I did some performance check on socLiveJournal PageRank b/w my local machine (8 cores, 16 gb ) in local mode and my small cluster (4 nodes, 12 cores, 40 gb) and i found cluster mode is way faster than local mode. So I confused. no. of iterations ---> Local mode(in mins) --> cluster mode(in mins) 1 20 1 2 31.3 1.2 3 39.5 1.3 5 56.4 1.6 10 117.26 2.6 with the help of this , I think , might be installing spark cluster on the same machine and instead of giving local[no. of cores] , I'll set to spark://host:7070.
Please let me know If I wrong somewhere. On Tue, Apr 21, 2015 at 6:27 PM, Reynold Xin <r...@databricks.com> wrote: > Actually if you only have one machine, just use the Spark local mode. > > Just download the Spark tarball, untar it, set master to local[N], where N > = number of cores. You are good to go. There is no setup of job tracker or > Hadoop. > > > On Mon, Apr 20, 2015 at 3:21 PM, haihar nahak <harihar1...@gmail.com> > wrote: > >> Thank you :) >> >> On Mon, Apr 20, 2015 at 4:46 PM, Jörn Franke <jornfra...@gmail.com> >> wrote: >> >>> Hi, If you have just one physical machine then I would try out Docker >>> instead of a full VM (would be waste of memory and CPU). >>> >>> Best regards >>> Le 20 avr. 2015 00:11, "hnahak" <harihar1...@gmail.com> a écrit : >>> >>>> Hi All, >>>> >>>> I've big physical machine with 16 CPUs , 256 GB RAM, 20 TB Hard disk. I >>>> just >>>> need to know what should be the best solution to make a spark cluster? >>>> >>>> If I need to process TBs of data then >>>> 1. Only one machine, which contain driver, executor, job tracker and >>>> task >>>> tracker everything. >>>> 2. create 4 VMs and each VM should consist 4 CPUs , 64 GB RAM >>>> 3. create 8 VMs and each VM should consist 2 CPUs , 32 GB RAM each >>>> >>>> please give me your views/suggestions >>>> >>>> >>>> >>>> -- >>>> View this message in context: >>>> http://apache-spark-user-list.1001560.n3.nabble.com/how-to-make-a-spark-cluster-tp22563.html >>>> Sent from the Apache Spark User List mailing list archive at Nabble.com. >>>> >>>> --------------------------------------------------------------------- >>>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>>> For additional commands, e-mail: user-h...@spark.apache.org >>>> >>>> >> >> >> -- >> {{{H2N}}}-----(@: >> > > -- {{{H2N}}}-----(@: