Hi Arnaud,

I'm happy that you were able to resolve the issue. If you are still interested in the first approach, you could try some things, for example using only one slot per task manager (the slots share the heap of the TM).


On Fri, Nov 13, 2015 at 9:18 AM, LINZ, Arnaud <ALINZ@bouyguestelecom.fr> wrote:



I’ve worked around my problem by not using the HiveServer2 JDBC driver to read the ref table. Apparently, despite all the good options passed to the Statement object, it poorly handles RAM, since converting the table into textformat and directly reading the hdfs works without any problem and with a lot of free mem…





De : LINZ, Arnaud
Envoyé : jeudi
12 novembre 2015 17:48
À : 'user@flink.apache.org' <user@flink.apache.org>
Objet : Join Stream with big ref table




I have to enrich a stream with a big reference table (11,000,000 rows). I cannot use “join” because I cannot window the stream ; so in the “open()” function of each mapper I read the content of the table and put it in a HashMap (stored on the heap).


11M rows is quite big but it should take less than 100Mb in RAM, so it’s supposed to be easy. However, I systematically run into a Java Out Of Memory error, even with huge 64Gb containers (5 slots / container).


Path, ID

Data Port

Last Heartbeat

All Slots

Free Slots

CPU Cores

Physical Memory

Free Memory

Flink Managed Memory




2015-11-12, 17:46:14




126.0 GB

46.0 GB

31.5 GB


I don’t clearly understand why this happens and how to fix it. Any clue?




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