This helps indeed. Thank you Claudio! Alexandros
On 4 February 2013 18:48, Claudio Martella <claudio.marte...@gmail.com>wrote: > Giraph runs on a Hadoop cluster as a map reduce job. Each worker is hence > a different task and it runs as a different jvm. This means that you can > have two workers running in the same machine. Hence it can happen that two > vertices running on two different workers executed in the same machine > might exchange messages over the network. The practical impact depends on > the host operating system. > On the other side, two vertices residing on the same worker but being > computed by different compute threads will behave as mentioned in the > previous email. If you would like to minimize the first behavior, you > should ensure a single worker is executed on each machine, and set > adequately the number of compute threads per worker. > > Hope this helps, > Claudio > > > On Monday, February 4, 2013, Daglis Alexandros wrote: > >> Hello Claudio, >> >> Thank you for your prompt answer! >> So, vertices that belong to the same worker thread do not require access >> to the network in order to exchange messages. >> However, what about *different worker threads* that reside on different >> cores *of the same node*? >> >> Cheers, >> Alexandros >> >> ------------------------------ >> *From:* Claudio Martella [claudio.marte...@gmail.com] >> *Sent:* Monday, February 04, 2013 6:19 PM >> *To:* user@giraph.apache.org >> *Subject:* Re: Inter- and intra-node message passing >> >> Hi Alexandros, >> >> if two vertices are on the same worker, the message does not pass >> through the network but it is put directly in the mailbox of the >> destination vertex. >> >> Cheers, >> Claudio >> >> >> On Mon, Feb 4, 2013 at 6:03 PM, Alexandros Daglis < >> alexandros.dag...@epfl.ch> wrote: >> >>> Hello everybody, >>> >>> I was wondering about the message-passing protocol: is there a >>> difference if two communicating threads are on the same node, as opposed to >>> being on different ones? Is communication achieved through memory whenever >>> the threads are local to the node, or does it always default to the >>> network? >>> >>> I tried answering that question by going through the code, but I haven't >>> seen any high-level difference in handling those two different cases. I >>> would appreciate if someone could give me a hint on that. >>> >>> Thank you in advance. >>> Alexandros >>> >> >> >> >> -- >> Claudio Martella >> claudio.marte...@gmail.com >> > > > -- > Claudio Martella > claudio.marte...@gmail.com >
