Data caching and data grids

Transcript

3. Data Grids and Data Caching ! Galder Zamarreño Senior Software Engineer Red Hat, Inc ! 3rd October 2011, Soft Shake
4. Galder Zamarreño • R&D Engineer, Red Hat Inc. • Infinispan developer • 5+ years exp. with distributed data systems • Twitter: @galderz • Blog: zamarreno.com
5. Agenda • What is Infinispan? • Infinispan as in-memory cache • Infinispan as in-memory data grid • Data-as-a-Service with Infinispan • Who uses Infinispan?
6. Introducing
7. What is Infinispan? An in-memory, highly available, elastic, and open source (LGPL) data grid platform
8. Infinispan can be used as...
9. Local in-memory cache Boost performance caching data which is hard to calculate or expensive to retrieve
10. ConcurrentHashMap ? Infinispan provides greater concurrency with MVCC, has built-in eviction...etc
11. Local cache example
12. A local cache might not be enough...
13. Clustered caches Scale up your application and maintain cache consistency
14. Consistency in a clustered cache...
15. Invalidation
16. Invalidation
17. Invalidation
18. Cache-oriented operations...
19. 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 fail Will never affect existing transactions
20. Accessing Infinispan caches
21. Embedded Access
22. Infinispan is not just a cache!
23. In-memory data grid It’s a Fast, Available, Distributed, Elastic data store, not just a cache!
24. Invalidation won’t work for data grids!
25. Data distribution
26. Replication
27. Distribution • With number of copies = 2
28. How is data distributed??
29. Consistent Hashing
30. Solving unequal distribution
31. Virtual Nodes
32. Accessing Infinispan data grid
33. Remote Access •Via protocols : •REST •Hot Rod
34. Hot Rod clients
35. Infinispan as
    cloud data store
36. Traditional 3-tier App
37. Typical IaaS App
38. Traditional PaaS App
39. Where’s your data stored??
40. Clouds are ephemeral!!
41. State
42. Virtualizing Data Some public services exist (i.e. Amazon RDS), but not all cloud deployments are public!
43. Build your own Data-as-a-Service!
44. Characteristics of DaaS Elastic, scalable and highly available!
45. DaaS with Infinispan
46. Architecture Manage and Monitor
47. Who uses Infinispan?
48. As a cache... Hibernate 2nd level cache, Torquebox Rails cache...
49. As a temporary store... Http session cache & EJB SFSB cache, in JBoss AS7
50. As data grid... Real-time trading app of a well known stock exchange
51. What’s next?
52. Towards EDG Solidifying Infinispan towards integration with Red Hat’s Enterprise Data Grid
53. Plus more data grid... Enhancing Hot Rod protocol, Hibernate Object/Grid Mapper ...etc
54. Summary Infinispan as fast powerful local cache that can be clustered!
55. Summary But also a F.A.D.E. data grid, accessible in embedded or remote fashion
56. Summary Build your own Infinispan based Data-as-a-Service in your private cloud!
57. Questions infinispan.org - @infinispan ! speakerrate.com/galder ! More on data grids at 5pm!