PocketCluster Now Supports In-Memory Big Data Analytics Computation

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PocketCluster Now Supports In-Memory Big Data Analytics Computation - Published on 12/07/15

An updated version of PocketCluster, an OS X BigData application, has been released. The new update supports Apache Spark 1.5.2, an In-Memory Big Data analytics engine. PocketCluster is designed to provide a simple approach to deploy multi-nodes Big Data environment on OS X 10.11 El Capitan. With the latest update, users can deploy multi-node Spark/Hadoop combination clusters, and experience a speed boost from in-memory based MapReduce computation.

Seoul, Korea, Republic Of - A new version of PocketCluster, an OS X BigData application, has been released on Saturday Dec. 5, 2015. The version 0.1.3 now supports Apache Spark 1.5.2, an In-Memory Big Data Analytics engine. With the latest update, users can deploy a multi-node Spark/Hadoop combination cluster, and experience a speed boost from in-memory based MapReduce computation.

PocketCluster lets users build and operate a up-to 6 nodes Spark/Hadoop cluster with Raspberry PI 2 or a 3 nodes cluster with Vagrant in Graphical User Interface. With the simple approach to operate multi-nodes Spark/Hadoop Big Data cluster, PocketCluster helps users in the following use cases:

* Execute quick experiments on Spark/Hadoop combination to test a hypothesis
* Conduct a small scale data analysis to quickly identify hazardous element involved within
* Experience challenges from multi-nodes Spark/Hadoop environment

The new version also provide a console window feature for users to monitor service startup and shutdown progress. Further, the update come with improvements on some stability and compatibility issues for OS X 10.11 El Capitan.

Features:
* Apache Spark 1.5.2 with Scala 2.11.7 and Python 2.x Support
* Hadoop 2.4.0 with Java 8 Support
* Up-to 6 nodes Hadoop cluster with Raspberry PI 2
* 3 nodes Hadoop cluster with Vagrant
* Control HDFS, YARN, and Spark service from OSX top menu bar
* Cluster status indicator on OSX top menu bar
* Web based Hadoop cluster status monitor
* Hadoop Environment Shell
* Web-based Spark cluster status monitor
* Web-based Spark Job scheduler status monitor
* Spark Environment Shell

Device Requirements:
* iMac, Mac Pro, Mac mini, MacBook Air, Macbook, Macbook Pro, MacBook Pro with Retina
* Requires OSX 10.11 or later
* Raspberry PI 2

Pricing and Availability:
PocketCluster 0.1.3 is free with no in-app purchase, and available worldwide through the PocketCluster blog in combination with video tutorials.

PocketCluster Blog: https://pocketcluster.wordpress.com/2015/12/05/apache-spark-1-5-2-on-raspberry-pi-2-cluster/
YouTube Tutorial (Raspberry PI 2): https://www.youtube.com/watch?v=QVnSa9hp8fk
Direct Download Link (v0.1.3): https://github.com/stkim1/pocketcluster/raw/master/release/PocketCluster-0.1.3.dmg
App Icon: https://raw.githubusercontent.com/stkim1/pocketcluster/master/images/icon_256x256.png


Sung-Taek Kim is a Big-Data engineer enthusiastic about solving problems in unique ways. He is currently focused on building great developer experience. All Material and Software (C) 2015 Sung-Taek, Kim, All Rights Reserved. Apple, the Apple logo, iMac, Mac Pro, MacBook, MacBook Air, Macbook Pro, and MacBook Pro with Retina are registered trademarks of Apple Inc. in the U.S. and/or other countries. Other trademarks and registered trademarks may be the property of their respective owners.


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Link To Article: http://prmac.com/release-id-77889.htm
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