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}}}-----(@: >
