Infinispan for Dummies

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Galder Zamarreño

Technology

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

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

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

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Distribution vs Replication

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Distribution
• With number of copies = 2

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Consistent Hashing

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

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Traditional 3-tier App

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Typical IaaS App

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Typical PaaS App

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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?

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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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William Hill is one of the UK’s largest, most well-established gaming companies with a global presence across 9 countries with over 16,000 employees. In recent years the gaming industry and in particular sports betting, has been revolutionised by technology. Customers now demand a wide range of events and markets to bet on both pre-game and in-play 24/7. This has driven out a business need to process more data, provide more updates and offer more markets and prices in real time. At William Hill, we have invested in a completely new trading platform using Apache Kafka. We process vast quantities of data from a variety of feeds, this data is fed through a variety of odds compilation models, before being piped out to UI apps for use by our trading teams to provide events, markets and pricing data out to various end points across the whole of William Hill. We deal with thousands of sporting events, each with sometimes hundreds of betting markets, each market receiving hundreds of updates. This scales up to vast numbers of messages flowing through our system. We have to process, transform and route that data in real time. Using Apache Kafka, we have built a high throughput, low latency pipeline, based on Cloud hosted Microservices. When we started, we were on a steep learning curve with Kafka, Microservices and associated technologies. This led to fast learnings and fast failings. In this session, we will tell the story of what we built, what went well, what didn’t go so well and what we learnt. This is a story of how a team of developers learnt (and are still learning) how to use Kafka. We hope that you will be able to take away lessons and learnings of how to build a data processing pipeline with Apache Kafka.

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Infinispan for Dummies

1. Thursday, November 3, 11

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

7. Local cache example 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

9. Invalidation Thursday, November 3, 11

10. Invalidation Thursday, November 3, 11

11. Invalidation 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

13. Clustered cache configuration Thursday, November 3, 11

14. P2P Embedded Architecture 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

16. Distribution vs Replication Thursday, November 3, 11

17. Replication Thursday, November 3, 11

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

19. Consistent Hashing Thursday, November 3, 11

20. Virtual Nodes Thursday, November 3, 11

21. Client/Server Architecture • Supported protocols • REST • Memcached • Hot Rod Thursday, November 3, 11

22. Server Endpoint Comparison Thursday, November 3, 11

23. Hot Rod server and clients Thursday, November 3, 11

24. Traditional 3-tier App Thursday, November 3, 11

25. Typical IaaS App Thursday, November 3, 11

26. Typical PaaS App Thursday, November 3, 11

27. State 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

30. DaaS with Infinispan 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

Infinispan for Dummies

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