Caching technology comparison

Caching Technologies for Java Applications
Martin Presler-Marshall ICS Performance
09/30/2011

Technologies
General object cache attributes
Memcached
DistributedMap (part of Dynacache)

General Object Cache Characteristics
An object cache is a Key-Value lookup table
Similar to java.util.Hashtable
Have configurable maximum sizes
May be configured number of cache entries or memory size
Objects typically discarded on least-recently-used policy when cache is full
Some caches may offer other algorithms, such as priority-based schemes
Have configurable lifetimes per cache entry
Items are automatically discarded once lifetime is exceeded

Overview: Cache Instances
A cache instance is a logical grouping of cache keys & values
Identical keys in two separate cache instances do not collide
Cache statistics can typically be monitored on an instance level
Support for creating multiple instances varies by cache implementation

Overview: Memcached
“ Free & open source, high-performance, distributed memory object caching system” (from memcached.org)
Main components:
memcached server – standalone server storing cached items
Each cluster of servers is a single cache instance
To run multiple instances, must run multiple servers on each node
memcached client software
Available for multiple programming languages
Keys & values must be serialized, then transmitted over TCP/IP
Cluster design:
Client uses hashing algorithm to assign keys to servers
Each key is cached on at most one server
Explicit invalidations go only to the server which should store that key

Overview: DistributedMap
Built-in component in WAS Network Deployment
Only available to Java clients
Content is cached in JVM memory
Cache operations are POJO calls
Multiple cache instances can be created simply
Each is treated separately for monitoring, synchronization, LRU and invalidation
Cluster design:
Cache keys may be cached in multiple nodes
Explicit invalidation notifies peers to discard the cache key
Option available to push entries to peers on cache insert

Advantages: Dynacache
Fast cache operations - the key raison d'etre for a cache
Lookups through POJO calls - no network delays
No serialization/ deserialization of keys and values – lower CPU consumption
Successful experience with many IBM products & customers
We know how to use it well
Mature, supported part of WAS
Integration points: Extreme Scale, OpenJPA
Flexibility
Easy support for multiple cache instances
Priority-based LRU algorithm
Disk offload
Monitoring/management tools: (PMI, Mbean, Cache Monitor)

Advantages: Memcached
Does not consume memory in Java heap
This is less important on a 64-bit JVM
We've successfully run WAS apps with 6+GB heaps
Active community support
...though available documentation is not great
Usable in Tomcat, WAS CE, php applications
Used successfully by multiple public sites
Single instance of each cache key
No peer-to-peer traffic on invalidations
A key inserted by one node is immediately available to all peers
Typically will increase hit rates
Cache size increases as nodes are added
Free tools exist for monitoring
...but somewhat hard to use

Open Questions
Need some direct performance comparisons
Have done some limited benchmarking of memcached using various clients
Small-scale (single server, small cachesize)
Monitor memcached servers in LotusLive performance environment
May provide useful data on memcached performance in a nearly-real-world use case

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Caching technology comparison

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Caching technology comparison — Presentation Transcript