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GridGain Java Grid Computing Made Simple

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Like JBoss, Spring Source, Mule Source... GridGain Java Grid Computing Made Simple ... Mule. JMS. ActiveMQ. SunMQ. Jgroups. Email. TCP, IP-Multicast. Others ... – PowerPoint PPT presentation

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Title: GridGain Java Grid Computing Made Simple


1
GridGain Java Grid Computing Made Simple
  • Nikita Ivanov
  • www.gridgain.org

The Israeli Association of Grid Technologies (IGT)
2
Agenda
  • GridGain
  • What is GridGain?
  • Why GridGain?
  • Professional Open Source
  • Key Concepts
  • Demo
  • Grid Application in 15 Minutes

GridGain Java Grid Computing Made Simple
Slide 2
3
What is GridGain?
  • Grid computing framework
  • Full-stack grid computing
  • Innovative Map/Reduce
  • Integration with leading Data Grids
  • Ground-breaking simplicity
  • Think Spring, Hibernate vs. EJB2
  • Java centric
  • Built in Java and for Java
  • Open source
  • LGPL/Apache license

GridGain Java Grid Computing Made Simple
Slide 3
4
Why GridGain?
  • Existing projects are
  • Too complex to use
  • Globus, GridEngine anyone?
  • Too expensive to use
  • M for DataSynapse, Platform, UD
  • Not Java-based or Java friendly
  • Alien to Java 5 and JEE
  • Open source is NOT enterprise oriented

GridGain Java Grid Computing Made Simple
Slide 4
5
Professional Open Source
  • GridGain - Professional Open Source
  • Open source
  • FREE software
  • FREE upgrades
  • FREE community support
  • FREE source code
  • No gimmicks
  • Commercial enterprise-level support and services
  • Indemnification
  • Custom SLAs
  • Guaranteed response time
  • Like JBoss, Spring Source, Mule Source

GridGain Java Grid Computing Made Simple
Slide 5
6
Key Concepts
  • Map/Reduce
  • Zero Deployment
  • On Demand Scalability
  • Blend-In Integration
  • Transparent Grid Enabling with AOP
  • Data Grids Integration

GridGain Java Grid Computing Made Simple
7
Map/Reduce
  • Task execution request
  • Task splits into jobs
  • Result of job execution
  • Aggregation of job results

GridGain Java Grid Computing Made Simple
8
Zero Deployment
  • Peer-to-Peer On-Demand Class Loading technology
  • No Ant scripts to run
  • No JARs to copy or FTP
  • No nodes to restart
  • Develop in EXACTLY the same way as locally
  • Change-gtCompile-gtRun on the grid
  • Start many grid nodes in
  • Single JVM debug grid apps locally (!)
  • Single computer run grid on your workstation
  • Single biggest developers productivity boost

Slide 8
GridGain Java Grid Computing Made Simple
9
On Demand Scalability
GridGain Java Grid Computing Made Simple
10
Blend-In Integration
  • Service Provider Interface (SPI)-based
    architecture
  • Plug in and customize almost any aspect of grid
    computing framework
  • LEGO-like assembly of custom grid infrastructure
  • Grid computing framework aspect that are fully
    pluggable
  • Checkpoints
  • Failover
  • Collision Resolution
  • Topology management
  • Load balancing
  • Deployment
  • Communication
  • Discovery
  • Tracing
  • Startup
  • Event storage

Slide 10
GridGain Java Grid Computing Made Simple
11
Blend-In Integration, cont.
  • Out-of-the-box integration with
  • Application Servers
  • JBoss AS
  • BEA Weblogic
  • IBM Websphere
  • Glassfish
  • Tomcat
  • Data Grids
  • JBoss Cache
  • Coherence
  • GigaSpaces
  • AOP
  • JBoss AOP
  • Spring AOP
  • AspectJ
  • Messaging Middleware
  • Mule
  • JMS
  • ActiveMQ
  • SunMQ
  • Jgroups
  • Email
  • TCP, IP-Multicast
  • Others
  • Spring
  • Junit
  • JXInsight

GridGain Java Grid Computing Made Simple
12
Transparent Grid Enabling w/AOP
  • 01 class BizLogic 02   _at_Gridify()
    03   public static Result process(String param) 
    04     ...05   06 07 08 class Caller 09  
     public static void Main(String args) 10     G
    ridFactory.start()11 12     try 13       BizL
    ogic.process(args0)14     15     finally 1
    6       GridFactory.stop()17     18   19 

Execution of process() method will be performed
on the grid
GridGain Java Grid Computing Made Simple
13
Data Grids Integration
  • Data Compute Grids Full stack grid computing
  • Compute grids parallelize processing logic
  • Data grids parallelize data storage
  • Affinity Map/Reduce ability to co-locate
    processing logic and the data
  • Minimizes noise traffic
  • Optimal grid load and performance

GridGain Java Grid Computing Made Simple
Slide 13
14
Data Grids Integration, cont.
  • GridGain full stack grid computing
  • GridGainJBoss Cache
  • Full OPEN SOURCE grid computing platform
  • Native integration
  • GridGainCoherence Data Grid
  • Native integration
  • GridGainGigaSpaces Data Grid
  • One compute grid - many data grids
  • Freedom of choice

GridGain Java Grid Computing Made Simple
15
Data Grid Integration, cont.
GridGain Java Grid Computing Made Simple
16
Demo
  • 15 minutes for full split/aggregate example from
    scratch
  • Java 5/Eclipse 3.3/Windows XP
  • GridGain 1.6.1

GridGain Java Grid Computing Made Simple
Slide 16
17
Q A
  • Thanks for your time!
  • Nikita Ivanov nivanov_at_gridgain.com
  • GridGain www.gridgain.org

GridGain Java Grid Computing Made Simple
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