Also, the Spark examples can run out of the box on a single machine, as well as a cluster. See the "Master URLs" heading here: http://spark.apache.org/docs/latest/submitting-applications.html#master-urls
On Fri, May 30, 2014 at 9:24 AM, Surendranauth Hiraman < suren.hira...@velos.io> wrote: > With respect to virtual hosts, my team uses Vagrant/Virtualbox. We have 3 > CentOS VMs with 4 GB RAM each - 2 worker nodes and a master node. > > Everything works fine, though if you are using MapR, you have to make sure > they are all on the same subnet. > > -Suren > > > > On Fri, May 30, 2014 at 12:20 PM, Upender Nimbekar <upent...@gmail.com> > wrote: > >> Great News ! I've been awaiting this release to start doing some coding >> with Spark using Java 8. Can I run Spark 1.0 examples on a virtual host >> with 16 GB ram and fair descent amount of hard disk ? Or do I reaaly need >> to use a cluster of machines. >> Second, are there any good exmaples of using MLIB on Spark. Please shoot >> me in the right direction. >> >> Thanks >> Upender >> >> On Fri, May 30, 2014 at 6:12 AM, Patrick Wendell <pwend...@gmail.com> >> wrote: >> >>> I'm thrilled to announce the availability of Spark 1.0.0! Spark 1.0.0 >>> is a milestone release as the first in the 1.0 line of releases, >>> providing API stability for Spark's core interfaces. >>> >>> Spark 1.0.0 is Spark's largest release ever, with contributions from >>> 117 developers. I'd like to thank everyone involved in this release - >>> it was truly a community effort with fixes, features, and >>> optimizations contributed from dozens of organizations. >>> >>> This release expands Spark's standard libraries, introducing a new SQL >>> package (SparkSQL) which lets users integrate SQL queries into >>> existing Spark workflows. MLlib, Spark's machine learning library, is >>> expanded with sparse vector support and several new algorithms. The >>> GraphX and Streaming libraries also introduce new features and >>> optimizations. Spark's core engine adds support for secured YARN >>> clusters, a unified tool for submitting Spark applications, and >>> several performance and stability improvements. Finally, Spark adds >>> support for Java 8 lambda syntax and improves coverage of the Java and >>> Python API's. >>> >>> Those features only scratch the surface - check out the release notes >>> here: >>> http://spark.apache.org/releases/spark-release-1-0-0.html >>> >>> Note that since release artifacts were posted recently, certain >>> mirrors may not have working downloads for a few hours. >>> >>> - Patrick >>> >> >> > > > -- > > SUREN HIRAMAN, VP TECHNOLOGY > Velos > Accelerating Machine Learning > > 440 NINTH AVENUE, 11TH FLOOR > NEW YORK, NY 10001 > O: (917) 525-2466 ext. 105 > F: 646.349.4063 > E: suren.hiraman@v <suren.hira...@sociocast.com>elos.io > W: www.velos.io > >
