Hello, 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…
Greetings, Arnaud 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 Hello, 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 akka.tcp://flink@172.21.125.28:43653/user/taskmanager 4B4D0A725451E933C39E891AAE80B53B 41982 2015-11-12, 17:46:14 5 5 32 126.0 GB 46.0 GB 31.5 GB I don’t clearly understand why this happens and how to fix it. Any clue? ________________________________ L'intégrité de ce message n'étant pas assurée sur internet, la société expéditrice ne peut être tenue responsable de son contenu ni de ses pièces jointes. Toute utilisation ou diffusion non autorisée est interdite. Si vous n'êtes pas destinataire de ce message, merci de le détruire et d'avertir l'expéditeur. The integrity of this message cannot be guaranteed on the Internet. The company that sent this message cannot therefore be held liable for its content nor attachments. Any unauthorized use or dissemination is prohibited. If you are not the intended recipient of this message, then please delete it and notify the sender.
