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GridGain – Java Grid Computing
         Made Simple

               Dmitriy Setrakyan
                   www.gridgain.org
Agenda
• GridGain
  • What is Grid Computing and why
  • GridGain In a Glance
  • Key Concepts
• Demos
  • Grid Application in 15 Minutes




                GridGain – Java Grid Computing Made Simple   Slide 2
What is Grid Computing?
•Compute Grids
  •Parallelize execution
•Data Grids
  •Parallelize data storage
•Grid Computing = Compute Grids + Data
Grids
  •a.k.a. Data Partitioning + Affinity Map/Reduce
•Utility, on-demand, cloud computing…?

                 GridGain – Java Grid Computing Made Simple   Slide 3
Why Grid Computing?
•Ask Google, Yahoo, eBay, Amazon
•Solves problems often unsolvable otherwise
  •Google has ~1,000,000 nodes in its grid
•Uniformed programming paradigm
  •Scales from garage to Google




              GridGain – Java Grid Computing Made Simple   Slide 4
GridGain In a Glance
    Open Source Java Grid Computing
• Grid Computing
   • Innovative Compute Grid
   • Integration with Data Grids
• Java
   • Built in Java and for Java
• Open Source
   • LGPL and Apache 2.0

            Elegant simplicity with powerful features

                        GridGain – Java Grid Computing Made Simple   Slide 5
Professional Open Source
• GridGain - Professional Open Source
   • Free and Open Source licenses: LGPL and Apache 2.0
   • Commercial support, training and consulting
• Best business model for software middleware
• Like JBoss, Spring Source, Mule Source…




                    GridGain – Java Grid Computing Made Simple   Slide 6
GridGain Statistics
            In 12 months since the 1st release:

•   Over 20,000 downloads
•   Starts every 60 seconds around the globe
•   One of the largest Amazon EC2 clouds – 512 nodes
•   Over 2000 different individuals, projects and
    organizations

     Fastest Growing Java Grid Computing Middleware


                   GridGain – Java Grid Computing Made Simple   Slide 7
Key Concepts
• MapReduce
• Zero Deployment
• On Demand Scalability
• Fault Tolerance
• LEGO-like Integration
• Transparent Grid Enabling
• Data Grids Integration
• JMX Monitoring
               GridGain – Java Grid Computing Made Simple   Slide 8
MapReduce
Features:
•Direct API support for MapReduce
• Pluggable failover resolution
• Pluggable topology resolution
• Distributed task session
• Annotation-based execution
• Asynchronous execution
• Redundant mapping
• Partial asynchronous reduction
• Adaptive split
• Checkpoints for long running tasks
• Early and late load balancing                  1.     Task execution request
• Affinity co-location with data grids           2.     Task splits into jobs
                                                 3.     Result of job execution
                                                 4.     Aggregation of job results



                                  GridGain – Java Grid Computing Made Simple         Slide 9
Zero Deployment
• Peer-to-Peer Grid Class Loading technology
   • No Ant scripts to run
   • No JARs to copy or FTP
   • No need 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
=> Biggest developer’s productivity boost

                   GridGain – Java Grid Computing Made Simple   Slide 10
On Demand Scalability
• Early and late load balancing:
  • Optimal scalability for non-deterministic
    execution on the grid
• Load Balancing SPI
  • Early load balancing
• Collision SPI
  • Late load balancing
=> Most comprehensive scalability support
                  GridGain – Java Grid Computing Made Simple   Slide 11
Fault Tolerance
• Customizable failover resolution
   • Automatic failover
   • Fail-fast, fail-slow implementation
• Failure – is result too
• Redundant jobs
• Asynchronous results processing
   • Policy-based continuation
• Checkpoints for long-running tasks
   • “Smart” restart in case of failover
• => Most comprehensive fault tolerance functionality

                    GridGain – Java Grid Computing Made Simple   Slide 12
LEGO-Like 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
    • Design approach enabling transparent usability for HPC, traditional grid
      computing and cloud computing
• Grid computing framework aspects that are fully pluggable:
         •   Communication                    •   Checkpoints
         •   Discovery                        •   Failover
         •   Tracing                          •   Collision Resolution
         •   Startup                          •   Topology management
         •   Event storage                    •   Load balancing
         •   Marshalling                      •   Deployment
         •   OnDemand


                          GridGain – Java Grid Computing Made Simple         Slide 13
LEGO-like Integration
“Out-of-the-box” integration with:
Application Servers                        Messaging Middleware
• JBoss AS                                 • Mule
• BEA Weblogic                             • JMS
• IBM Websphere                                • ActiveMQ
• Glassfish                                    • SunMQ
• Tomcat                                   • Jgroups
Data Grids                                 • Email
• JBoss Cache                              • TCP, IP-Multicast
• Coherence                                Others
• GigaSpaces                               • Spring
AOP                                        • Junit
• JBoss AOP                                • JXInsight
• Spring AOP
• AspectJ


                      GridGain – Java Grid Computing Made Simple   Slide 14
Transparent Grid Enabling
01 class BizLogic {                                                  Execution of process()
02   @Gridify(…)                                                     method will be performed on
03   public static Result process(String param) {                    the grid
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 }


                        GridGain – Java Grid Computing Made Simple                      Slide 15
Data Grids Integration
• Integration with Data Grids – key to ultimate
  scalability
• Affinity MapReduce – ability to co-locate processing
  logic and the data
   • a.k.a. Data-aware routing
   • Minimizes “noise” traffic
   • Optimal grid load and performance
• Out-of-the-box support:
   • JBoss Cache
   • Oracle Coherence
                   GridGain – Java Grid Computing Made Simple
Data Grid Integration




    GridGain – Java Grid Computing Made Simple   Slide 17
JMX Monitoring
• Full JMX instrumentation
  • Every SPI
  • Kernal
  • Public APIs
• Flexible access
  • Programmatic via JMX API
  • From GUI JMX console
     • Jboss Management
     • Hyperic
     • Jconsole/VisualVM

                  GridGain – Java Grid Computing Made Simple   Slide 18
Roadmap
• GridGain 1.5 - July 2007
• GridGain 2.0 - February 2008
• GridGain 3.0 - Q109
  • Improved support for cloud computing with
    Amazon EC2
  • Web 2.0 Grid Computing: REST + JSON
  • Enhanced Management and Monitoring


                GridGain – Java Grid Computing Made Simple   Slide 19
Demos
• Java 5/Eclipse 3.2/Windows Vista
• GridGain 2.0




              GridGain – Java Grid Computing Made Simple   Slide 20
Q&A
       Thanks for your time!

Nikita Ivanov: nivanov@gridgain.com
     GridGain: www.gridgain.org




         GridGain – Java Grid Computing Made Simple   Slide 21

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Jug gridgain java_grid_computing_made_simple

  • 1. GridGain – Java Grid Computing Made Simple Dmitriy Setrakyan www.gridgain.org
  • 2. Agenda • GridGain • What is Grid Computing and why • GridGain In a Glance • Key Concepts • Demos • Grid Application in 15 Minutes GridGain – Java Grid Computing Made Simple Slide 2
  • 3. What is Grid Computing? •Compute Grids •Parallelize execution •Data Grids •Parallelize data storage •Grid Computing = Compute Grids + Data Grids •a.k.a. Data Partitioning + Affinity Map/Reduce •Utility, on-demand, cloud computing…? GridGain – Java Grid Computing Made Simple Slide 3
  • 4. Why Grid Computing? •Ask Google, Yahoo, eBay, Amazon •Solves problems often unsolvable otherwise •Google has ~1,000,000 nodes in its grid •Uniformed programming paradigm •Scales from garage to Google GridGain – Java Grid Computing Made Simple Slide 4
  • 5. GridGain In a Glance Open Source Java Grid Computing • Grid Computing • Innovative Compute Grid • Integration with Data Grids • Java • Built in Java and for Java • Open Source • LGPL and Apache 2.0 Elegant simplicity with powerful features GridGain – Java Grid Computing Made Simple Slide 5
  • 6. Professional Open Source • GridGain - Professional Open Source • Free and Open Source licenses: LGPL and Apache 2.0 • Commercial support, training and consulting • Best business model for software middleware • Like JBoss, Spring Source, Mule Source… GridGain – Java Grid Computing Made Simple Slide 6
  • 7. GridGain Statistics In 12 months since the 1st release: • Over 20,000 downloads • Starts every 60 seconds around the globe • One of the largest Amazon EC2 clouds – 512 nodes • Over 2000 different individuals, projects and organizations Fastest Growing Java Grid Computing Middleware GridGain – Java Grid Computing Made Simple Slide 7
  • 8. Key Concepts • MapReduce • Zero Deployment • On Demand Scalability • Fault Tolerance • LEGO-like Integration • Transparent Grid Enabling • Data Grids Integration • JMX Monitoring GridGain – Java Grid Computing Made Simple Slide 8
  • 9. MapReduce Features: •Direct API support for MapReduce • Pluggable failover resolution • Pluggable topology resolution • Distributed task session • Annotation-based execution • Asynchronous execution • Redundant mapping • Partial asynchronous reduction • Adaptive split • Checkpoints for long running tasks • Early and late load balancing 1. Task execution request • Affinity co-location with data grids 2. Task splits into jobs 3. Result of job execution 4. Aggregation of job results GridGain – Java Grid Computing Made Simple Slide 9
  • 10. Zero Deployment • Peer-to-Peer Grid Class Loading technology • No Ant scripts to run • No JARs to copy or FTP • No need 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 => Biggest developer’s productivity boost GridGain – Java Grid Computing Made Simple Slide 10
  • 11. On Demand Scalability • Early and late load balancing: • Optimal scalability for non-deterministic execution on the grid • Load Balancing SPI • Early load balancing • Collision SPI • Late load balancing => Most comprehensive scalability support GridGain – Java Grid Computing Made Simple Slide 11
  • 12. Fault Tolerance • Customizable failover resolution • Automatic failover • Fail-fast, fail-slow implementation • Failure – is result too • Redundant jobs • Asynchronous results processing • Policy-based continuation • Checkpoints for long-running tasks • “Smart” restart in case of failover • => Most comprehensive fault tolerance functionality GridGain – Java Grid Computing Made Simple Slide 12
  • 13. LEGO-Like 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 • Design approach enabling transparent usability for HPC, traditional grid computing and cloud computing • Grid computing framework aspects that are fully pluggable: • Communication • Checkpoints • Discovery • Failover • Tracing • Collision Resolution • Startup • Topology management • Event storage • Load balancing • Marshalling • Deployment • OnDemand GridGain – Java Grid Computing Made Simple Slide 13
  • 14. LEGO-like Integration “Out-of-the-box” integration with: Application Servers Messaging Middleware • JBoss AS • Mule • BEA Weblogic • JMS • IBM Websphere • ActiveMQ • Glassfish • SunMQ • Tomcat • Jgroups Data Grids • Email • JBoss Cache • TCP, IP-Multicast • Coherence Others • GigaSpaces • Spring AOP • Junit • JBoss AOP • JXInsight • Spring AOP • AspectJ GridGain – Java Grid Computing Made Simple Slide 14
  • 15. Transparent Grid Enabling 01 class BizLogic { Execution of process() 02   @Gridify(…) method will be performed on 03   public static Result process(String param) { the grid 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 } GridGain – Java Grid Computing Made Simple Slide 15
  • 16. Data Grids Integration • Integration with Data Grids – key to ultimate scalability • Affinity MapReduce – ability to co-locate processing logic and the data • a.k.a. Data-aware routing • Minimizes “noise” traffic • Optimal grid load and performance • Out-of-the-box support: • JBoss Cache • Oracle Coherence GridGain – Java Grid Computing Made Simple
  • 17. Data Grid Integration GridGain – Java Grid Computing Made Simple Slide 17
  • 18. JMX Monitoring • Full JMX instrumentation • Every SPI • Kernal • Public APIs • Flexible access • Programmatic via JMX API • From GUI JMX console • Jboss Management • Hyperic • Jconsole/VisualVM GridGain – Java Grid Computing Made Simple Slide 18
  • 19. Roadmap • GridGain 1.5 - July 2007 • GridGain 2.0 - February 2008 • GridGain 3.0 - Q109 • Improved support for cloud computing with Amazon EC2 • Web 2.0 Grid Computing: REST + JSON • Enhanced Management and Monitoring GridGain – Java Grid Computing Made Simple Slide 19
  • 20. Demos • Java 5/Eclipse 3.2/Windows Vista • GridGain 2.0 GridGain – Java Grid Computing Made Simple Slide 20
  • 21. Q&A Thanks for your time! Nikita Ivanov: nivanov@gridgain.com GridGain: www.gridgain.org GridGain – Java Grid Computing Made Simple Slide 21

Editor's Notes

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