Infinispan for Dummies

Thursday, November 3, 11

for Dummies

Galder ZamarreñoSenior Software Engineer

Red Hat, Inc


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


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?


What is Infinispan?

• Data grid platform:

• Open source (LGPL)

• In-memory

• Highly available

• Elastic


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


Local cache example


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


Invalidation


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 fail

Will never affect existing transactions


Clustered cache configuration


P2P Embedded Architecture


In-memory data grid

• It’s a data store, not just a cache

• An authoritative data sink

• FADE

• Fast

• Available

• Distributed

• Elastic


Distribution vs Replication


Replication


Distribution

• With number of copies = 2


Consistent Hashing


Virtual Nodes


Client/Server Architecture

• Supported protocols

• REST

• Memcached

• Hot Rod


Server Endpoint Comparison


Hot Rod server and clients


Traditional 3-tier App


Typical IaaS App


Typical PaaS App


State


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?


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


DaaS with Infinispan


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


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


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


What’s next?

• Distributed Executors and Map/Reduce

• Hibernate OGM (Object-Grid-Mapping)

• JPA-like interface backed by Infinispan

• ...etc


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


Questions?

• infinispan.org

• blog.infinispan.org

• @infinispan on twitter

• #infinispan for comments

• IRC: #infinispan on FreeNode

• speakerrate.com/galder


Infinispan for Dummies

Technology

Transcript of Infinispan for Dummies