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GridGain Java Grid Computing Made Simple

Agenda. GridGainWhat is Grid Computing and why?What is GridGain and why?Why Java and Open Source?Key ConceptsDemosGrid Application in 15 MinutesRunning JUnits on Grid. GridGain

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GridGain Java Grid Computing Made Simple

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

    2. Agenda GridGain What is Grid Computing and why? What is GridGain and why? Why Java and Open Source? Key Concepts Demos Grid Application in 15 Minutes Running JUnits on Grid

    3. Product. Business. People. Slide 3

    4. Product. Business. People. Slide 4

    5. What is GridGain? Grid computing framework Full-stack grid computing Innovative Map/Reduce Integration with leading Data Grids Elegant simplicity Think Spring, Hibernate vs. EJB2 Java centric Built in Java and for Java Open source LGPL/Apache license

    6. 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

    7. 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

    8. Key Concepts MapReduce Zero Deployment On Demand Scalability Blend-In Integration Transparent Grid Enabling with AOP Data Grids Integration Slide 8

    9. MapReduce Slide 9

    10. MapReduce Example Slide 10

    11. 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->Compile->Run 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

    12. On Demand Scalability Slide 12

    13. Blend-In Integration Checkpoints Failover Collision Resolution Topology management Load balancing Deployment 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: Communication Discovery Tracing Startup Event storage

    14. Blend-In Integration, cont. 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 Out-of-the-box integration with: Slide 14

    15. Transparent Grid Enabling w/AOP 01classBizLogic{ 02@Gridify() 03publicstaticResultprocess(Stringparam){ 04... 05} 06} 07 08classCaller{ 09publicstaticvoidMain(String[]args){ 10GridFactory.start(); 11 12try{ 13BizLogic.process(args[0]); 14} 15finally{ 16GridFactory.stop(); 17} 18} 19} Slide 15

    16. 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

    17. Data Grids Integration, cont. GridGain full stack grid computing: GridGain+JBoss Cache Full OPEN SOURCE grid computing platform Native integration GridGain+Coherence Data Grid Native integration GridGain+GigaSpaces Data Grid One compute grid - many data grids Freedom of choice Slide 17

    18. Data Grid Integration, cont. Slide 18

    19. Demos Java 5/Eclipse 3.2/Windows XP GridGain 2.0

    20. Q & A Slide 20

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