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Ehcache Architecture, Features and
Usage Patterns
Greg Luck
Maintainer, ehcache - http://ehcache.sf.net
Member, JSR 107 JCACHE Expert Group
Chief Architect, Wotif.com - http://wotif.com


                             2009 Updated from JavaOne Session 2007 |
Agenda
Introduction
The Theory of Caching
Ehcache Architecture
General Purpose Caching
Web Caching
Java Persistence API (JPA)/Hibernate Caching
Distributed Caching for Clusters
Cache Server
Step-by-Step Coding Demo
                    2009 Updated from JavaOne Session 2007 |   2
Introduction
About Ehcache
    Since 2003
●


    The most widely used Java platform Cache
●


    Apache 2.0 License
●


    Integrated by lots of projects, products
●


    Hibernate Provider implemented 2003
●


    Web Caching 2004
●


    Distributed Caching 2006
●


    JCACHE implementation 2007
●


    Cache Server 2008
●



                        2009 Updated from JavaOne Session 2007 |   3
The Theory of Caching
How much faster will caching make an application?
It depends on a multitude of factors being:
● how many times a cached piece of data can and

   is reused by the application
● the proportion of the response time that is

   alleviated by caching
● In applications that are I/O bound, which is most

   business applications, most of the response time
   is getting data from a database. Therefore the
   speed up mostly depends on how much reuse a
   piece of data gets.

                         2009 Updated from JavaOne Session 2007 |   4
The Theory of Caching
Cache Efficiency
Factors which affect the efficiency of a cache are:
● Required Liveness of Data


● Proportion of total data cached


● Read/Write ratio


● Caching in a single VM versus Caching Clusters




                       2009 Updated from JavaOne Session 2007 |   5
The Theory of Caching
How to calculate entire system speedup: Amdahl's Law
Amdahl's law, after Gene Amdahl, is used to find the
 system speed up from a speed up in part of the
 system.
1/ ((1 - Proportion Sped Up) + Proportion Sped Up / Speed up)



Things to Watch:
   ● For a web application the “system” should

     include browser render time and network
     latency.

                           2009 Updated from JavaOne Session 2007 |   6
The Theory of Caching
Speed up from a Web Page Cache
Uncached page time: 2 seconds
Cache retrieval time: 2ms
Proportion: 100%
The expected server side system speedup is thus:
     1 / ((1 - 1) + 1 / 1000)
     = 1 / (0 + .001)
     = 1000 times system speedup
The to the browser “system” speed up is much less

                       2009 Updated from JavaOne Session 2007 |   7
The Theory of Caching
Speed up from a Database Level Cache
Uncached page time: 2 seconds
Database time: 1.5 seconds
Cache retrieval time: 2ms
Proportion: 75% (1.5/2)
The expected system speedup is thus:
    1 / ((1 - .75) + .75 / (1500/2)))
    = 1 / (.25 + .75/750)
    = 3.98 times system speedup

                        2009 Updated from JavaOne Session 2007 |   8
Architecture




               2009 Updated from JavaOne Session 2007 |   9
General Purpose Caching
Step by Step
1. Add ehcache Java Archive (JAR) to your
   classpath
2. Place configuration in ehcache.xml and add it to
   your classpath
3. Create a CacheManager
  CacheManager manager = CacheManager.create();

4. Reference a Cache
  Ehcache sampleCache = manager.getCache();

5. Use it
  sampleCache.put(new Element(“key”, “value”));
  sampleCache.get(“key”);


                                2009 Updated from JavaOne Session 2007 |   10
Usage - General Purpose Caching
ehcache.xml Configuration
<ehcache>

   <diskStore path=quot;java.io.tmpdirquot;/>

   ...

   <cache name=quot;sampleCache1quot;
           maxElementsInMemory=quot;10000quot;
           maxElementsOnDisk=quot;1000quot;
           eternal=quot;falsequot;
           overflowToDisk=quot;truequot;
           timeToIdleSeconds=quot;300quot;
           timeToLiveSeconds=quot;600quot;
           memoryStoreEvictionPolicy=quot;LFUquot;
            />
</ehcache>
                         2009 Updated from JavaOne Session 2007 |   11
Web Caching
Step by Step
1. Use or Subclass SimpleCachingFilter or
   SimplePageFragmentCachingFilter
2. Configure filter in web.xml
3. Create a mapping in web.xml
4. Configure a cache entry matching the filter name




                      2009 Updated from JavaOne Session 2007 |   12
Web Caching
Example Scenario



  /index.jsp




 /include/footer.jsp




                       2009 Updated from JavaOne Session 2007 |   13
Filter Configuration in web.xml
Full Page Cache
<filter>
   <filter-name>SimplePageCachingFilter</filter-name>
   <filter-class>net.sf.ehcache.constructs.web.filter.
               SimplePageCachingFilter
   </filter-class>
</filter>

<filter-mapping>
     <filter-name>SimplePageCachingFilter</filter-name>
     <url-pattern>/index.jsp</url-pattern>
     <dispatcher>REQUEST</dispatcher>
     <dispatcher>INCLUDE</dispatcher>
     <dispatcher>FORWARD</dispatcher>
 </filter-mapping>

                          2009 Updated from JavaOne Session 2007 |   14
Add Cache to Ehcache Configuration
Full Page Cache
<ehcache>

   <diskStore path=quot;java.io.tmpdirquot;/>

   ...

   <cache name=quot;SimplePageCachingFilterquot;
           maxElementsInMemory=quot;10000quot;
           maxElementsOnDisk=quot;1000quot;
           eternal=quot;falsequot;
           overflowToDisk=quot;truequot;
           timeToIdleSeconds=quot;300quot;
           timeToLiveSeconds=quot;600quot;
           memoryStoreEvictionPolicy=quot;LFUquot;
            />
</ehcache>
                         2009 Updated from JavaOne Session 2007 |   15
Filter Configuration in web.xml
Page Fragment Cache
<filter>
   <filter-name>SimplePageFragmentCache</filter-name>
   <filter-class>net.sf.ehcache.constructs.web.filter.
                    SimplePageFragmentCachingFilter
   </filter-class>
</filter>

<!-- Page Fragment Cache -->
<filter-mapping>
     <filter-name>SimplePageFragmentCachingFilter
</filter-name>
     <url-pattern>/include/Footer.jsp</url-pattern>
</filter-mapping>



                          2009 Updated from JavaOne Session 2007 |   16
JPA/Hibernate Caching
Overview
    Hibernate can either be used directly either or
●

    via the Hibernate Java Persistence API Provider
    in Hibernate 3.2
    Ehcache is a CacheProvider for Hibernate 2.x
●

    and 3.x
Example

        Simple Country persistent
    ●

        object/Entity


                         2009 Updated from JavaOne Session 2007 |   17
JPA/Hibernate Caching
Step by Step
1. Configure Hibernate to use ehcache
2. Configure the Country object's cacheability. This
   can be done in a number of ways.
3. Decide whether to use defaults, or to configure
   specific cache settings for the Country object
   cache in ehcache.xml




                       2009 Updated from JavaOne Session 2007 |   18
JPA/Hibernate Caching
Configure Hibernate to use ehcache


Add the following to hibernate.properties
hibernate.cache.provider_class=net.sf.ehcache.hibernate.EhCacheProvider

<!-- optional configuration file parameter -->
net.sf.ehcache.configurationResourceName=/name_of_configuration_resource




                                2009 Updated from JavaOne Session 2007 |   19
JPA/Hibernate Caching
Native Hibernate Mapping File Configuration
<hibernate-mapping>

<class
    name=quot;com.somecompany.someproject.domain.Countryquot;
    table=quot;ut_Countriesquot;
    dynamic-update=quot;falsequot;
    dynamic-insert=quot;falsequot;
>
    <cache usage=quot;read-write|nonstrict-read-write|read-onlyquot; />
</class>
...
</hibernate-mapping>

<cache
    usage=quot;transactional|read-write|nonstrict-read-write|read-onlyquot;
    region=quot;RegionNamequot;
    include=quot;all|non-lazyquot;
/>

                                2009 Updated from JavaOne Session 2007 |   20
JPA/Hibernate Caching
Entity Configuration with JPA and Hibernate Annotations

@Entity
...
@Cache(usage = CacheConcurrencyStrategy.NONSTRICT_READ_WRITE)
public Class Country {

    private String name;

    ...

}




                                2009 Updated from JavaOne Session 2007 |   21
Distributed Caching for Clusters
Features
1. Pluggable distribution mechanism.
2. RMI, JGroups and JMS replication modules.
   Terracotta also has an ehcache provider.
3. Multiple “clusters”
4. Replication set per Cache. Options:
   1. Replicate adds
   2. Replicate removes
   3. Replicate update by copy or invalidate
   4. Async or Sync
5. Bootstrapping from existing Caches in a cluster
                          2009 Updated from JavaOne Session 2007 |   22
Distributed Caching for Clusters
Architecture




                 2009 Updated from JavaOne Session 2007 |   23
Distributed Caching for Clusters
RMI Based Replication
1. Multicast Peer Discovery
  <cacheManagerPeerProviderFactory class=
  quot;net.sf.ehcache.distribution.
  RMICacheManagerPeerProviderFactoryquot;
  properties=quot;peerDiscovery=automatic,
     multicastGroupAddress=230.0.0.1,
  multicastGroupPort=4446/>



2. RMI Listener
   <cacheManagerPeerListenerFactory class=
   quot;net.sf.ehcache.distribution.RMICacheManagerPeerLis
   tenerFactoryquot;properties=quot;port=40001quot;/>



                        2009 Updated from JavaOne Session 2007 |   24
Distributed Caching for Clusters
    Set Replication Per Cache
<cache ...>
   <cacheEventListenerFactory
  class=quot;net.sf.ehcache.distribution.RMICacheReplicatorFactoryquot;
      properties=quot;replicateAsynchronously=true,
      replicatePuts=true,
      replicateUpdates=true,
      replicateUpdatesViaCopy=true,
      replicateRemovals=true,
      asynchronousReplicationIntervalMillis=1000quot;/>
      ...
</cache>




                                2009 Updated from JavaOne Session 2007 |   25
Distributed Caching for Clusters
    Set Bootstrapping Per Cache
<cache ...>
       <bootstrapCacheLoaderFactory class=quot;
  net.sf.ehcache.distribution.RMIBootstrapCacheLoaderFactoryquot;
   properties=quot;bootstrapAsynchronously=true,
               maximumChunkSizeBytes=5000000quot;/>
</cache>




                               2009 Updated from JavaOne Session 2007 |   26
Cache Server
REST and SOAP APIs
Supports HTTP/1.1 request pipelining
Deployed to a WAR or self-contained with Glassfish
Embedded
Benefits over memcached:
•clients in any language
•may utilise HTTP load balancers
•servers are clustered using ehcache replication



                           2009 Updated from JavaOne Session 2007 |   27
Cache Server
Architecture




               2009 Updated from JavaOne Session 2007 |   28
Cache Server
 Ehcache in-process compared with Memcached
 (Ehcache server would be similar to memcached)
7000

6000

5000
                                                                             ehcache-1.2.4
                                                                             memory
4000
                                                                             ehcache-1.2.4 disk
                                                                             memcached-1.2.1
3000

2000

1000

   0
        put/set        get                         remove/delete
                             2009 Updated from JavaOne Session 2007 |   29
Cache Server
Client coding examples
Scala
import java.net.URL
   import scala.io.Source.fromInputStream

   object ExampleScalaGet extends Application {
     val url = new URL(quot;http://localhost:8080/ehcache/rest/sampleCache2/2quot;)
     fromInputStream(url.openStream).getLines.foreach(print)
   }



PHP
<?php
   $ch = curl_init();
   curl_setopt ($ch, CURLOPT_URL, quot;http://localhost:8080/ehcache/rest/sampleCache2/3quot;);
   curl_setopt ($ch, CURLOPT_HEADER, 0);
   curl_exec ($ch);
   curl_close ($ch);
   ?>




                                        2009 Updated from JavaOne Session 2007 |   30
Summary
    Most apps will benefit from caching
●


    You can calculate the speed up
●


    Ehcache is a modern, modular family of caching
●

    tools
    You can also benefit from ehcache indirectly
●

    through frameworks that use it
    Distributed ehcache is a small configuration step
●


    Cache Server is the new kid on the block
●




                        2009 Updated from JavaOne Session 2007 |   31
For More Information
    Project Website:
●

    http://ehcache.sf.net
    Downloadable Book:
●


    http://www.lulu.com/content/paperback-
●

    book/ehcache-150-guide-reference/3553390
    My Email:
●

    gluck@gregluck.com




                            2009 Updated from JavaOne Session 2007 |   32
Q&A
Greg Luck
gluck@gregluck.com




                                                                33
                     2009 Updated from JavaOne Session 2007 |

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Ehcache Architecture, Features And Usage Patterns

  • 1. Ehcache Architecture, Features and Usage Patterns Greg Luck Maintainer, ehcache - http://ehcache.sf.net Member, JSR 107 JCACHE Expert Group Chief Architect, Wotif.com - http://wotif.com 2009 Updated from JavaOne Session 2007 |
  • 2. Agenda Introduction The Theory of Caching Ehcache Architecture General Purpose Caching Web Caching Java Persistence API (JPA)/Hibernate Caching Distributed Caching for Clusters Cache Server Step-by-Step Coding Demo 2009 Updated from JavaOne Session 2007 | 2
  • 3. Introduction About Ehcache Since 2003 ● The most widely used Java platform Cache ● Apache 2.0 License ● Integrated by lots of projects, products ● Hibernate Provider implemented 2003 ● Web Caching 2004 ● Distributed Caching 2006 ● JCACHE implementation 2007 ● Cache Server 2008 ● 2009 Updated from JavaOne Session 2007 | 3
  • 4. The Theory of Caching How much faster will caching make an application? It depends on a multitude of factors being: ● how many times a cached piece of data can and is reused by the application ● the proportion of the response time that is alleviated by caching ● In applications that are I/O bound, which is most business applications, most of the response time is getting data from a database. Therefore the speed up mostly depends on how much reuse a piece of data gets. 2009 Updated from JavaOne Session 2007 | 4
  • 5. The Theory of Caching Cache Efficiency Factors which affect the efficiency of a cache are: ● Required Liveness of Data ● Proportion of total data cached ● Read/Write ratio ● Caching in a single VM versus Caching Clusters 2009 Updated from JavaOne Session 2007 | 5
  • 6. The Theory of Caching How to calculate entire system speedup: Amdahl's Law Amdahl's law, after Gene Amdahl, is used to find the system speed up from a speed up in part of the system. 1/ ((1 - Proportion Sped Up) + Proportion Sped Up / Speed up) Things to Watch: ● For a web application the “system” should include browser render time and network latency. 2009 Updated from JavaOne Session 2007 | 6
  • 7. The Theory of Caching Speed up from a Web Page Cache Uncached page time: 2 seconds Cache retrieval time: 2ms Proportion: 100% The expected server side system speedup is thus: 1 / ((1 - 1) + 1 / 1000) = 1 / (0 + .001) = 1000 times system speedup The to the browser “system” speed up is much less 2009 Updated from JavaOne Session 2007 | 7
  • 8. The Theory of Caching Speed up from a Database Level Cache Uncached page time: 2 seconds Database time: 1.5 seconds Cache retrieval time: 2ms Proportion: 75% (1.5/2) The expected system speedup is thus: 1 / ((1 - .75) + .75 / (1500/2))) = 1 / (.25 + .75/750) = 3.98 times system speedup 2009 Updated from JavaOne Session 2007 | 8
  • 9. Architecture 2009 Updated from JavaOne Session 2007 | 9
  • 10. General Purpose Caching Step by Step 1. Add ehcache Java Archive (JAR) to your classpath 2. Place configuration in ehcache.xml and add it to your classpath 3. Create a CacheManager CacheManager manager = CacheManager.create(); 4. Reference a Cache Ehcache sampleCache = manager.getCache(); 5. Use it sampleCache.put(new Element(“key”, “value”)); sampleCache.get(“key”); 2009 Updated from JavaOne Session 2007 | 10
  • 11. Usage - General Purpose Caching ehcache.xml Configuration <ehcache> <diskStore path=quot;java.io.tmpdirquot;/> ... <cache name=quot;sampleCache1quot; maxElementsInMemory=quot;10000quot; maxElementsOnDisk=quot;1000quot; eternal=quot;falsequot; overflowToDisk=quot;truequot; timeToIdleSeconds=quot;300quot; timeToLiveSeconds=quot;600quot; memoryStoreEvictionPolicy=quot;LFUquot; /> </ehcache> 2009 Updated from JavaOne Session 2007 | 11
  • 12. Web Caching Step by Step 1. Use or Subclass SimpleCachingFilter or SimplePageFragmentCachingFilter 2. Configure filter in web.xml 3. Create a mapping in web.xml 4. Configure a cache entry matching the filter name 2009 Updated from JavaOne Session 2007 | 12
  • 13. Web Caching Example Scenario /index.jsp /include/footer.jsp 2009 Updated from JavaOne Session 2007 | 13
  • 14. Filter Configuration in web.xml Full Page Cache <filter> <filter-name>SimplePageCachingFilter</filter-name> <filter-class>net.sf.ehcache.constructs.web.filter. SimplePageCachingFilter </filter-class> </filter> <filter-mapping> <filter-name>SimplePageCachingFilter</filter-name> <url-pattern>/index.jsp</url-pattern> <dispatcher>REQUEST</dispatcher> <dispatcher>INCLUDE</dispatcher> <dispatcher>FORWARD</dispatcher> </filter-mapping> 2009 Updated from JavaOne Session 2007 | 14
  • 15. Add Cache to Ehcache Configuration Full Page Cache <ehcache> <diskStore path=quot;java.io.tmpdirquot;/> ... <cache name=quot;SimplePageCachingFilterquot; maxElementsInMemory=quot;10000quot; maxElementsOnDisk=quot;1000quot; eternal=quot;falsequot; overflowToDisk=quot;truequot; timeToIdleSeconds=quot;300quot; timeToLiveSeconds=quot;600quot; memoryStoreEvictionPolicy=quot;LFUquot; /> </ehcache> 2009 Updated from JavaOne Session 2007 | 15
  • 16. Filter Configuration in web.xml Page Fragment Cache <filter> <filter-name>SimplePageFragmentCache</filter-name> <filter-class>net.sf.ehcache.constructs.web.filter. SimplePageFragmentCachingFilter </filter-class> </filter> <!-- Page Fragment Cache --> <filter-mapping> <filter-name>SimplePageFragmentCachingFilter </filter-name> <url-pattern>/include/Footer.jsp</url-pattern> </filter-mapping> 2009 Updated from JavaOne Session 2007 | 16
  • 17. JPA/Hibernate Caching Overview Hibernate can either be used directly either or ● via the Hibernate Java Persistence API Provider in Hibernate 3.2 Ehcache is a CacheProvider for Hibernate 2.x ● and 3.x Example Simple Country persistent ● object/Entity 2009 Updated from JavaOne Session 2007 | 17
  • 18. JPA/Hibernate Caching Step by Step 1. Configure Hibernate to use ehcache 2. Configure the Country object's cacheability. This can be done in a number of ways. 3. Decide whether to use defaults, or to configure specific cache settings for the Country object cache in ehcache.xml 2009 Updated from JavaOne Session 2007 | 18
  • 19. JPA/Hibernate Caching Configure Hibernate to use ehcache Add the following to hibernate.properties hibernate.cache.provider_class=net.sf.ehcache.hibernate.EhCacheProvider <!-- optional configuration file parameter --> net.sf.ehcache.configurationResourceName=/name_of_configuration_resource 2009 Updated from JavaOne Session 2007 | 19
  • 20. JPA/Hibernate Caching Native Hibernate Mapping File Configuration <hibernate-mapping> <class name=quot;com.somecompany.someproject.domain.Countryquot; table=quot;ut_Countriesquot; dynamic-update=quot;falsequot; dynamic-insert=quot;falsequot; > <cache usage=quot;read-write|nonstrict-read-write|read-onlyquot; /> </class> ... </hibernate-mapping> <cache usage=quot;transactional|read-write|nonstrict-read-write|read-onlyquot; region=quot;RegionNamequot; include=quot;all|non-lazyquot; /> 2009 Updated from JavaOne Session 2007 | 20
  • 21. JPA/Hibernate Caching Entity Configuration with JPA and Hibernate Annotations @Entity ... @Cache(usage = CacheConcurrencyStrategy.NONSTRICT_READ_WRITE) public Class Country { private String name; ... } 2009 Updated from JavaOne Session 2007 | 21
  • 22. Distributed Caching for Clusters Features 1. Pluggable distribution mechanism. 2. RMI, JGroups and JMS replication modules. Terracotta also has an ehcache provider. 3. Multiple “clusters” 4. Replication set per Cache. Options: 1. Replicate adds 2. Replicate removes 3. Replicate update by copy or invalidate 4. Async or Sync 5. Bootstrapping from existing Caches in a cluster 2009 Updated from JavaOne Session 2007 | 22
  • 23. Distributed Caching for Clusters Architecture 2009 Updated from JavaOne Session 2007 | 23
  • 24. Distributed Caching for Clusters RMI Based Replication 1. Multicast Peer Discovery <cacheManagerPeerProviderFactory class= quot;net.sf.ehcache.distribution. RMICacheManagerPeerProviderFactoryquot; properties=quot;peerDiscovery=automatic, multicastGroupAddress=230.0.0.1, multicastGroupPort=4446/> 2. RMI Listener <cacheManagerPeerListenerFactory class= quot;net.sf.ehcache.distribution.RMICacheManagerPeerLis tenerFactoryquot;properties=quot;port=40001quot;/> 2009 Updated from JavaOne Session 2007 | 24
  • 25. Distributed Caching for Clusters Set Replication Per Cache <cache ...> <cacheEventListenerFactory class=quot;net.sf.ehcache.distribution.RMICacheReplicatorFactoryquot; properties=quot;replicateAsynchronously=true, replicatePuts=true, replicateUpdates=true, replicateUpdatesViaCopy=true, replicateRemovals=true, asynchronousReplicationIntervalMillis=1000quot;/> ... </cache> 2009 Updated from JavaOne Session 2007 | 25
  • 26. Distributed Caching for Clusters Set Bootstrapping Per Cache <cache ...> <bootstrapCacheLoaderFactory class=quot; net.sf.ehcache.distribution.RMIBootstrapCacheLoaderFactoryquot; properties=quot;bootstrapAsynchronously=true, maximumChunkSizeBytes=5000000quot;/> </cache> 2009 Updated from JavaOne Session 2007 | 26
  • 27. Cache Server REST and SOAP APIs Supports HTTP/1.1 request pipelining Deployed to a WAR or self-contained with Glassfish Embedded Benefits over memcached: •clients in any language •may utilise HTTP load balancers •servers are clustered using ehcache replication 2009 Updated from JavaOne Session 2007 | 27
  • 28. Cache Server Architecture 2009 Updated from JavaOne Session 2007 | 28
  • 29. Cache Server Ehcache in-process compared with Memcached (Ehcache server would be similar to memcached) 7000 6000 5000 ehcache-1.2.4 memory 4000 ehcache-1.2.4 disk memcached-1.2.1 3000 2000 1000 0 put/set get remove/delete 2009 Updated from JavaOne Session 2007 | 29
  • 30. Cache Server Client coding examples Scala import java.net.URL import scala.io.Source.fromInputStream object ExampleScalaGet extends Application { val url = new URL(quot;http://localhost:8080/ehcache/rest/sampleCache2/2quot;) fromInputStream(url.openStream).getLines.foreach(print) } PHP <?php $ch = curl_init(); curl_setopt ($ch, CURLOPT_URL, quot;http://localhost:8080/ehcache/rest/sampleCache2/3quot;); curl_setopt ($ch, CURLOPT_HEADER, 0); curl_exec ($ch); curl_close ($ch); ?> 2009 Updated from JavaOne Session 2007 | 30
  • 31. Summary Most apps will benefit from caching ● You can calculate the speed up ● Ehcache is a modern, modular family of caching ● tools You can also benefit from ehcache indirectly ● through frameworks that use it Distributed ehcache is a small configuration step ● Cache Server is the new kid on the block ● 2009 Updated from JavaOne Session 2007 | 31
  • 32. For More Information Project Website: ● http://ehcache.sf.net Downloadable Book: ● http://www.lulu.com/content/paperback- ● book/ehcache-150-guide-reference/3553390 My Email: ● gluck@gregluck.com 2009 Updated from JavaOne Session 2007 | 32
  • 33. Q&A Greg Luck gluck@gregluck.com 33 2009 Updated from JavaOne Session 2007 |