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Thursday, November 3, 11
for Dummies
                              Galder Zamarreño
                           Senior Software Engineer
                                 Red Hat, Inc




Thursday, November 3, 11
Who is Galder?
                           • R&D engineer (Red Hat Inc):
                            • Infinispan developer
                           • Contributor and committer:
                            • JBoss AS, Hibernate, JGroups...etc
                           • More about me?
                            • Blog: zamarreno.com
                            • Twitter: @galderz


Thursday, November 3, 11
Agenda

                           • What is Infinispan?
                           • Infinispan as in-memory cache
                           • Infinispan as in-memory data grid
                           • Data-as-a-Service with Infinispan
                           • Clustering and migration challenges
                           • Who uses Infinispan?



Thursday, November 3, 11
What is Infinispan?

                           • Data grid platform:
                            • Open source (LGPL)
                            • In-memory
                            • Highly available
                            • Elastic




Thursday, November 3, 11
Local in-memory cache
                           • Performance booster
                           • Good for data that is:
                            • Hard to calculate
                            • Expensive to retrieve...etc
                           • Why not ConcurrentHashMap? Infinispan offers:
                            • Greater concurrency with MVCC
                            • Built-in eviction...etc


Thursday, November 3, 11
Local cache example




Thursday, November 3, 11
Clustered in-memory cache


                           • Same as local but cluster-aware
                           • More shared-cache space!
                           • Can help you cluster your framework too!
                           • Invalidation cache mode commonly used




Thursday, November 3, 11
Invalidation




Thursday, November 3, 11
Invalidation




Thursday, November 3, 11
Invalidation




Thursday, November 3, 11
Cache.putForExternalRead()
                                         put()                   putForExternalRead()

                                 Use for updating state          Use to cache state read from
                                                                       external source

                            Regular lock acquisition timeout               Fail-fast


                               Could throw an exception                  Fails quietly


                           Could cause existing transaction to     Will never affect existing
                                          fail                           transactions




Thursday, November 3, 11
Clustered cache configuration




Thursday, November 3, 11
P2P Embedded Architecture




Thursday, November 3, 11
In-memory data grid
                           • It’s a data store, not just a cache
                           • An authoritative data sink
                           • FADE
                            • Fast
                            • Available
                            • Distributed
                            • Elastic


Thursday, November 3, 11
Distribution vs Replication




Thursday, November 3, 11
Replication




Thursday, November 3, 11
Distribution
                           • With number of copies = 2




Thursday, November 3, 11
Consistent Hashing




Thursday, November 3, 11
Virtual Nodes




Thursday, November 3, 11
Client/Server Architecture


                                          •   Supported protocols
                                              •   REST
                                              •   Memcached
                                              •   Hot Rod




Thursday, November 3, 11
Server Endpoint Comparison




Thursday, November 3, 11
Hot Rod server and clients




Thursday, November 3, 11
Traditional 3-tier App




Thursday, November 3, 11
Typical IaaS App




Thursday, November 3, 11
Typical PaaS App




Thursday, November 3, 11
State




Thursday, November 3, 11
Virtualize data

                           • Some public services exist
                            • Amazon RDS and SimpleDB
                            • FathomDB, Cloudant...etc
                           • But not all cloud deployments are public!
                            • Private cloud very important
                            • How can you build a DaaS yourself?



Thursday, November 3, 11
Characteristics of DaaS

                           • Elastic data
                           • Need to scale with other tiers
                           • Response times should be linear
                           • Needs to be highly available!
                            • Nodes with die! The service shouldn’t




Thursday, November 3, 11
DaaS with Infinispan




Thursday, November 3, 11
Clustering challenges

                           • JGroups taking care of clustering
                            • Default config file good for 4-16 nodes
                           • Bigger clusters require tweaking...
                           • Adjust transport and discovery to environment limitations
                            • Especially where UDP multicast not allowed
                           • These adjustments do not require altering code



Thursday, November 3, 11
Migration best practices


                           • ‘RadarGun’ project benchmarks different data grid products
                           • Benchmark your use case!
                           • Helps with mapping between different provider APIs
                           • XSLTs distributed to transform configuration




Thursday, November 3, 11
Who uses Infinispan?

                           • Examples:
                            • As a cache:
                              • Hibernate for the second level cache
                              • HTTP session cache in JBoss AS 6 and AS 7
                            • As a data grid:
                              • Real-time trading app of a well known stock exchange



Thursday, November 3, 11
What’s next?


                           • Distributed Executors and Map/Reduce
                           • Hibernate OGM (Object-Grid-Mapping)
                             • JPA-like interface backed by Infinispan
                           • ...etc




Thursday, November 3, 11
Summary

                           • Infinispan is a fast powerful local cache
                           • More space and scales up when cache is clustered
                           • Infinispan is also a distributed elastic data grid
                           • Accessible in embedded and client/server mode
                           • Build your own Data-as-a-Service with Infinispan




Thursday, November 3, 11
Questions?

                           • infinispan.org
                           • blog.infinispan.org
                           • @infinispan on twitter
                            • #infinispan for comments
                           • IRC: #infinispan on FreeNode
                           • speakerrate.com/galder



Thursday, November 3, 11

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Infinispan for Dummies

  • 2. for Dummies Galder Zamarreño Senior Software Engineer Red Hat, Inc Thursday, November 3, 11
  • 3. Who is Galder? • R&D engineer (Red Hat Inc): • Infinispan developer • Contributor and committer: • JBoss AS, Hibernate, JGroups...etc • More about me? • Blog: zamarreno.com • Twitter: @galderz Thursday, November 3, 11
  • 4. Agenda • What is Infinispan? • Infinispan as in-memory cache • Infinispan as in-memory data grid • Data-as-a-Service with Infinispan • Clustering and migration challenges • Who uses Infinispan? Thursday, November 3, 11
  • 5. What is Infinispan? • Data grid platform: • Open source (LGPL) • In-memory • Highly available • Elastic Thursday, November 3, 11
  • 6. Local in-memory cache • Performance booster • Good for data that is: • Hard to calculate • Expensive to retrieve...etc • Why not ConcurrentHashMap? Infinispan offers: • Greater concurrency with MVCC • Built-in eviction...etc Thursday, November 3, 11
  • 8. Clustered in-memory cache • Same as local but cluster-aware • More shared-cache space! • Can help you cluster your framework too! • Invalidation cache mode commonly used Thursday, November 3, 11
  • 12. Cache.putForExternalRead() put() putForExternalRead() Use for updating state Use to cache state read from external source Regular lock acquisition timeout Fail-fast Could throw an exception Fails quietly Could cause existing transaction to Will never affect existing fail transactions Thursday, November 3, 11
  • 15. In-memory data grid • It’s a data store, not just a cache • An authoritative data sink • FADE • Fast • Available • Distributed • Elastic Thursday, November 3, 11
  • 18. Distribution • With number of copies = 2 Thursday, November 3, 11
  • 21. Client/Server Architecture • Supported protocols • REST • Memcached • Hot Rod Thursday, November 3, 11
  • 23. Hot Rod server and clients Thursday, November 3, 11
  • 25. Typical IaaS App Thursday, November 3, 11
  • 26. Typical PaaS App Thursday, November 3, 11
  • 28. Virtualize data • Some public services exist • Amazon RDS and SimpleDB • FathomDB, Cloudant...etc • But not all cloud deployments are public! • Private cloud very important • How can you build a DaaS yourself? Thursday, November 3, 11
  • 29. Characteristics of DaaS • Elastic data • Need to scale with other tiers • Response times should be linear • Needs to be highly available! • Nodes with die! The service shouldn’t Thursday, November 3, 11
  • 31. Clustering challenges • JGroups taking care of clustering • Default config file good for 4-16 nodes • Bigger clusters require tweaking... • Adjust transport and discovery to environment limitations • Especially where UDP multicast not allowed • These adjustments do not require altering code Thursday, November 3, 11
  • 32. Migration best practices • ‘RadarGun’ project benchmarks different data grid products • Benchmark your use case! • Helps with mapping between different provider APIs • XSLTs distributed to transform configuration Thursday, November 3, 11
  • 33. Who uses Infinispan? • Examples: • As a cache: • Hibernate for the second level cache • HTTP session cache in JBoss AS 6 and AS 7 • As a data grid: • Real-time trading app of a well known stock exchange Thursday, November 3, 11
  • 34. What’s next? • Distributed Executors and Map/Reduce • Hibernate OGM (Object-Grid-Mapping) • JPA-like interface backed by Infinispan • ...etc Thursday, November 3, 11
  • 35. Summary • Infinispan is a fast powerful local cache • More space and scales up when cache is clustered • Infinispan is also a distributed elastic data grid • Accessible in embedded and client/server mode • Build your own Data-as-a-Service with Infinispan Thursday, November 3, 11
  • 36. Questions? • infinispan.org • blog.infinispan.org • @infinispan on twitter • #infinispan for comments • IRC: #infinispan on FreeNode • speakerrate.com/galder Thursday, November 3, 11