes <chanfentes@gmail.com> wrote:

> Thank you all for your help and for pointing out different possibilities.
> It would be nice to have an input format that takes a directory and a
> regex pattern (for file names) to create one data source instead of 1500.
> This would have helped me to avoid the problem. Maybe this can be included
> in one of the future releases. ;)
>
> 2015-06-30 19:02 GMT+02:00 Stephan Ewen <sewen@apache.org>:
>
>> I agree with Aljoscha and Ufuk.
>>
>> As said, it will be hard for the system (currently) to handle 1500
>> sources, but handling a parallel source with 1500 files will be very
>> efficient.
>> This is possible, if all sources (files) deliver the same data type and
>> would be unioned.
>>
>> If that is true, you can
>>
>>  - Specify the input as a directory.
>>
>>  - If you cannot do that, because there is no common parent directory,
>> you can "union" the files into one data source with a simple trick, as
>> described here:
>> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/open-multiple-file-from-list-of-uri-tp1804p1807.html
>>
>>
>>
>> On Tue, Jun 30, 2015 at 5:36 PM, Aljoscha Krettek <aljoscha@apache.org>
>> wrote:
>>
>>> Hi Chan,
>>> Flink sources support giving a directory as an input path in a source.
>>> If you do this it will read each of the files in that directory. They way
>>> you do it leads to a very big plan, because the plan will be replicated
>>> 1500 times, this could lead to the OutOfMemoryException.
>>>
>>> Is there a specific reason why you create 1500 separate sources?
>>>
>>> Regards,
>>> Aljoscha
>>>
>>> On Tue, 30 Jun 2015 at 17:17 chan fentes <chanfentes@gmail.com> wrote:
>>>
>>>> Hello,
>>>>
>>>> how many data sources can I use in one Flink plan? Is there any limit?
>>>> I get an
>>>> java.lang.OutOfMemoryException: unable to create native thread
>>>> when having approx. 1500 files. What I basically do is the following:
>>>> DataSource ->Map -> Map -> GroupBy -> GroupReduce per file
>>>> and then
>>>> Union -> GroupBy -> Sum in a tree-like reduction.
>>>>
>>>> I have checked the workflow. It runs on a cluster without any problem,
>>>> if I only use few files. Does Flink use a thread per operator? It seems as
>>>> if I am limited in the amount of threads I can use. How can I avoid the
>>>> exception mentioned above?
>>>>
>>>> Best regards
>>>> Chan
>>>>
>>>
>>
>

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