Applying SPE Techniques for Modelling a Grid-enabled Java Platform
GridGain – Java Grid Computing Made Simple
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GridGain – Java Grid Computing Made Simple
Nikita Ivanovwww.gridgain.org
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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
GridGain – Java Grid Computing Made Simple
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Product. Business. People. Slide 3
What is Grid Computing?
•Compute Grids•Parallelize logic execution
•Data Grids•Parallelize data storage
•Grid Computing = Data Grids + Compute Grids
•Data Partitioning + Affinity Map/Reduce
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Product. Business. People. Slide 4
Why Grid Computing?
•Ask Google, Yahoo, eBay, Amazon•Solves problems often unsolvable otherwise
•Google has almost 1,000,000 nodes in its grid•Uniformed programming paradigm that scales from garage to Google
•This code returns the same result on 1, 2 or 1,000 nodes – only faster, much faster…
@Gridify(taskName = "Optimizer")public double optimizePortfolio(Portfolio p) {
...}
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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
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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
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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…
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Key Concepts
• MapReduce• Zero Deployment• On Demand Scalability• Blend-In Integration• Transparent Grid Enabling with AOP• Data Grids Integration
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MapReduce
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1. Task execution request
2. Task splits into jobs3. Result of job execution4. Aggregation of job
results
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MapReduce Example
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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
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On Demand Scalability
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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:
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• Communication• Discovery• Tracing• Startup• Event storage
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Blend-In Integration, cont.
Application Servers• JBoss AS• BEA Weblogic• IBM Websphere• Glassfish• TomcatData Grids• JBoss Cache• Coherence• GigaSpacesAOP• JBoss AOP• Spring AOP• AspectJ
Messaging Middleware• Mule• JMS
• ActiveMQ• SunMQ
• Jgroups• Email• TCP, IP-MulticastOthers• Spring• Junit• JXInsight
“Out-of-the-box” integration with:
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Transparent Grid Enabling w/AOP
01 class BizLogic {02 @Gridify(…) 03 public static Result process(String param) {04 ...05 }06 }07 08 class Caller {09 public static void Main(String[] args) {10 GridFactory.start();11 12 try {13 BizLogic.process(args[0]);14 }15 finally {16 GridFactory.stop();17 }18 }19 }
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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
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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
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Data Grid Integration, cont.
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Demos
• Java 5/Eclipse 3.2/Windows XP• GridGain 2.0
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Q & A
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Thanks for your time!
Nikita Ivanov: [email protected]: www.gridgain.org
GridGain – Java Grid Computing Made Simple