Hi Val, Thanks for reply.
We are trying to eliminate the reduce step in hadoop processing by sending each map results in a distribuited cache for minimize time of execution. Do you think it's a reasonable thing? When we send data with DataStream overwrite true through more parallel DataStreamer the time increases a lot. So we would like to split Ignite cluster for manage a set of HashMap, ( Node1 word from "a" to "d", Node2 word from "e" to "f" .... ). The HashMap are divided efficiently in map job but we aren't able to send this Map to specific node. Could you advise us on how to send data to node efficiently? For an HashMap of 10 millions entries sizenodebuffer 8192 16 sec ----> 1 Client send to 1 Node Server || Overwrite true sizenodebuffer 8192 42 sec ----> 3 Client send at the same time to 1 Node Server || Overwrite true sizenodebuffer 8192 12 sec ----> 1 Client send to 1 Node Server || Overwrite false sizenodebuffer 8192 23 sec ----> 3 Client send at the same time to 1 Node Server || Overwrite false Problem is thah we need to send GB of data, and this approach is too slow. Thanks Mimmo 2017-07-17 20:14 GMT+02:00 vkulichenko <[email protected]>: > I can't reproduce this behavior. Can you create a small project that I can > run on my side and investigate? > > -Val > > > > -- > View this message in context: http://apache-ignite-users. > 70518.x6.nabble.com/Ignite-Information-tp14330p15025.html > Sent from the Apache Ignite Users mailing list archive at Nabble.com. >
