Release 2.2.0 Poblano
Copyright © 2004, 2005, 2006, 2007, 2008 JBoss, a division of Red Hat Inc.
May 2008
This is the official JBoss Cache user guide. Along with its accompanying documents (an FAQ, a tutorial and a whole set of documents on PojoCache), this is freely available on the JBoss Cache documentation site.
When used, JBoss Cache refers to JBoss Cache Core, a tree-structured, clustered, transactional cache. Pojo Cache, also a part of the JBoss Cache distribution, is documented separately. (Pojo Cache is a cache that deals with Plain Old Java Objects, complete with object relationships, with the ability to cluster such pojos while maintaining their relationships. Please see the Pojo Cache documentation for more information about this.)
This book is targeted at both developers wishing to use JBoss Cache as a clustering and caching library in their codebase, as well as people who wish to "OEM" JBoss Cache by building on and extending its features. As such, this book is split into two major sections - one detailing the "User" API and the other going much deeper into specialist topics and the JBoss Cache architecture.
In general, a good knowledge of the Java programming language along with a strong appreciation and understanding of transactions and concurrent threads is necessary. No prior knowledge of JBoss Application Server is expected or required.
For further discussion, use the user forum linked on the JBoss Cache website. We also provide a mechanism for tracking bug reports and feature requests on the JBoss Cache JIRA issue tracker. If you are interested in the development of JBoss Cache or in translating this documentation into other languages, we'd love to hear from you. Please post a message on the user forum or contact us by using the JBoss Cache developer mailing list.
This book is specifically targeted at the JBoss Cache release of the same version number. It may not apply to older or newer releases of JBoss Cache. It is important that you use the documentation appropriate to the version of JBoss Cache you intend to use.
This section covers what developers would need to quickly start using JBoss Cache in their projects. It covers an overview of the concepts and API, configuration and deployment information.
Table of Contents
JBoss Cache is a tree-structured, clustered, transactional cache. It is the backbone for many fundamental JBoss Application Server clustering services, including - in certain versions - clustering JNDI, HTTP and EJB sessions.
JBoss Cache can also be used as a standalone transactional and clustered caching library or even an object oriented data store. It can even be embedded in other enterprise Java frameworks and application servers such as BEA WebLogic or IBM WebSphere, Tomcat, Spring, Hibernate, and many others. It is also very commonly used directly by standalone Java applications that do not run from within an application server, to maintain clustered state.
Pojo Cache is an extension of the core JBoss Cache API. Pojo Cache offers additional functionality such as:
maintaining object references even after replication or persistence.
fine grained replication, where only modified object fields are replicated.
"API-less" clustering model where pojos are simply annotated as being clustered.
Pojo Cache has a complete and separate set of documentation, including a user guide, FAQ and tutorial and as such, Pojo Cache is not discussed further in this book.
JBoss Cache offers a simple and straightforward API, where data (simple Java objects) can be placed in the cache and, based on configuration options selected, this data may be one or all of:
replicated to some or all cache instances in a cluster.
persisted to disk and/or a remote cluster ("far-cache").
garbage collected from memory when memory runs low, and passivated to disk so state isn't lost.
In addition, JBoss Cache offers a rich set of enterprise-class features:
being able to participate in JTA transactions (works with Java EE compliant TransactionManagers).
attach to JMX servers and provide runtime statistics on the state of the cache.
allow client code to attach listeners and receive notifications on cache events.
A cache is organised as a tree, with a single root. Each node in the tree essentially contains a Map, which acts as a store for key/value pairs. The only requirement placed on objects that are cached is that they implement java.io.Serializable
. Note that this requirement does not exist for Pojo Cache.
JBoss Cache can be either local or replicated. Local trees exist only inside the JVM in which they are created, whereas replicated trees propagate any changes to some or all other trees in the same cluster. A cluster may span different hosts on a network or just different JVMs on a single host.
When a change is made to an object in the cache and that change is done in the context of a transaction, the replication of changes is deferred until the transaction commits successfully. All modifications are kept in a list associated with the transaction for the caller. When the transaction commits, we replicate the changes. Otherwise, (on a rollback) we simply undo the changes locally resulting in zero network traffic and overhead. For example, if a caller makes 100 modifications and then rolls back the transaction, we will not replicate anything, resulting in no network traffic.
If a caller has no transaction associated with it (and isolation level is not NONE - more about this later), we will replicate right after each modification, e.g. in the above case we would send 100 messages, plus an additional message for the rollback. In this sense, running without a transaction can be thought of as analogous as running with auto-commit switched on in JDBC terminology, where each operation is committed automatically.
JBoss Cache works out of the box with most popular transaction managers, and even provides an API where custom transaction manager lookups can be written.
The cache is also completely thread-safe. It uses a pessimistic locking scheme for nodes in the tree by default, with an optimistic locking scheme as a configurable option. With pessimistic locking, the degree of concurrency can be tuned using a number of isolation levels, corresponding to database-style transaction isolation levels, i.e., SERIALIZABLE, REPEATABLE_READ, READ_COMMITTED, READ_UNCOMMITTED and NONE. Concurrency, locking and isolation levels will be discussed later.
JBoss Cache requires Java 5.0 (or newer).
However, there is a way to build JBoss Cache as a Java 1.4.x compatible binary using JBossRetro to retroweave the Java 5.0 binaries. However, Red Hat Inc. does not offer professional support around the retroweaved binary at this time and the Java 1.4.x compatible binary is not in the binary distribution. See this wiki page for details on building the retroweaved binary for yourself.
In addition to Java 5.0, at a minimum, JBoss Cache has dependencies on JGroups , and Apache's commons-logging . JBoss Cache ships with all dependent libraries necessary to run out of the box.
JBoss Cache is an open source product, using the business and OEM-friendly OSI-approvedLGPL license. Commercial development support, production support and training for JBoss Cache is available through JBoss, a division of Red Hat Inc. JBoss Cache is a part of JBoss Professional Open Source JEMS (JBoss Enterprise Middleware Suite).
The Cache
interface is the primary mechanism for interacting with JBoss Cache. It is constructed and optionally started using the CacheFactory
. The CacheFactory
allows you to create a Cache
either from a Configuration
object or an XML file. Once you have a reference to a Cache
, you can use it to look up Node
objects in the tree structure, and store data in the tree.
Reviewing the javadoc for the above interfaces is the best way to learn the API. Below we cover some of the main points.
An instance of the Cache
interface can only be created via a CacheFactory
. (This is unlike JBoss Cache 1.x, where an instance of the old TreeCache
class could be directly instantiated.)
CacheFactory
provides a number of overloaded methods for creating a Cache
, but they all do the same thing:
Gain access to a Configuration
, either by having one passed in as a method parameter, or by parsing XML content and constructing one. The XML content can come from a provided input stream or from a classpath or filesystem location. See the chapter on Configuration for more on obtaining a Configuration
.
Instantiate the Cache
and provide it with a reference to the Configuration
.
Optionally invoke the cache's create()
and start()
methods.
An example of the simplest mechanism for creating and starting a cache, using the default configuration values:
CacheFactory factory = new DefaultCacheFactory(); Cache cache = factory.createCache();
Here we tell the CacheFactory
to find and parse a configuration file on the classpath:
CacheFactory factory = new DefaultCacheFactory(); Cache cache = factory.createCache("cache-configuration.xml");
Here we configure the cache from a file, but want to programatically change a configuration element. So, we tell the factory not to start the cache, and instead do it ourselves:
CacheFactory factory = new DefaultCacheFactory(); Cache cache = factory.createCache("cache-configuration.xml", false); Configuration config = cache.getConfiguration(); config.setClusterName(this.getClusterName()); // Have to create and start cache before using it cache.create(); cache.start();
Next, let's use the Cache
API to access a Node
in the cache and then do some simple reads and writes to that node.
// Let's get ahold of the root node. Node rootNode = cache.getRoot(); // Remember, JBoss Cache stores data in a tree structure. // All nodes in the tree structure are identified by Fqn objects. Fqn peterGriffinFqn = Fqn.fromString("/griffin/peter"); // Create a new Node Node peterGriffin = rootNode.addChild(peterGriffinFqn); // let's store some data in the node peterGriffin.put("isCartoonCharacter", Boolean.TRUE); peterGriffin.put("favouriteDrink", new Beer()); // some tests (just assume this code is in a JUnit test case) assertTrue(peterGriffin.get("isCartoonCharacter")); assertEquals(peterGriffinFqn, peterGriffin.getFqn()); assertTrue(rootNode.hasChild(peterGriffinFqn)); Set keys = new HashSet(); keys.add("isCartoonCharacter"); keys.add("favouriteDrink"); assertEquals(keys, peterGriffin.getKeys()); // let's remove some data from the node peterGriffin.remove("favouriteDrink"); assertNull(peterGriffin.get("favouriteDrink"); // let's remove the node altogether rootNode.removeChild(peterGriffinFqn); assertFalse(rootNode.hasChild(peterGriffinFqn));
The Cache
interface also exposes put/get/remove operations that take an Fqn as an argument:
Fqn peterGriffinFqn = Fqn.fromString("/griffin/peter"); cache.put(peterGriffinFqn, "isCartoonCharacter", Boolean.TRUE); cache.put(peterGriffinFqn, "favouriteDrink", new Beer()); assertTrue(peterGriffin.get(peterGriffinFqn, "isCartoonCharacter")); assertTrue(cache.getRootNode().hasChild(peterGriffinFqn)); cache.remove(peterGriffinFqn, "favouriteDrink"); assertNull(cache.get(peterGriffinFqn, "favouriteDrink"); cache.removeNode(peterGriffinFqn); assertFalse(cache.getRootNode().hasChild(peterGriffinFqn));
The previous section used the Fqn
class in its examples; now let's learn a bit more about that class.
A Fully Qualified Name (Fqn) encapsulates a list of names which represent a path to a particular location in the cache's tree structure. The elements in the list are typically String
s but can be any Object
or a mix of different types.
This path can be absolute (i.e., relative to the root node), or relative to any node in the cache. Reading the documentation on each API call that makes use of Fqn
will tell you whether the API expects a relative or absolute Fqn
.
The Fqn
class provides are variety of constructors; see the javadoc for all the possibilities. The following illustrates the most commonly used approaches to creating an Fqn:
// Create an Fqn pointing to node 'Joe' under parent node 'Smith' // under the 'people' section of the tree // Parse it from a String Fqn<String> abc = Fqn.fromString("/people/Smith/Joe/"); // Build it directly. Marginally more efficient to construct than parsing String[] strings = new String[] { "people", "Smith", "Joe" }; Fqn<String> abc = new Fqn<String>(strings); // Here we want to use types other than String Object[] objs = new Object[]{ "accounts", "NY", new Integer(12345) }; Fqn<Object> acctFqn = new Fqn<Object>(objs);
Note that
Fqn<String> f = new Fqn<String>("/a/b/c");
is not the same as
Fqn<String> f = Fqn.fromString("/a/b/c");
The former will result in an Fqn with a single element, called "/a/b/c" which hangs directly under the cache root. The latter will result in a 3 element Fqn, where "c" idicates a child of "b", which is a child of "a", and "a" hangs off the cache root. Another way to look at it is that the "/" separarator is only parsed when it forms part of a String passed in to Fqn.fromString()
and not otherwise.
The JBoss Cache API in the 1.x releases included many overloaded convenience methods that took a string in the /a/b/c
format in place of an Fqn
. In the interests of API simplicity, no such convenience methods are available in the JBC 2.x API.
It is good practice to stop and destroy your cache when you are done using it, particularly if it is a clustered cache and has thus used a JGroups channel. Stopping and destroying a cache ensures resources like the JGroups channel are properly cleaned up.
cache.stop(); cache.destroy();
Not also that a cache that has had stop()
invoked on it can be started again with a new call to start()
. Similarly, a cache that has had destroy()
invoked on it can be created again with a new call to create()
(and then started again with a start()
call).
Although technically not part of the API, the mode in which the cache is configured to operate affects the cluster-wide behavior of any put
or remove
operation, so we'll briefly mention the various modes here.
JBoss Cache modes are denoted by the org.jboss.cache.config.Configuration.CacheMode
enumeration. They consist of:
LOCAL - local, non-clustered cache. Local caches don't join a cluster and don't communicate with other caches in a cluster. Therefore their contents don't need to be Serializable; however, we recommend making them Serializable, allowing you the flexibility to change the cache mode at any time.
REPL_SYNC - synchronous replication. Replicated caches replicate all changes to the other caches in the cluster. Synchronous replication means that changes are replicated and the caller blocks until replication acknowledgements are received.
REPL_ASYNC - asynchronous replication. Similar to REPL_SYNC above, replicated caches replicate all changes to the other caches in the cluster. Being asynchronous, the caller does not block until replication acknowledgements are received.
INVALIDATION_SYNC - if a cache is configured for invalidation rather than replication, every time data is changed in a cache other caches in the cluster receive a message informing them that their data is now stale and should be evicted from memory. This reduces replication overhead while still being able to invalidate stale data on remote caches.
INVALIDATION_ASYNC - as above, except this invalidation mode causes invalidation messages to be broadcast asynchronously.
See the chapter on Clustering for more details on how the cache's mode affects behavior. See the chapter on Configuration for info on how to configure things like the cache's mode.
JBoss Cache provides a convenient mechanism for registering notifications on cache events.
Object myListener = new MyCacheListener(); cache.addCacheListener(myListener);
Similar methods exist for removing or querying registered listeners. See the javadocs on the Cache
interface for more details.
Basically any public class can be used as a listener, provided it is annotated with the @CacheListener
annotation. In addition, the class needs to have one or more methods annotated with one of the method-level annotations (in the org.jboss.cache.notifications.annotation
package). Methods annotated as such need to be public, have a void return type, and accept a single parameter of type org.jboss.cache.notifications.event.Event
or one of its subtypes.
@CacheStarted
- methods annotated such receive a notification when the cache is started. Methods need to accept a parameter type which is assignable from CacheStartedEvent
.
@CacheStopped
- methods annotated such receive a notification when the cache is stopped. Methods need to accept a parameter type which is assignable from CacheStoppedEvent
.
@NodeCreated
- methods annotated such receive a notification when a node is created. Methods need to accept a parameter type which is assignable from NodeCreatedEvent
.
@NodeRemoved
- methods annotated such receive a notification when a node is removed. Methods need to accept a parameter type which is assignable from NodeRemovedEvent
.
@NodeModified
- methods annotated such receive a notification when a node is modified. Methods need to accept a parameter type which is assignable from NodeModifiedEvent
.
@NodeMoved
- methods annotated such receive a notification when a node is moved. Methods need to accept a parameter type which is assignable from NodeMovedEvent
.
@NodeVisited
- methods annotated such receive a notification when a node is started. Methods need to accept a parameter type which is assignable from NodeVisitedEvent
.
@NodeLoaded
- methods annotated such receive a notification when a node is loaded from a CacheLoader
. Methods need to accept a parameter type which is assignable from NodeLoadedEvent
.
@NodeEvicted
- methods annotated such receive a notification when a node is evicted from memory. Methods need to accept a parameter type which is assignable from NodeEvictedEvent
.
@NodeActivated
- methods annotated such receive a notification when a node is activated. Methods need to accept a parameter type which is assignable from NodeActivatedEvent
.
@NodePassivated
- methods annotated such receive a notification when a node is passivated. Methods need to accept a parameter type which is assignable from NodePassivatedEvent
.
@TransactionRegistered
- methods annotated such receive a notification when the cache registers a javax.transaction.Synchronization
with a registered transaction manager. Methods need to accept a parameter type which is assignable from TransactionRegisteredEvent
.
@TransactionCompleted
- methods annotated such receive a notification when the cache receives a commit or rollback call from a registered transaction manager. Methods need to accept a parameter type which is assignable from TransactionCompletedEvent
.
@ViewChanged
- methods annotated such receive a notification when the group structure of the cluster changes. Methods need to accept a parameter type which is assignable from ViewChangedEvent
.
@CacheBlocked
- methods annotated such receive a notification when the cluster requests that cache operations are blocked for a state transfer event. Methods need to accept a parameter type which is assignable from CacheBlockedEvent
.
@CacheUnblocked
- methods annotated such receive a notification when the cluster requests that cache operations are unblocked after a state transfer event. Methods need to accept a parameter type which is assignable from CacheUnblockedEvent
.
Refer to the javadocs on the annotations as well as the Event
subtypes for details of what is passed in to your method, and when.
Example:
@CacheListener public class MyListener { @CacheStarted @CacheStopped public void cacheStartStopEvent(Event e) { switch (e.getType()) { case Event.Type.CACHE_STARTED: System.out.println("Cache has started"); break; case Event.Type.CACHE_STOPPED: System.out.println("Cache has stopped"); break; } } @NodeCreated @NodeRemoved @NodeVisited @NodeModified @NodeMoved public void logNodeEvent(NodeEvent ne) { log("An event on node " + ne.getFqn() + " has occured"); } }
Cache loaders are an important part of JBoss Cache. They allow persistence of nodes to disk or to remote cache clusters, and allow for passivation when caches run out of memory. In addition, cache loaders allow JBoss Cache to perform 'warm starts', where in-memory state can be preloaded from persistent storage. JBoss Cache ships with a number of cache loader implementations.
org.jboss.cache.loader.FileCacheLoader
- a basic, filesystem based cache loader that persists data to disk. Non-transactional and not very performant, but a very simple solution. Used mainly for testing and not recommended for production use.
org.jboss.cache.loader.JDBCCacheLoader
- uses a JDBC connection to store data. Connections could be created and maintained in an internal pool (uses the c3p0 pooling library) or from a configured DataSource. The database this CacheLoader connects to could be local or remotely located.
org.jboss.cache.loader.BdbjeCacheLoader
- uses Oracle's BerkeleyDB file-based transactional database to persist data. Transactional and very performant, but potentially restrictive license.
org.jboss.cache.loader.JdbmCacheLoader
- an upcoming open source alternative to the BerkeleyDB.
org.jboss.cache.loader.tcp.TcpCacheLoader
- uses a TCP socket to "persist" data to a remote cluster, using a "far cache" pattern. [1]
org.jboss.cache.loader.ClusteredCacheLoader
- used as a "read-only" CacheLoader, where other nodes in the cluster are queried for state.
These CacheLoaders, along with advanced aspects and tuning issues, are discussed in the chapter dedicated to CacheLoaders .
Eviction policies are the counterpart to CacheLoaders. They are necessary to make sure the cache does not run out of memory and when the cache starts to fill, the eviction algorithm running in a separate thread offloads in-memory state to the CacheLoader and frees up memory. Eviction policies can be configured on a per-region basis, so different subtrees in the cache could have different eviction preferences. JBoss Cache ships with several eviction policies:
org.jboss.cache.eviction.LRUPolicy
- an eviction policy that evicts the least recently used nodes when thresholds are hit.
org.jboss.cache.eviction.LFUPolicy
- an eviction policy that evicts the least frequently used nodes when thresholds are hit.
org.jboss.cache.eviction.MRUPolicy
- an eviction policy that evicts the most recently used nodes when thresholds are hit.
org.jboss.cache.eviction.FIFOPolicy
- an eviction policy that creates a first-in-first-out queue and evicts the oldest nodes when thresholds are hit.
org.jboss.cache.eviction.ExpirationPolicy
- an eviction policy that selects nodes for eviction based on an expiry time each node is configured with.
org.jboss.cache.eviction.ElementSizePolicy
- an eviction policy that selects nodes for eviction based on the number of key/value pairs held in the node.
Detailed configuration and implementing custom eviction policies are discussed in the chapter dedicated to eviction policies. .
The org.jboss.cache.config.Configuration
class (along with its component parts ) is a Java Bean that encapsulates the configuration of the Cache
and all of its architectural elements (cache loaders, evictions policies, etc.)
The Configuration
exposes numerous properties which are summarized in the configuration reference section of this book and many of which are discussed in later chapters. Any time you see a configuration option discussed in this book, you can assume that the Configuration
class or one of its component parts exposes a simple property setter/getter for that configuration option.
As discussed in the User API section , before a Cache
can be created, the CacheFactory
must be provided with a Configuration
object or with a file name or input stream to use to parse a Configuration
from XML. The following sections describe how to accomplish this.
The most convenient way to configure JBoss Cache is via an XML file. The JBoss Cache distribution ships with a number of configuration files for common use cases. It is recommended that these files be used as a starting point, and tweaked to meet specific needs.
Here is a simple example configuration file:
<?xml version="1.0" encoding="UTF-8"?> <!-- ===================================================================== --> <!-- --> <!-- Sample JBoss Cache Service Configuration --> <!-- --> <!-- ===================================================================== --> <server> <mbean code="org.jboss.cache.jmx.CacheJmxWrapper" name="jboss.cache:service=Cache"> <!-- Configure the TransactionManager --> <attribute name="TransactionManagerLookupClass"> org.jboss.cache.transaction.GenericTransactionManagerLookup </attribute> <!-- Node locking level : SERIALIZABLE REPEATABLE_READ (default) READ_COMMITTED READ_UNCOMMITTED NONE --> <attribute name="IsolationLevel">READ_COMMITTED</attribute> <!-- Lock parent before doing node additions/removes --> <attribute name="LockParentForChildInsertRemove">true</attribute> <!-- Valid modes are LOCAL (default) REPL_ASYNC REPL_SYNC INVALIDATION_ASYNC INVALIDATION_SYNC --> <attribute name="CacheMode">LOCAL</attribute> <!-- Max number of milliseconds to wait for a lock acquisition --> <attribute name="LockAcquisitionTimeout">15000</attribute> <!-- Specific eviction policy configurations. This is LRU --> <attribute name="EvictionConfig"> <config> <attribute name="wakeUpIntervalSeconds">5</attribute> <attribute name="policyClass">org.jboss.cache.eviction.LRUPolicy</attribute> <!-- Cache wide default --> <region name="/_default_"> <attribute name="maxNodes">5000</attribute> <attribute name="timeToLiveSeconds">1000</attribute> </region> </config> </attribute> </mbean> </server>
Another, more complete, sample XML file is included in the configuration reference section of this book, along with a handy look-up table explaining the various options.
For historical reasons, the format of the JBoss Cache configuraton file follows that of a JBoss AS Service Archive (SAR) deployment descriptor (and still can be used as such inside JBoss AS ). Because of this dual usage, you may see elements in some configuration files (such as depends
or classpath
) that are not relevant outside JBoss AS. These can safely be ignored.
Here's how you tell the CacheFactory
to create and start a cache by finding and parsing a configuration file on the classpath:
CacheFactory factory = new DefaultCacheFactory(); Cache cache = factory.createCache("cache-configuration.xml");
In addition to the XML-based configuration above, the Configuration
can be built up programatically, using the simple property mutators exposed by Configuration
and its components. When constructed, the Configuration
object is preset with JBoss Cache defaults and can even be used as-is for a quick start.
Following is an example of programatically creating a Configuration
configured to match the one produced by the XML example above, and then using it to create a Cache
:
Configuration config = new Configuration(); String tmlc = GenericTransactionManagerLookup.class.getName(); config.setTransactionManagerLookupClass(tmlc); config.setIsolationLevel(IsolationLevel.READ_COMMITTED); config.setCacheMode(CacheMode.LOCAL); config.setLockParentForChildInsertRemove(true); config.setLockAcquisitionTimeout(15000); EvictionConfig ec = new EvictionConfig(); ec.setWakeupIntervalSeconds(5); ec.setDefaultEvictionPolicyClass(LRUPolicy.class.getName()); EvictionRegionConfig erc = new EvictionRegionConfig(); erc.setRegionName("_default_"); LRUConfiguration lru = new LRUConfiguration(); lru.setMaxNodes(5000); lru.setTimeToLiveSeconds(1000); erc.setEvictionPolicyConfig(lru); List<EvictionRegionConfig> ercs = new ArrayList<EvictionRegionConfig>(); ercs.add(erc); ec.setEvictionRegionConfigs(erc); config.setEvictionConfig(ec); CacheFactory factory = new DefaultCacheFactory(); Cache cache = factory.createCache(config);
Even the above fairly simple configuration is pretty tedious programming; hence the preferred use of XML-based configuration. However, if your application requires it, there is no reason not to use XML-based configuration for most of the attributes, and then access the Configuration
object to programatically change a few items from the defaults, add an eviction region, etc.
Note that configuration values may not be changed programmatically when a cache is running, except those annotated as @Dynamic
. Dynamic properties are also marked as such in the configuration reference table. Attempting to change a non-dynamic property will result in a ConfigurationException
.
The Configuration
class and its component parts are all Java Beans that expose all config elements via simple setters and getters. Therefore, any good IOC framework should be able to build up a Configuration
from an XML file in the framework's own format. See the deployment via the JBoss micrcontainer section for an example of this.
A Configuration
is composed of a number of subobjects:
Following is a brief overview of the components of a Configuration
. See the javadoc and the linked chapters in this book for a more complete explanation of the configurations associated with each component.
Configuration
: top level object in the hierarchy; exposes the configuration properties listed in the configuration reference section of this book.
BuddyReplicationConfig
: only relevant if buddy replication is used. General buddy replication configuration options. Must include a:
BuddyLocatorConfig
: implementation-specific configuration object for the BuddyLocator
implementation being used. What configuration elements are exposed depends on the needs of the BuddyLocator
implementation.
EvictionConfig
: only relevant if eviction is used. General eviction configuration options. Must include at least one:
EvictionRegionConfig
: one for each eviction region; names the region, etc. Must include a:
EvictionPolicyConfig
: implementation-specific configuration object for the EvictionPolicy
implementation being used. What configuration elements are exposed depends on the needs of the EvictionPolicy
implementation.
CacheLoaderConfig
: only relevant if a cache loader is used. General cache loader configuration options. Must include at least one:
IndividualCacheLoaderConfig
: implementation-specific configuration object for the CacheLoader
implementation being used. What configuration elements are exposed depends on the needs of the CacheLoader
implementation.
RuntimeConfig
: exposes to cache clients certain information about the cache's runtime environment (e.g. membership in buddy replication groups if buddy replication is used.) Also allows direct injection into the cache of needed external services like a JTA TransactionManager
or a JGroups ChannelFactory
.
Dynamically changing the configuration of some options while the cache is running is supported, by programmatically obtaining the Configuration
object from the running cache and changing values. E.g.,
Configuration liveConfig = cache.getConfiguration(); liveConfig.setLockAcquisitionTimeout(2000);
A complete listing of which options may be changed dynamically is in the configuration reference section. An org.jboss.cache.config.ConfigurationException
will be thrown if you attempt to change a setting that is not dynamic.
The Option API allows you to override certain behaviours of the cache on a per invocation basis. This involves creating an instance of org.jboss.cache.config.Option
, setting the options you wish to override on the Option
object and passing it in the InvocationContext
before invoking your method on the cache.
E.g., to override the default node versioning used with optimistic locking:
DataVersion v = new MyCustomDataVersion(); cache.getInvocationContext().getOptionOverrides().setDataVersion(v); Node ch = cache.getRoot().addChild(Fqn.fromString("/a/b/c"));
E.g., to suppress replication of a put call in a REPL_SYNC cache:
Node node = cache.getChild(Fqn.fromString("/a/b/c")); cache.getInvocationContext().getOptionOverrides().setLocalOnly(true); node.put("localCounter", new Integer(2));
See the javadocs on the Option
class for details on the options available.
When used in a standalone Java program, all that needs to be done is to instantiate the cache using the CacheFactory
and a Configuration
instance or an XML file, as discussed in the User API and Configuration chapters.
The same techniques can be used when an application running in an application server wishes to programatically deploy a cache rather than relying on an application server's deployment features. An example of this would be a webapp deploying a cache via a javax.servlet.ServletContextListener
.
If, after deploying your cache you wish to expose a management interface to it in JMX, see the section on Programatic Registration in JMX .
If JBoss Cache is run in JBoss AS then the cache can be deployed as an MBean simply by copying a standard cache configuration file to the server's deploy
directory. The standard format of JBoss Cache's standard XML configuration file (as shown in the Configuration Reference ) is the same as a JBoss AS MBean deployment descriptor, so the AS's SAR Deployer has no trouble handling it. Also, you don't have to place the configuration file directly in deploy
; you can package it along with other services or JEE components in a SAR or EAR.
In AS 5, if you're using a server config based on the standard all
config, then that's all you need to do; all required jars will be on the classpath. Otherwise, you will need to ensure jbosscache.jar
and jgroups-all.jar
are on the classpath. You may need to add other jars if you're using things like JdbmCacheLoader
. The simplest way to do this is to copy the jars from the JBoss Cache distribution's lib
directory to the server config's lib
directory. You could also package the jars with the configuration file in Service Archive (.sar) file or an EAR.
It is possible to deploy a JBoss Cache 2.0 instance in JBoss AS 4.x (at least in 4.2.0.GA; other AS releases are completely untested). However, the significant API changes between the JBoss Cache 2.x and 1.x releases mean none of the standard AS 4.x clustering services (e.g. http session replication) that rely on JBoss Cache will work with JBoss Cache 2.x. Also, be aware that usage of JBoss Cache 2.x in AS 4.x is not something the JBoss Cache developers are making any significant effort to test, so be sure to test your application well (which of course you're doing anyway.)
Note in the example the value of the mbean
element's code
attribute: org.jboss.cache.jmx.CacheJmxWrapper
. This is the class JBoss Cache uses to handle JMX integration; the Cache
itself does not expose an MBean interface. See the JBoss Cache MBeans section for more on the CacheJmxWrapper
.
Once your cache is deployed, in order to use it with an in-VM client such as a servlet, a JMX proxy can be used to get a reference to the cache:
MBeanServer server = MBeanServerLocator.locateJBoss(); ObjectName on = new ObjectName("jboss.cache:service=Cache"); CacheJmxWrapperMBean cacheWrapper = (CacheJmxWrapperMBean) MBeanServerInvocationHandler.newProxyInstance(server, on, CacheJmxWrapperMBean.class, false); Cache cache = cacheWrapper.getCache(); Node root = cache.getRoot(); // etc etc
The MBeanServerLocator class is a helper to find the (only) JBoss MBean server inside the current JVM. The javax.management.MBeanServerInvocationHandler
class' newProxyInstance
method creates a dynamic proxy implementing the given interface and uses JMX to dynamically dispatch methods invoked against the generated interface to the MBean. The name used to look up the MBean is the same as defined in the cache's configuration file.
Once the proxy to the CacheJmxWrapper
is obtained, the getCache()
will return a reference to the Cache
itself.
Beginning with AS 5, JBoss AS also supports deployment of POJO services via deployment of a file whose name ends with -beans.xml
. A POJO service is one whose implementation is via a "Plain Old Java Object", meaning a simple java bean that isn't required to implement any special interfaces or extend any particular superclass. A Cache
is a POJO service, and all the components in a Configuration
are also POJOS, so deploying a cache in this way is a natural step.
Deployment of the cache is done using the JBoss Microcontainer that forms the core of JBoss AS. JBoss Microcontainer is a sophisticated IOC framework (similar to Spring). A -beans.xml
file is basically a descriptor that tells the IOC framework how to assemble the various beans that make up a POJO service.
For each configurable option exposed by the Configuration
components, a getter/setter must be defined in the configuration class. This is required so that JBoss Microcontainer can, in typical IOC way, call these methods when the corresponding properties have been configured.
The rules for how to deploy the file, how to package it, how to ensure the required jars are on the classpath, etc. are the same as for a JMX-based deployment .
Following is an example -beans.xml
file. If you look in the server/all/deploy
directory of an AS 5 installation, you can find several more examples.
<?xml version="1.0" encoding="UTF-8"?> <deployment xmlns="urn:jboss:bean-deployer:2.0"> <!-- First we create a Configuration object for the cache --> <bean name="ExampleCacheConfig" class="org.jboss.cache.config.Configuration"> <!-- Externally injected services --> <property name="runtimeConfig"> <bean name="ExampleCacheRuntimeConfig" class="org.jboss.cache.config.RuntimeConfig"> <property name="transactionManager"> <inject bean="jboss:service=TransactionManager" property="TransactionManager"/> </property> <property name="muxChannelFactory"><inject bean="JChannelFactory"/></property> </bean> </property> <property name="multiplexerStack">udp</property> <property name="clusterName">Example-EntityCache</property> <!-- Node locking level : SERIALIZABLE REPEATABLE_READ (default) READ_COMMITTED READ_UNCOMMITTED NONE --> <property name="isolationLevel">REPEATABLE_READ</property> <!-- Valid modes are LOCAL REPL_ASYNC REPL_SYNC --> <property name="cacheMode">REPL_SYNC</property> <!-- The max amount of time (in milliseconds) we wait until the initial state (ie. the contents of the cache) are retrieved from existing members in a clustered environment --> <property name="initialStateRetrievalTimeout">15000</property> <!-- Number of milliseconds to wait until all responses for a synchronous call have been received. --> <property name="syncReplTimeout">20000</property> <!-- Max number of milliseconds to wait for a lock acquisition --> <property name="lockAcquisitionTimeout">15000</property> <property name="exposeManagementStatistics">true</property> <!-- Must be true if any entity deployment uses a scoped classloader --> <property name="useRegionBasedMarshalling">true</property> <!-- Must match the value of "useRegionBasedMarshalling" --> <property name="inactiveOnStartup">true</property> <!-- Specific eviction policy configurations. This is LRU --> <property name="evictionConfig"> <bean name="ExampleEvictionConfig" class="org.jboss.cache.config.EvictionConfig"> <property name="defaultEvictionPolicyClass"> org.jboss.cache.eviction.LRUPolicy </property> <property name="wakeupIntervalSeconds">5</property> <property name="evictionRegionConfigs"> <list> <bean name="ExampleDefaultEvictionRegionConfig" class="org.jboss.cache.config.EvictionRegionConfig"> <property name="regionName">/_default_</property> <property name="evictionPolicyConfig"> <bean name="ExampleDefaultLRUConfig" class="org.jboss.cache.eviction.LRUConfiguration"> <property name="maxNodes">5000</property> <property name="timeToLiveSeconds">1000</property> </bean> </property> </bean> </list> </property> </bean> </property> </bean> <!-- Factory to build the Cache. --> <bean name="DefaultCacheFactory" class="org.jboss.cache.DefaultCacheFactory"> <constructor factoryClass="org.jboss.cache.DefaultCacheFactory" factoryMethod="getInstance"/> </bean> <!-- The cache itself --> <bean name="ExampleCache" class="org.jboss.cache.Cache"> <constructor factoryMethod="createCache"> <factory bean="DefaultCacheFactory"/> <parameter class="org.jboss.cache.config.Configuration"><inject bean="ExampleCacheConfig"/></parameter> <parameter class="boolean">false</false> </constructor> </bean> </deployment>
See the JBoss Microcontainer documentation [2] for details on the above syntax. Basically, each bean
element represents an object; most going to create a Configuration
and its constituent parts .
An interesting thing to note in the above example is the use of the RuntimeConfig
object. External resources like a TransactionManager
and a JGroups ChannelFactory
that are visible to the microcontainer are dependency injected into the RuntimeConfig
. The assumption here is that in some other deployment descriptor in the AS, the referenced beans have been described.
With the 1.x JBoss Cache releases, a proxy to the cache could be bound into JBoss AS's JNDI tree using the AS's JRMPProxyFactory
service. With JBoss Cache 2.x, this no longer works. An alternative way of doing a similar thing with a POJO (i.e. non-JMX-based) service like a Cache
is under development by the JBoss AS team [3] . That feature is not available as of the time of this writing, although it will be completed before AS 5.0.0.GA is released. We will add a wiki page describing how to use it once it becomes available.
JBoss Cache includes JMX MBeans to expose cache functionality and provide statistics that can be used to analyze cache operations. JBoss Cache can also broadcast cache events as MBean notifications for handling via JMX monitoring tools.
JBoss Cache provides an MBean that can be registered with your environments JMX server to allow access to the cache instance via JMX. This MBean is the org.jboss.cache.jmx.CacheJmxWrapper
. It is a StandardMBean, so it's MBean interface is org.jboss.cache.jmx.CacheJmxWrapperMBean
. This MBean can be used to:
Get a reference to the underlying Cache
.
Invoke create/start/stop/destroy lifecycle operations on the underlying Cache
.
Inspect various details about the cache's current state (number of nodes, lock information, etc.)
See numerous details about the cache's configuration, and change those configuration items that can be changed when the cache has already been started.
See the CacheJmxWrapperMBean
javadoc for more details.
It is important to note a significant architectural difference between JBoss Cache 1.x and 2.x. In 1.x, the old TreeCache
class was itself an MBean, and essentially exposed the cache's entire API via JMX. In 2.x, JMX has been returned to it's fundamental role as a management layer. The Cache
object itself is completely unaware of JMX; instead JMX functionality is added through a wrapper class designed for that purpose. Furthermore, the interface exposed through JMX has been limited to management functions; the general Cache
API is no longer exposed through JMX. For example, it is no longer possible to invoke a cache put
or get
via the JMX interface.
If a CacheJmxWrapper
is registered, JBoss Cache also provides MBeans for each interceptor configured in the cache's interceptor stack. These MBeans are used to capture and expose statistics related to cache operations. They are hierarchically associated with the CacheJmxWrapper
MBean and have service names that reflect this relationship. For example, a replication interceptor MBean for the jboss.cache:service=TomcatClusteringCache
instance will be accessible through the service named jboss.cache:service=TomcatClusteringCache,cache-interceptor=ReplicationInterceptor
.
The best way to ensure the CacheJmxWrapper
is registered in JMX depends on how you are deploying your cache:
Simplest way to do this is to create your Cache
and pass it to the CacheJmxWrapper
constructor.
CacheFactory factory = new DefaultCacheFactory(); // Build but don't start the cache // (although it would work OK if we started it) Cache cache = factory.createCache("cache-configuration.xml", false); CacheJmxWrapperMBean wrapper = new CacheJmxWrapper(cache); MBeanServer server = getMBeanServer(); // however you do it ObjectName on = new ObjectName("jboss.cache:service=TreeCache"); server.registerMBean(wrapper, on); // Invoking lifecycle methods on the wrapper results // in a call through to the cache wrapper.create(); wrapper.start(); ... use the cache ... on application shutdown // Invoking lifecycle methods on the wrapper results // in a call through to the cache wrapper.stop(); wrapper.destroy();
Alternatively, build a Configuration
object and pass it to the CacheJmxWrapper
. The wrapper will construct the Cache
:
Configuration config = buildConfiguration(); // whatever it does CacheJmxWrapperMBean wrapper = new CacheJmxWrapper(config); MBeanServer server = getMBeanServer(); // however you do it ObjectName on = new ObjectName("jboss.cache:service=TreeCache"); server.registerMBean(wrapper, on); // Call to wrapper.create() will build the Cache if one wasn't injected wrapper.create(); wrapper.start(); // Now that it's built, created and started, get the cache from the wrapper Cache cache = wrapper.getCache(); ... use the cache ... on application shutdown wrapper.stop(); wrapper.destroy();
When you deploy your cache in JBoss AS using a -service.xml file , a CacheJmxWrapper
is automatically registered. There is no need to do anything further. The CacheJmxWrapper
is accessible from an MBean server through the service name specified in the cache configuration file's mbean
element.
CacheJmxWrapper
is a POJO, so the microcontainer has no problem creating one. The trick is getting it to register your bean in JMX. This can be done by specifying the org.jboss.aop.microcontainer.aspects.jmx.JMX
annotation on the CacheJmxWrapper
bean:
<?xml version="1.0" encoding="UTF-8"?> <deployment xmlns="urn:jboss:bean-deployer:2.0"> <!-- First we create a Configuration object for the cache --> <bean name="ExampleCacheConfig" class="org.jboss.cache.config.Configuration"> ... build up the Configuration </bean> <!-- Factory to build the Cache. --> <bean name="DefaultCacheFactory" class="org.jboss.cache.DefaultCacheFactory"> <constructor factoryClass="org.jboss.cache.DefaultCacheFactory" factoryMethod="getInstance"/> </bean> <!-- The cache itself --> <bean name="ExampleCache" class="org.jboss.cache.CacheImpl"> <constructor factoryMethod="createnewInstance"> <factory bean="DefaultCacheFactory"/> <parameter><inject bean="ExampleCacheConfig"/></parameter> <parameter>false</false> </constructor> </bean> <!-- JMX Management --> <bean name="ExampleCacheJmxWrapper" class="org.jboss.cache.jmx.CacheJmxWrapper"> <annotation>@org.jboss.aop.microcontainer.aspects.jmx.JMX(name="jboss.cache:service=ExampleTreeCache", exposedInterface=org.jboss.cache.jmx.CacheJmxWrapperMBean.class, registerDirectly=true)</annotation> <constructor> <parameter><inject bean="ExampleCache"/></parameter> </constructor> </bean> </deployment>
As discussed in the Programatic Registration section, CacheJmxWrapper
can do the work of building, creating and starting the Cache
if it is provided with a Configuration
. With the microcontainer, this is the preferred approach, as it saves the boilerplate XML needed to create the CacheFactory
:
<?xml version="1.0" encoding="UTF-8"?> <deployment xmlns="urn:jboss:bean-deployer:2.0"> <!-- First we create a Configuration object for the cache --> <bean name="ExampleCacheConfig" class="org.jboss.cache.config.Configuration"> ... build up the Configuration </bean> <bean name="ExampleCache" class="org.jboss.cache.jmx.CacheJmxWrapper"> <annotation>@org.jboss.aop.microcontainer.aspects.jmx.JMX(name="jboss.cache:service=ExampleTreeCache", exposedInterface=org.jboss.cache.jmx.CacheJmxWrapperMBean.class, registerDirectly=true)</annotation> <constructor> <parameter><inject bean="ExampleCacheConfig"/></parameter> </constructor> </bean> </deployment>
JBoss Cache captures statistics in its interceptors and exposes the statistics through interceptor MBeans. Gathering of statistics is enabled by default; this can be disabled for a specific cache instance through the ExposeManagementStatistics
configuration attribute. Note that the majority of the statistics are provided by the CacheMgmtInterceptor
, so this MBean is the most significant in this regard. If you want to disable all statistics for performance reasons, you set ExposeManagementStatistics
to false
as this will prevent the CacheMgmtInterceptor
from being included in the cache's interceptor stack when the cache is started.
If a CacheJmxWrapper
is registered with JMX, the wrapper also ensures that an MBean is registered in JMX for each interceptor that exposes statistics [4] . Management tools can then access those MBeans to examine the statistics. See the section in the JMX Reference chapter pertaining to the statistics that are made available via JMX.
The name under which the interceptor MBeans will be registered is derived by taking the ObjectName
under which the CacheJmxWrapper
is registered and adding a cache-interceptor
attribute key whose value is the non-qualified name of the interceptor class. So, for example, if the CacheJmxWrapper
were registered under jboss.cache:service=TreeCache
, the name of the CacheMgmtInterceptor
MBean would be jboss.cache:service=TreeCache,cache-interceptor=CacheMgmtInterceptor
.
Each interceptor's MBean exposes a StatisticsEnabled
attribute that can be used to disable maintenance of statistics for that interceptor. In addition, each interceptor MBean provides the following common operations and attributes.
dumpStatistics
- returns a Map
containing the interceptor's attributes and values.
resetStatistics
- resets all statistics maintained by the interceptor.
setStatisticsEnabled(boolean)
- allows statistics to be disabled for a specific interceptor.
JBoss Cache users can register a listener to receive cache events described earlier in the User API chapter. Users can alternatively utilize the cache's management information infrastructure to receive these events via JMX notifications. Cache events are accessible as notifications by registering a NotificationListener
for the CacheJmxWrapper
.
See the section in the JMX Reference chapter pertaining to JMX notifications for a list of notifications that can be received through the CacheJmxWrapper
.
The following is an example of how to programmatically receive cache notifications when running in a JBoss AS environment. In this example, the client uses a filter to specify which events are of interest.
MyListener listener = new MyListener(); NotificationFilterSupport filter = null; // get reference to MBean server Context ic = new InitialContext(); MBeanServerConnection server = (MBeanServerConnection)ic.lookup("jmx/invoker/RMIAdaptor"); // get reference to CacheMgmtInterceptor MBean String cache_service = "jboss.cache:service=TomcatClusteringCache"; ObjectName mgmt_name = new ObjectName(cache_service); // configure a filter to only receive node created and removed events filter = new NotificationFilterSupport(); filter.disableAllTypes(); filter.enableType(CacheNotificationBroadcaster.NOTIF_NODE_CREATED); filter.enableType(CacheNotificationBroadcaster.NOTIF_NODE_REMOVED); // register the listener with a filter // leave the filter null to receive all cache events server.addNotificationListener(mgmt_name, listener, filter, null); // ... // on completion of processing, unregister the listener server.removeNotificationListener(mgmt_name, listener, filter, null);
The following is the simple notification listener implementation used in the previous example.
private class MyListener implements NotificationListener, Serializable { public void handleNotification(Notification notification, Object handback) { String message = notification.getMessage(); String type = notification.getType(); Object userData = notification.getUserData(); System.out.println(type + ": " + message); if (userData == null) { System.out.println("notification data is null"); } else if (userData instanceof String) { System.out.println("notification data: " + (String) userData); } else if (userData instanceof Object[]) { Object[] ud = (Object[]) userData; for (Object data : ud) { System.out.println("notification data: " + data.toString()); } } else { System.out.println("notification data class: " + userData.getClass().getName()); } } }
Note that the JBoss Cache management implementation only listens to cache events after a client registers to receive MBean notifications. As soon as no clients are registered for notifications, the MBean will remove itself as a cache listener.
JBoss Cache MBeans are easily accessed when running cache instances in an application server that provides an MBean server interface such as JBoss JMX Console. Refer to your server documentation for instructions on how to access MBeans running in a server's MBean container.
In addition, though, JBoss Cache MBeans are also accessible when running in a non-server environment if the JVM is JDK 5.0 or later. When running a standalone cache in a JDK 5.0 environment, you can access the cache's MBeans as follows.
Set the system property -Dcom.sun.management.jmxremote
when starting the JVM where the cache will run.
Once the JVM is running, start the JDK 5.0 jconsole
utility, located in your JDK's /bin
directory.
When the utility loads, you will be able to select your running JVM and connect to it. The JBoss Cache MBeans will be available on the MBeans panel.
Note that the jconsole
utility will automatically register as a listener for cache notifications when connected to a JVM running JBoss Cache instances.
The following figure shows cache interceptor MBeans in jconsole
. Cache statistics are displayed for the CacheMgmtInterceptor
:
[2] http://labs.jboss.com/jbossmc/docs
[3] http://jira.jboss.com/jira/browse/JBAS-4456
[4]
Note that if the CacheJmxWrapper
is not registered in JMX, the interceptor MBeans will not be registered either. The JBoss Cache 1.4 releases included code that would try to "discover" an MBeanServer
and automatically register the interceptor MBeans with it. For JBoss Cache 2.x we decided that this sort of "discovery" of the JMX environment was beyond the proper scope of a caching library, so we removed this functionality.
Within a major version, releases of JBoss Cache are meant to be compatible and interoperable. Compatible in the sense that it should be possible to upgrade an application from one version to another by simply replacing the jars. Interoperable in the sense that if two different versions of JBoss Cache are used in the same cluster, they should be able to exchange replication and state transfer messages. Note however that interoperability requires use of the same JGroups version in all nodes in the cluster. In most cases, the version of JGroups used by a version of JBoss Cache can be upgraded.
As such, JBoss Cache 2.x.x is not API or binary compatible with prior 1.x.x versions. However, JBoss Cache 2.1.x will be API and binary compatible with 2.0.x.
A configuration attribute, ReplicationVersion
, is available and is used to control the wire format of inter-cache communications. They can be wound back from more efficient and newer protocols to "compatible" versions when talking to older releases. This mechanism allows us to improve JBoss Cache by using more efficient wire formats while still providing a means to preserve interoperability.
A compatibility matrix is maintained on the JBoss Cache website, which contains information on different versions of JBoss Cache, JGroups and JBoss AS.
This section digs deeper into the JBoss Cache architecture, and is meant for developers wishing to extend or enhance JBoss Cache, write plugins or are just looking for detailed knowledge of how things work under the hood.
Table of Contents
A Cache
consists of a collection of Node
instances, organised in a tree structure. Each Node
contains a Map
which holds the data objects to be cached. It is important to note that the structure is a mathematical tree, and not a graph; each Node
has one and only one parent, and the root node is denoted by the constant fully qualitied name, Fqn.ROOT
.
The reason for organising nodes as such is to improve concurrent access to data and make replication and persistence more fine-grained.
In the diagram above, each box represents a JVM. You see 2 caches in separate JVMs, replicating data to each other. These VMs can be located on the same physical machine, or on 2 different machines connected by a network link. The underlying group communication between networked nodes is done using JGroups .
Any modifications (see API chapter ) in one cache instance will be replicated to the other cache. Naturally, you can have more than 2 caches in a cluster. Depending on the transactional settings, this replication will occur either after each modification or at the end of a transaction, at commit time. When a new cache is created, it can optionally acquire the contents from one of the existing caches on startup.
In addition to Cache
and Node
interfaces, JBoss Cache exposes more powerful CacheSPI
and NodeSPI
interfaces, which offer more control over the internals of JBoss Cache. These interfaces are not intended for general use, but are designed for people who wish to extend and enhance JBoss Cache, or write custom Interceptor
or CacheLoader
instances.
The CacheSPI
interface cannot be created, but is injected into Interceptor
and CacheLoader
implementations by the setCache(CacheSPI cache)
methods on these interfaces. CacheSPI
extends Cache
so all the functionality of the basic API is made available.
Similarly, a NodeSPI
interface cannot be created. Instead, one is obtained by performing operations on CacheSPI
, obtained as above. For example, Cache.getRoot() : Node
is overridden as CacheSPI.getRoot() : NodeSPI
.
It is important to note that directly casting a Cache
or Node
to it's SPI counterpart is not recommended and is bad practice, since the inheritace of interfaces it is not a contract that is guaranteed to be upheld moving forward. The exposed public APIs, on the other hand, is guaranteed to be upheld.
Since the cache is essentially a collection of nodes, aspects such as clustering, persistence, eviction, etc. need to be applied to these nodes when operations are invoked on the cache as a whole or on individual nodes. To achieve this in a clean, modular and extensible manner, an interceptor chain is used. The chain is built up of a series of interceptors, each one adding an aspect or particular functionality. The chain is built when the cache is created, based on the configuration used.
It is important to note that the NodeSPI
offers some methods (such as the xxxDirect()
method family) that operate on a node directly without passing through the interceptor stack. Plugin authors should note that using such methods will affect the aspects of the cache that may need to be applied, such as locking, replication, etc. Basically, don't use such methods unless you really know what you're doing!
An Interceptor
is an abstract class, several of which comprise an interceptor chain. It exposes an invoke()
method, which must be overridden by implementing classes to add behaviour to a call before passing the call down the chain by calling super.invoke()
.
JBoss Cache ships with several interceptors, representing different configuration options, some of which are:
TxInterceptor
- looks for ongoing transactions and registers with transaction managers to participate in synchronization events
ReplicationInterceptor
- replicates state across a cluster using a JGroups channel
CacheLoaderInterceptor
- loads data from a persistent store if the data requested is not available in memory
The interceptor chain configured for your cache instance can be obtained and inspected by calling CacheSPI.getInterceptorChain()
, which returns an ordered List
of interceptors.
Custom interceptors to add specific aspects or features can be written by extending Interceptor
and overriding invoke()
. The custom interceptor will need to be added to the interceptor chain by using the CacheSPI.addInterceptor()
method.
Adding custom interceptors via XML is not supported at this time.
org.jboss.cache.marshall.MethodCall
is a class that encapsulates a java.lang.reflection.Method
and an Object[]
representing the method's arguments. It is an extension of the org.jgroups.blocks.MethodCall
class, that adds a mechanism for identifying known methods using magic numbers and method ids, which makes marshalling and unmarshalling more efficient and performant.
This is central to the Interceptor
architecture, and is the only parameter passed in to Interceptor.invoke()
.
InvocationContext
holds intermediate state for the duration of a single invocation, and is set up and destroyed by the InvocationContextInterceptor
which sits at the start of the chain.
InvocationContext
, as its name implies, holds contextual information associated with a single cache method invocation. Contextual information includes associated javax.transaction.Transaction
or org.jboss.cache.transaction.GlobalTransaction
, method invocation origin ( InvocationContext.isOriginLocal()
) as well as Option
overrides .
The InvocationContext
can be obtained by calling Cache.getInvocationContext()
.
Some aspects and functionality is shared by more than a single interceptor. Some of these have been encapsulated into managers, for use by various interceptors, and are made available by the CacheSPI
interface.
This class is responsible for calls made via the JGroups channel for all RPC calls to remote caches, and encapsulates the JGroups channel used.
This class manages buddy groups and invokes group organisation remote calls to organise a cluster of caches into smaller sub-groups.
Early versions of JBoss Cache simply wrote cached data to the network by writing to an ObjectOutputStream
during replication. Over various releases in the JBoss Cache 1.x.x series this approach was gradually deprecated in favour of a more mature marshalling framework. In the JBoss Cache 2.x.x series, this is the only officially supported and recommended mechanism for writing objects to datastreams.
The Marshaller
interface extends RpcDispatcher.Marshaller
from JGroups. This interface has two main implementations - a delegating VersionAwareMarshaller
and a concrete CacheMarshaller200
.
The marshaller can be obtained by calling CacheSPI.getMarshaller()
, and defaults to the VersionAwareMarshaller
. Users may also write their own marshallers by implementing the Marshaller
interface and adding it to their configuration, by using the MarshallerClass
configuration attribute.
As the name suggests, this marshaller adds a version short
to the start of any stream when writing, enabling similar VersionAwareMarshaller
instances to read the version short and know which specific marshaller implementation to delegate the call to. For example, CacheMarshaller200
, is the marshaller for JBoss Cache 2.0.x. JBoss Cache 2.1.x, say, may ship with CacheMarshaller210
with an improved wire protocol. Using a VersionAwareMarshaller
helps achieve wire protocol compatibility between minor releases but still affords us the flexibility to tweak and improve the wire protocol between minor or micro releases.
This marshaller treats well-known objects that need marshalling - such as MethodCall
, Fqn
, DataVersion
, and even some JDK objects such as String
, List
, Boolean
and others as types that do not need complete class definitions. Instead, each of these well-known types are represented by a short
, which is a lot more efficient.
In addition, reference counting is done to reduce duplication of writing certain objects multiple times, to help keep the streams small and efficient.
Also, if UseRegionBasedMarshalling
is enabled (disabled by default) the marshaller adds region information to the stream before writing any data. This region information is in the form of a String
representation of an Fqn
. When unmarshalling, the RegionManager
can be used to find the relevant Region
, and use a region-specific ClassLoader
to unmarshall the stream. This is specifically useful when used to cluster state for application servers, where each deployment has it's own ClassLoader
. See the section below on regions for more information.
When used to cluster state of application servers, applications deployed in the application tend to put instances of objects specific to their application in the cache (or in an HttpSession
object) which would require replication. It is common for application servers to assign separate ClassLoader
instances to each application deployed, but have JBoss Cache libraries referenced by the application server's ClassLoader
.
To enable us to successfully marshall and unmarshall objects from such class loaders, we use a concept called regions. A region is a portion of the cache which share a common class loader (a region also has other uses - see eviction policies ).
A region is created by using the Cache.getRegion(Fqn fqn, boolean createIfNotExists)
method, and returns an implementation of the Region
interface. Once a region is obtained, a class loader for the region can be set or unset, and the region can be activated/deactivated. By default, regions are active unless the InactiveOnStartup
configuration attribute is set to true
.
This chapter talks about aspects around clustering JBoss Cache.
JBoss Cache can be configured to be either local (standalone) or clustered. If in a cluster, the cache can be configured to replicate changes, or to invalidate changes. A detailed discussion on this follows.
Local caches don't join a cluster and don't communicate with other caches in a cluster. Therefore their elements don't need to be serializable - however, we recommend making them serializable, enabling a user to change the cache mode at any time. The dependency on the JGroups library is still there, although a JGroups channel is not started.
Replicated caches replicate all changes to some or all of the other cache instances in the cluster. Replication can either happen after each modification (no transactions), or at the end of a transaction (commit time).
Replication can be synchronous or asynchronous . Use of either one of the options is application dependent. Synchronous replication blocks the caller (e.g. on a put()
) until the modifications have been replicated successfully to all nodes in a cluster. Asynchronous replication performs replication in the background (the put()
returns immediately). JBoss Cache also offers a replication queue, where modifications are replicated periodically (i.e. interval-based), or when the queue size exceeds a number of elements, or a combination thereof.
Asynchronous replication is faster (no caller blocking), because synchronous replication requires acknowledgments from all nodes in a cluster that they received and applied the modification successfully (round-trip time). However, when a synchronous replication returns successfully, the caller knows for sure that all modifications have been applied to all cache instances, whereas this is not be the case with asynchronous replication. With asynchronous replication, errors are simply written to a log. Even when using transactions, a transaction may succeed but replication may not succeed on all cache instances.
When using transactions, replication only occurs at the transaction boundary - i.e., when a transaction commits. This results in minimising replication traffic since a single modification is broadcast rather than a series of individual modifications, and can be a lot more efficient than not using transactions. Another effect of this is that if a transaction were to roll back, nothing is broadcast across a cluster.
Depending on whether you are running your cluster in asynchronous or synchronous mode, JBoss Cache will use either a single phase or two phase commit protocol, respectively.
Used when your cache mode is REPL_ASYNC. All modifications are replicated in a single call, which instructs remote caches to apply the changes to their local in-memory state and commit locally. Remote errors/rollbacks are never fed back to the originator of the transaction since the communication is asynchronous.
Used when your cache mode is REPL_SYNC. Upon committing your transaction, JBoss Cache broadcasts a prepare call, which carries all modifications relevant to the transaction. Remote caches then acquire local locks on their in-memory state and apply the modifications. Once all remote caches respond to the prepare call, the originator of the transaction broadcasts a commit. This instructs all remote caches to commit their data. If any of the caches fail to respond to the prepare phase, the originator broadcasts a rollback.
Note that although the prepare phase is synchronous, the commit and rollback phases are asynchronous. This is because Sun's JTA specification does not specify how transactional resources should deal with failures at this stage of a transaction; and other resources participating in the transaction may have indeterminate state anyway. As such, we do away with the overhead of synchronous communication for this phase of the transaction. That said, they can be forced to be synchronous using the SyncCommitPhase
and SyncRollbackPhase
configuration attributes.
Buddy Replication allows you to suppress replicating your data to all instances in a cluster. Instead, each instance picks one or more 'buddies' in the cluster, and only replicates to these specific buddies. This greatly helps scalability as there is no longer a memory and network traffic impact every time another instance is added to a cluster.
One of the most common use cases of Buddy Replication is when a replicated cache is used by a servlet container to store HTTP session data. One of the pre-requisites to buddy replication working well and being a real benefit is the use of session affinity , more casually known as sticky sessions in HTTP session replication speak. What this means is that if certain data is frequently accessed, it is desirable that this is always accessed on one instance rather than in a round-robin fashion as this helps the cache cluster optimise how it chooses buddies, where it stores data, and minimises replication traffic.
If this is not possible, Buddy Replication may prove to be more of an overhead than a benefit.
Buddy Replication uses an instance of a BuddyLocator
which contains the logic used to select buddies in a network. JBoss Cache currently ships with a single implementation, NextMemberBuddyLocator
, which is used as a default if no implementation is provided. The NextMemberBuddyLocator
selects the next member in the cluster, as the name suggests, and guarantees an even spread of buddies for each instance.
The NextMemberBuddyLocator
takes in 2 parameters, both optional.
numBuddies
- specifies how many buddies each instance should pick to back its data onto. This defaults to 1.
ignoreColocatedBuddies
- means that each instance will try to select a buddy on a different physical host. If not able to do so though, it will fall back to colocated instances. This defaults to true
.
Also known as replication groups , a buddy pool is an optional construct where each instance in a cluster may be configured with a buddy pool name. Think of this as an 'exclusive club membership' where when selecting buddies, BuddyLocator
s that support buddy pools would try and select buddies sharing the same buddy pool name. This allows system administrators a degree of flexibility and control over how buddies are selected. For example, a sysadmin may put two instances on two separate physical servers that may be on two separate physical racks in the same buddy pool. So rather than picking an instance on a different host on the same rack, BuddyLocator
s would rather pick the instance in the same buddy pool, on a separate rack which may add a degree of redundancy.
In the unfortunate event of an instance crashing, it is assumed that the client connecting to the cache (directly or indirectly, via some other service such as HTTP session replication) is able to redirect the request to any other random cache instance in the cluster. This is where a concept of Data Gravitation comes in.
Data Gravitation is a concept where if a request is made on a cache in the cluster and the cache does not contain this information, it asks other instances in the cluster for the data. In other words, data is lazily transferred, migrating only when other nodes ask for it. This strategy prevents a network storm effect where lots of data is pushed around healthy nodes because only one (or a few) of them die.
If the data is not found in the primary section of some node, it would (optionally) ask other instances to check in the backup data they store for other caches. This means that even if a cache containing your session dies, other instances will still be able to access this data by asking the cluster to search through their backups for this data.
Once located, this data is transferred to the instance which requested it and is added to this instance's data tree. The data is then (optionally) removed from all other instances (and backups) so that if session affinity is used, the affinity should now be to this new cache instance which has just taken ownership of this data.
Data Gravitation is implemented as an interceptor. The following (all optional) configuration properties pertain to data gravitation.
dataGravitationRemoveOnFind
- forces all remote caches that own the data or hold backups for the data to remove that data, thereby making the requesting cache the new data owner. This removal, of course, only happens after the new owner finishes replicating data to its buddy. If set to false
an evict is broadcast instead of a remove, so any state persisted in cache loaders will remain. This is useful if you have a shared cache loader configured. Defaults to true
.
dataGravitationSearchBackupTrees
- Asks remote instances to search through their backups as well as main data trees. Defaults to true
. The resulting effect is that if this is true
then backup nodes can respond to data gravitation requests in addition to data owners.
autoDataGravitation
- Whether data gravitation occurs for every cache miss. By default this is set to false
to prevent unnecessary network calls. Most use cases will know when it may need to gravitate data and will pass in an Option
to enable data gravitation on a per-invocation basis. If autoDataGravitation
is true
this Option
is unnecessary.
<!-- Buddy Replication config --> <attribute name="BuddyReplicationConfig"> <config> <!-- Enables buddy replication. This is the ONLY mandatory configuration element here. --> <buddyReplicationEnabled>true</buddyReplicationEnabled> <!-- These are the default values anyway --> <buddyLocatorClass>org.jboss.cache.buddyreplication.NextMemberBuddyLocator</buddyLocatorClass> <!-- numBuddies is the number of backup nodes each node maintains. ignoreColocatedBuddies means that each node will *try* to select a buddy on a different physical host. If not able to do so though, it will fall back to colocated nodes. --> <buddyLocatorProperties> numBuddies = 1 ignoreColocatedBuddies = true </buddyLocatorProperties> <!-- A way to specify a preferred replication group. If specified, we try and pick a buddy which shares the same pool name (falling back to other buddies if not available). This allows the sysdmin to hint at backup buddies are picked, so for example, nodes may be hinted topick buddies on a different physical rack or power supply for added fault tolerance. --> <buddyPoolName>myBuddyPoolReplicationGroup</buddyPoolName> <!-- Communication timeout for inter-buddy group organisation messages (such as assigning to and removing from groups, defaults to 1000. --> <buddyCommunicationTimeout>2000</buddyCommunicationTimeout> <!-- Whether data is removed from old owners when gravitated to a new owner. Defaults to true. --> <dataGravitationRemoveOnFind>true</dataGravitationRemoveOnFind> <!-- Whether backup nodes can respond to data gravitation requests, or only the data owner is supposed to respond. Defaults to true. --> <dataGravitationSearchBackupTrees>true</dataGravitationSearchBackupTrees> <!-- Whether all cache misses result in a data gravitation request. Defaults to false, requiring callers to enable data gravitation on a per-invocation basis using the Options API. --> <autoDataGravitation>false</autoDataGravitation> </config> </attribute>
If a cache is configured for invalidation rather than replication, every time data is changed in a cache other caches in the cluster receive a message informing them that their data is now stale and should be evicted from memory. Invalidation, when used with a shared cache loader (see chapter on Cache Loaders) would cause remote caches to refer to the shared cache loader to retrieve modified data. The benefit of this is twofold: network traffic is minimised as invalidation messages are very small compared to replicating updated data, and also that other caches in the cluster look up modified data in a lazy manner, only when needed.
Invalidation messages are sent after each modification (no transactions), or at the end of a transaction, upon successful commit. This is usually more efficient as invalidation messages can be optimised for the transaction as a whole rather than on a per-modification basis.
Invalidation too can be synchronous or asynchronous, and just as in the case of replication, synchronous invalidation blocks until all caches in the cluster receive invalidation messages and have evicted stale data while asynchronous invalidation works in a 'fire-and-forget' mode, where invalidation messages are broadcast but doesn't block and wait for responses.
State Transfer refers to the process by which a JBoss Cache instance prepares itself to begin providing a service by acquiring the current state from another cache instance and integrating that state into its own state.
There are three divisions of state transfer types depending on a point of view related to state transfer. First, in the context of particular state transfer implementation, the underlying plumbing, there are two starkly different state transfer types: byte array and streaming based state transfer. Second, state transfer can be full or partial state transfer depending on a subtree being transferred. Entire cache tree transfer represents full transfer while transfer of a particular subtree represents partial state transfer. And finally state transfer can be "in-memory" and "persistent" transfer depending on a particular use of cache.
Byte array based transfer was a default and only transfer methodology for cache in all previous releases up to 2.0. Byte array based transfer loads entire state transferred into a byte array and sends it to a state receiving member. Major limitation of this approach is that the state transfer that is very large (>1GB) would likely result in OutOfMemoryException. Streaming state transfer provides an InputStream to a state reader and an OutputStream to a state writer. OutputStream and InputStream abstractions enable state transfer in byte chunks thus resulting in smaller memory requirements. For example, if application state is represented as a tree whose aggregate size is 1GB, rather than having to provide a 1GB byte array streaming state transfer transfers the state in chunks of N bytes where N is user configurable.
Byte array and streaming based state transfer are completely API transparent, interchangeable, and statically configured through a standard cache configuration XML file. Refer to JGroups documentation on how to change from one type of transfer to another.
If either in-memory or persistent state transfer is enabled, a full or partial state transfer will be done at various times, depending on how the cache is used. "Full" state transfer refers to the transfer of the state related to the entire tree -- i.e. the root node and all nodes below it. A "partial" state transfer is one where just a portion of the tree is transferred -- i.e. a node at a given Fqn and all nodes below it.
If either in-memory or persistent state transfer is enabled, state transfer will occur at the following times:
Initial state transfer. This occurs when the cache is first started (as part of the processing of the start()
method). This is a full state transfer. The state is retrieved from the cache instance that has been operational the longest. [5] If there is any problem receiving or integrating the state, the cache will not start.
Initial state transfer will occur unless:
The cache's InactiveOnStartup
property is true
. This property is used in conjunction with region-based marshalling.
Buddy replication is used. See below for more on state transfer with buddy replication.
Partial state transfer following region activation. When region-based marshalling is used, the application needs to register a specific class loader with the cache. This class loader is used to unmarshall the state for a specific region (subtree) of the cache.
After registration, the application calls cache.getRegion(fqn, true).activate()
, which initiates a partial state transfer of the relevant subtree's state. The request is first made to the oldest cache instance in the cluster. However, if that instance responds with no state, it is then requested from each instance in turn until one either provides state or all instances have been queried.
Typically when region-based marshalling is used, the cache's InactiveOnStartup
property is set to true
. This suppresses initial state transfer, which would fail due to the inability to deserialize the transferred state.
Buddy replication. When buddy replication is used, initial state transfer is disabled. Instead, when a cache instance joins the cluster, it becomes the buddy of one or more other instances, and one or more other instances become its buddy. Each time an instance determines it has a new buddy providing backup for it, it pushes it's current state to the new buddy. This "pushing" of state to the new buddy is slightly different from other forms of state transfer, which are based on a "pull" approach (i.e. recipient asks for and receives state). However, the process of preparing and integrating the state is the same.
This "push" of state upon buddy group formation only occurs if the InactiveOnStartup
property is set to false
. If it is true
, state transfer amongst the buddies only occurs when the application activates the region on the various members of the group.
Partial state transfer following a region activation call is slightly different in the buddy replication case as well. Instead of requesting the partial state from one cache instance, and trying all instances until one responds, with buddy replication the instance that is activating a region will request partial state from each instance for which it is serving as a backup.
The state that is acquired and integrated can consist of two basic types:
"Transient" or "in-memory" state. This consists of the actual in-memory state of another cache instance - the contents of the various in-memory nodes in the cache that is providing state are serialized and transferred; the recipient deserializes the data, creates corresponding nodes in its own in-memory tree, and populates them with the transferred data.
"In-memory" state transfer is enabled by setting the cache's FetchInMemoryState
configuration attribute to true
.
"Persistent" state. Only applicable if a non-shared cache loader is used. The state stored in the state-provider cache's persistent store is deserialized and transferred; the recipient passes the data to its own cache loader, which persists it to the recipient's persistent store.
"Persistent" state transfer is enabled by setting a cache loader's fetchPersistentState
attribute to true
. If multiple cache loaders are configured in a chain, only one can have this property set to true; otherwise you will get an exception at startup.
Persistent state transfer with a shared cache loader does not make sense, as the same persistent store that provides the data will just end up receiving it. Therefore, if a shared cache loader is used, the cache will not allow a persistent state transfer even if a cache loader has fetchPersistentState
set to true
.
Which of these types of state transfer is appropriate depends on the usage of the cache.
If a write-through cache loader is used, the current cache state is fully represented by the persistent state. Data may have been evicted from the in-memory state, but it will still be in the persistent store. In this case, if the cache loader is not shared, persistent state transfer is used to ensure the new cache has the correct state. In-memory state can be transferred as well if the desire is to have a "hot" cache -- one that has all relevant data in memory when the cache begins providing service. (Note that the <cacheloader><preload>
element in the CacheLoaderConfig
configuration parameter can be used as well to provide a "warm" or "hot" cache without requiring an in-memory state transfer. This approach somewhat reduces the burden on the cache instance providing state, but increases the load on the persistent store on the recipient side.)
If a cache loader is used with passivation, the full representation of the state can only be obtained by combining the in-memory (i.e. non-passivated) and persistent (i.e. passivated) states. Therefore an in-memory state transfer is necessary. A persistent state transfer is necessary if the cache loader is not shared.
If no cache loader is used and the cache is solely a write-aside cache (i.e. one that is used to cache data that can also be found in a persistent store, e.g. a database), whether or not in-memory state should be transferred depends on whether or not a "hot" cache is desired.
To ensure state transfer behaves as expected, it is important that all nodes in the cluster are configured with the same settings for persistent and transient state. This is because byte array based transfers, when requested, rely only on the requester's configuration while stream based transfers rely on both the requester and sender's configuration, and this is expected to be identical.
JBoss Cache can use a CacheLoader
to back up the in-memory cache to a backend datastore. If JBoss Cache is configured with a cache loader, then the following features are provided:
Whenever a cache element is accessed, and that element is not in the cache (e.g. due to eviction or due to server restart), then the cache loader transparently loads the element into the cache if found in the backend store.
Whenever an element is modified, added or removed, then that modification is persisted in the backend store via the cache loader. If transactions are used, all modifications created within a transaction are persisted. To this end, the CacheLoader
takes part in the two phase commit protocol run by the transaction manager, although it does not do so explicitly.
The interaction between JBoss Cache and a CacheLoader
implementation is as follows. When CacheLoaderConfiguration
(see below) is non-null, an instance of each configured CacheLoader
is created when the cache is created, and started when the cache is started.
CacheLoader.create()
and CacheLoader.start()
are called when the cache is started. Correspondingly, stop()
and destroy()
are called when the cache is stopped.
Next, setConfig()
and setCache()
are called. The latter can be used to store a reference to the cache, the former is used to configure this instance of the CacheLoader
. For example, here a database cache loader could establish a connection to the database.
The CacheLoader
interface has a set of methods that are called when no transactions are used: get()
, put()
, remove()
and removeData()
: they get/set/remove the value immediately. These methods are described as javadoc comments in the interface.
Then there are three methods that are used with transactions: prepare()
, commit()
and rollback()
. The prepare()
method is called when a transaction is to be committed. It has a transaction object and a list of modfications as argument. The transaction object can be used as a key into a hashmap of transactions, where the values are the lists of modifications. Each modification list has a number of Modification
elements, which represent the changes made to a cache for a given transaction. When prepare()
returns successfully, then the cache loader must be able to commit (or rollback) the transaction successfully.
JBoss Cache takes care of calling prepare(), commit() and rollback() on the cache loaders at the right time.
The commit()
method tells the cache loader to commit the transaction, and the rollback()
method tells the cache loader to discard the changes associated with that transaction.
See the javadocs on this interface for a detailed explanation on each method and the contract implementations would need to fulfil.
Cache loaders are configured as follows in the JBoss Cache XML file. Note that you can define several cache loaders, in a chain. The impact is that the cache will look at all of the cache loaders in the order they've been configured, until it finds a valid, non-null element of data. When performing writes, all cache loaders are written to (except if the ignoreModifications
element has been set to true
for a specific cache loader. See the configuration section below for details.
<!-- Cache loader config block --> <attribute name="CacheLoaderConfiguration"> <config> <!-- if passivation is true, only the first cache loader is used; the rest are ignored --> <passivation>false</passivation> <!-- comma delimited FQNs to preload --> <preload>/</preload> <!-- are the cache loaders shared in a cluster? --> <shared>false</shared> <!-- we can now have multiple cache loaders, which get chained --> <!-- the 'cacheloader' element may be repeated --> <cacheloader> <class>org.jboss.cache.loader.JDBCCacheLoader</class> <!-- properties to pass in to the cache loader --> <properties> cache.jdbc.driver=com.mysql.jdbc.Driver cache.jdbc.url=jdbc:mysql://localhost:3306/jbossdb cache.jdbc.user=root cache.jdbc.password= cache.jdbc.sql-concat=concat(1,2) </properties> <!-- whether the cache loader writes are asynchronous --> <async>false</async> <!-- only one cache loader in the chain may set fetchPersistentState to true. An exception is thrown if more than one cache loader sets this to true. --> <fetchPersistentState>true</fetchPersistentState> <!-- determines whether this cache loader ignores writes - defaults to false. --> <ignoreModifications>false</ignoreModifications> <!-- if set to true, purges the contents of this cache loader when the cache starts up. Defaults to false. --> <purgeOnStartup>false</purgeOnStartup> <!-- defines the cache loader as a singleton store where only the coordinator of the cluster will store modifications. --> <singletonStore> <!-- if true, singleton store functionality is enabled, defaults to false --> <enabled>false</enabled> <!-- implementation class for singleton store functionality which must extend org.jboss.cache.loader.AbstractDelegatingCacheLoader. Default implementation is org.jboss.cache.loader.SingletonStoreCacheLoader --> <class>org.jboss.cache.loader.SingletonStoreCacheLoader</class> <!-- properties and default values for the default singleton store functionality implementation --> <properties> pushStateWhenCoordinator=true pushStateWhenCoordinatorTimeout=20000 </properties> </singletonStore> </cacheloader> </config> </attribute>
The class
element defines the class of the cache loader implementation. (Note that, because of a bug in the properties editor in JBoss AS, backslashes in variables for Windows filenames might not get expanded correctly, so replace="false" may be necessary). Note that an implementation of cache loader has to have an empty constructor.
The properties
element defines a configuration specific to the given implementation. The filesystem-based implementation for example defines the root directory to be used, whereas a database implementation might define the database URL, name and password to establish a database connection. This configuration is passed to the cache loader implementation via CacheLoader.setConfig(Properties)
. Note that backspaces may have to be escaped.
preload
allows us to define a list of nodes, or even entire subtrees, that are visited by the cache on startup, in order to preload the data associated with those nodes. The default ("/") loads the entire data available in the backend store into the cache, which is probably not a good idea given that the data in the backend store might be large. As an example, /a, /product/catalogue
loads the subtrees /a
and /product/catalogue
into the cache, but nothing else. Anything else is loaded lazily when accessed. Preloading makes sense when one anticipates using elements under a given subtree frequently. .
fetchPersistentState
determines whether or not to fetch the persistent state of a cache when joining a cluster. Only one configured cache loader may set this property to true; if more than one cache loader does so, a configuration exception will be thrown when starting your cache service.
async
determines whether writes to the cache loader block until completed, or are run on a separate thread so writes return immediately. If this is set to true, an instance of org.jboss.cache.loader.AsyncCacheLoader
is constructed with an instance of the actual cache loader to be used. The AsyncCacheLoader
then delegates all requests to the underlying cache loader, using a separate thread if necessary. See the Javadocs on AsyncCacheLoader
for more details. If unspecified, the async
element defaults to false
.
Note on using the async
element: there is always the possibility of dirty reads since all writes are performed asynchronously, and it is thus impossible to guarantee when (and even if) a write succeeds. This needs to be kept in mind when setting the async
element to true.
ignoreModifications
determines whether write methods are pushed down to the specific cache loader. Situations may arise where transient application data should only reside in a file based cache loader on the same server as the in-memory cache, for example, with a further shared JDBCCacheLoader
used by all servers in the network. This feature allows you to write to the 'local' file cache loader but not the shared JDBCCacheLoader
. This property defaults to false
, so writes are propagated to all cache loaders configured.
purgeOnStatup
empties the specified cache loader (if ignoreModifications
is false
) when the cache loader starts up.
shared
indicates that the cache loader is shared among different cache instances, for example where all instances in a cluster use the same JDBC settings t talk to the same remote, shared database. Setting this to true
prevents repeated and unnecessary writes of the same data to the cache loader by different cache instances. Default value is false
.
singletonStore
element enables modifications to be stored by only one node in the cluster, the coordinator. Essentially, whenever any data comes in to some node it is always replicated so as to keep the caches' in-memory states in sync; the coordinator, though, has the sole responsibility of pushing that state to disk. This functionality can be activated setting the enabled
subelement to true in all nodes, but again only the coordinator of the cluster will store the modifications in the underlying cache loader as defined in cacheloader
element. You cannot define a cache loader as shared
and with singletonStore
enabled at the same time. Default value for enabled
is false
.
Optionally, within the singletonStore
element, you can define a class
element that specifies the implementation class that provides the singleton store functionality. This class must extend org.jboss.cache.loader.AbstractDelegatingCacheLoader
, and if absent, it defaults to org.jboss.cache.loader.SingletonStoreCacheLoader
.
The properties
subelement defines properties that allow changing the behaivour of the class providing the singleton store functionality. By default, pushStateWhenCoordinator
and pushStateWhenCoordinatorTimeout
properties have been defined, but more could be added as required by the user-defined class providing singleton store functionality.
pushStateWhenCoordinator
allows the in-memory state to be pushed to the cache store when a node becomes the coordinator, as a result of the new election of coordinator due to a cluster topology change. This can be very useful in situations where the coordinator crashes and there's a gap in time until the new coordinator is elected. During this time, if this property was set to false
and the cache was updated, these changes would never be persisted. Setting this property to true
would ensure that any changes during this process also get stored in the cache loader. You would also want to set this property to true
if each node's cache loader is configured with a different location. Default value is true
.
pushStateWhenCoordinatorTimeout
is only relevant if pushStateWhenCoordinator
is true
in which case, sets the maximum number of milliseconds that the process of pushing the in-memory state to the underlying cache loader should take, reporting a PushStateException
if exceeded. Default value is 20000.
Note on using the singletonStore
element: setting up a cache loader as a singleton and using cache passivation (via evictions) can lead to undesired effects. If a node is to be passivated as a result of an eviction, while the cluster is in the process of electing a new coordinator, the data will be lost. This is because no coordinator is active at that time and therefore, none of the nodes in the cluster will store the passivated node. A new coordinator is elected in the cluster when either, the coordinator leaves the cluster, the coordinator crashes or stops responding.
The currently available implementations shipped with JBoss Cache are as follows.
JBoss Cache ships with several cache loaders that utilise the file system as a data store. They all require that the <cacheloader><properties>
configuration element contains a location
property, which maps to a directory to be used as a persistent store. (e.g., location=/tmp/myDataStore
). Used mainly for testing and not recommended for production use.
FileCacheLoader
, which is a simple filesystem-based implementation. By default, this cache loader checks for any potential character portability issues in the location or tree node names, for example invalid characters, producing warning messages. These checks can be disabled adding check.character.portability
property to the <properties>
element and setting it to false
(e.g., check.character.portability=false
).
The FileCacheLoader has some severe limitations which restrict it's use in a production environment, or if used in such an environment, it should be used with due care and sufficient understanding of these limitations.
Due to the way the FileCacheLoader represents a tree structure on disk (directories and files) traversal is inefficient for deep trees.
Usage on shared filesystems like NFS, Windows shares, etc. should be avoided as these do not implement proper file locking and can cause data corruption.
Usage with an isolation level of NONE can cause corrupt writes as multiple threads attempt to write to the same file.
File systems are inherently not transactional, so when attempting to use your cache in a transactional context, failures when writing to the file (which happens during the commit phase) cannot be recovered.
As a rule of thumb, it is recommended that the FileCacheLoader not be used in a highly concurrent, transactional or stressful environment, and it's use is restricted to testing.
BdbjeCacheLoader
, which is a cache loader implementation based on the Oracle/Sleepycat's BerkeleyDB Java Edition .
JdbmCacheLoader
, which is a cache loader implementation based on the JDBM engine , a fast and free alternative to BerkeleyDB.
Note that the BerkeleyDB implementation is much more efficient than the filesystem-based implementation, and provides transactional guarantees, but requires a commercial license if distributed with an application (see http://www.oracle.com/database/berkeley-db/index.html for details).
LocalDelegatingCacheLoader
, which enables loading from and storing to another local (same JVM) cache.
ClusteredCacheLoader
, which allows querying of other caches in the same cluster for in-memory data via the same clustering protocols used to replicate data. Writes are not 'stored' though, as replication would take care of any updates needed. You need to specify a property called timeout
, a long value telling the cache loader how many milliseconds to wait for responses from the cluster before assuming a null value. For example, timeout = 3000
would use a timeout value of 3 seconds.
JBossCache is distributed with a JDBC-based cache loader implementation that stores/loads nodes' state into a relational database. The implementing class is org.jboss.cache.loader.JDBCCacheLoader
.
The current implementation uses just one table. Each row in the table represents one node and contains three columns:
column for Fqn
(which is also a primary key column)
column for node contents (attribute/value pairs)
column for parent Fqn
Fqn
's are stored as strings. Node content is stored as a BLOB. WARNING: JBoss Cache does not impose any limitations on the types of objects used in Fqn
but this implementation of cache loader requires Fqn
to contain only objects of type java.lang.String
. Another limitation for Fqn
is its length. Since Fqn
is a primary key, its default column type is VARCHAR
which can store text values up to some maximum length determined by the database in use.
See http://wiki.jboss.org/wiki/Wiki.jsp?page=JDBCCacheLoader for configuration tips with specific database systems.
Table and column names as well as column types are configurable with the following properties.
cache.jdbc.table.name - the name of the table. Can be prepended with schema name for the given table: <schema_name>.<table_name>. The default value is 'jbosscache'.
cache.jdbc.table.primarykey - the name of the primary key for the table. The default value is 'jbosscache_pk'.
cache.jdbc.table.create - can be true or false. Indicates whether to create the table during startup. If true, the table is created if it doesn't already exist. The default value is true.
cache.jdbc.table.drop - can be true or false. Indicates whether to drop the table during shutdown. The default value is true.
cache.jdbc.fqn.column - FQN column name. The default value is 'fqn'.
cache.jdbc.fqn.type - FQN column type. The default value is 'varchar(255)'.
cache.jdbc.node.column - node contents column name. The default value is 'node'.
cache.jdbc.node.type - node contents column type. The default value is 'blob'. This type must specify a valid binary data type for the database being used.
If you are using JBossCache in a managed environment (e.g., an application server) you can specify the JNDI name of the DataSource you want to use.
cache.jdbc.datasource - JNDI name of the DataSource. The default value is java:/DefaultDS
.
If you are not using DataSource you have the following properties to configure database access using a JDBC driver.
cache.jdbc.driver - fully qualified JDBC driver name.
cache.jdbc.url - URL to connect to the database.
cache.jdbc.user - user name to connect to the database.
cache.jdbc.password - password to connect to the database.
JBoss Cache implements JDBC connection pooling when running outside of an application server standalone using the c3p0:JDBC DataSources/Resource Pools library. In order to enable it, just edit the following property:
cache.jdbc.connection.factory - Connection factory class name. If not set, it defaults to standard non-pooled implementation. To enable c3p0 pooling, just set the connection factory class for c3p0. See example below.
You can also set any c3p0 parameters in the same cache loader properties section but don't forget to start the property name with 'c3p0.'. To find a list of available properties, please check the c3p0 documentation for the c3p0 library version distributed in c3p0:JDBC DataSources/Resource Pools . Also, in order to provide quick and easy way to try out different pooling parameters, any of these properties can be set via a System property overriding any values these properties might have in the JBoss Cache XML configuration file, for example: -Dc3p0.maxPoolSize=20
. If a c3p0 property is not defined in either the configuration file or as a System property, default value, as indicated in the c3p0 documentation, will apply.
Below is an example of a JDBCCacheLoader using Oracle as database. The CacheLoaderConfiguration XML element contains an arbitrary set of properties which define the database-related configuration.
<attribute name="CacheLoaderConfiguration"> <config> <passivation>false</passivation> <preload>/some/stuff</preload> <cacheloader> <class>org.jboss.cache.loader.JDBCCacheLoader</class> <properties> cache.jdbc.table.name=jbosscache cache.jdbc.table.create=true cache.jdbc.table.drop=true cache.jdbc.table.primarykey=jbosscache_pk cache.jdbc.fqn.column=fqn cache.jdbc.fqn.type=varchar(255) cache.jdbc.node.column=node cache.jdbc.node.type=blob cache.jdbc.parent.column=parent cache.jdbc.driver=oracle.jdbc.OracleDriver cache.jdbc.url=jdbc:oracle:thin:@localhost:1521:JBOSSDB cache.jdbc.user=SCOTT cache.jdbc.password=TIGER cache.jdbc.sql-concat=concat(1,2) </properties> <async>false</async> <fetchPersistentState>true</fetchPersistentState> <ignoreModifications>false</ignoreModifications> <purgeOnStartup>false</purgeOnStartup> </cacheloader> </config> </attribute>
As an alternative to configuring the entire JDBC connection, the name of an existing data source can be given:
<attribute name="CacheLoaderConfiguration"> <config> <passivation>false</passivation> <preload>/some/stuff</preload> <cacheloader> <class>org.jboss.cache.loader.JDBCCacheLoader</class> <properties> cache.jdbc.datasource=java:/DefaultDS </properties> <async>false</async> <fetchPersistentState>true</fetchPersistentState> <ignoreModifications>false</ignoreModifications> <purgeOnStartup>false</purgeOnStartup> </cacheloader> </config> </attribute>
Cconfiguration example for a cache loader using c3p0 JDBC connection pooling:
<attribute name="CacheLoaderConfiguration"> <config> <passivation>false</passivation> <preload>/some/stuff</preload> <cacheloader> <class>org.jboss.cache.loader.JDBCCacheLoader</class> <properties> cache.jdbc.table.name=jbosscache cache.jdbc.table.create=true cache.jdbc.table.drop=true cache.jdbc.table.primarykey=jbosscache_pk cache.jdbc.fqn.column=fqn cache.jdbc.fqn.type=varchar(255) cache.jdbc.node.column=node cache.jdbc.node.type=blob cache.jdbc.parent.column=parent cache.jdbc.driver=oracle.jdbc.OracleDriver cache.jdbc.url=jdbc:oracle:thin:@localhost:1521:JBOSSDB cache.jdbc.user=SCOTT cache.jdbc.password=TIGER cache.jdbc.sql-concat=concat(1,2) cache.jdbc.connection.factory=org.jboss.cache.loader.C3p0ConnectionFactory c3p0.maxPoolSize=20 c3p0.checkoutTimeout=5000 </properties> <async>false</async> <fetchPersistentState>true</fetchPersistentState> <ignoreModifications>false</ignoreModifications> <purgeOnStartup>false</purgeOnStartup> </cacheloader> </config> </attribute>
The S3CacheLoader
uses the Amazon S3 (Simple Storage Solution) for storing cache data. Since Amazon S3 is remote network storage and has fairly high latency, it is really best for caches that store large pieces of data, such as media or files. But consider this cache loader over the JDBC or file system based cache loaders if you want remotely managed, highly reliable storage. Or, use it for applications running on Amazon's EC2 (Elastic Compute Cloud).
If you're planning to use Amazon S3 for storage, consider using it with JBoss Cache. JBoss Cache itself provides in-memory caching for your data to minimize the amount of remote access calls, thus reducing the latency and cost of fetching your Amazon S3 data. With cache replication, you are also able to load data from your local cluster without having to remotely access it every time.
Note that Amazon S3 does not support transactions. If transactions are used in your application then there is some possibility of state inconsistency when using this cache loader. However, writes are atomic, in that if a write fails nothing is considered written and data is never corrupted.
Data is stored in keys based on the Fqn of the Node and Node data is serialized as a java.util.Map using the CacheSPI.getMarshaller()
instance. Read the javadoc on how data is structured and stored. Data is stored using Java serialization. Be aware this means data is not readily accessible over HTTP to non-JBoss Cache clients. Your feedback and help would be appreciated to extend this cache loader for that purpose.
With this cache loader, single-key operations such as Node.remove(Object)
and Node.put(Object, Object)
are the slowest as data is stored in a single Map instance. Use bulk operations such as Node.replaceAll(Map)
and Node.clearData()
for more efficiency. Try the cache.s3.optimize
option as well.
The S3 cache loader is provided with the default distribution but requires a library to access the service at runtime. This runtime library may be obtained through a Sourceforge Maven Repository. Include the following sections in your pom.xml file:
<repository> <id>e-xml.sourceforge.net</id> <url>http://e-xml.sourceforge.net/maven2/repository</url> </repository> ... <dependency> <groupId>net.noderunner</groupId> <artifactId>amazon-s3</artifactId> <version>1.0.0.0</version> <scope>runtime</scope> </dependency>
If you do not use Maven, you can still download the amazon-s3 library by navigating the repository or through this URL.
At a minimum, you must configure your Amazon S3 access key and secret access key. The following configuration keys are listed in general order of utility.
cache.s3.accessKeyId
- Amazon S3 Access Key, available from your account profile.
cache.s3.secretAccessKey
- Amazon S3 Secret Access Key, available from your account profile. As this is a password, be careful not to distribute it or include this secret key in built software.
cache.s3.secure
- The default isfalse
: Traffic is sent unencrypted over the public Internet. Set to true
to use HTTPS. Note that unencrypted uploads and downloads use less CPU.
cache.s3.bucket
- Name of the bucket to store data. For different caches using the same access key, use a different bucket name. Read the S3 documentation on the definition of a bucket. The default value is jboss-cache
.
cache.s3.callingFormat
- One of PATH
, SUBDOMAIN
, or VANITY
. Read the S3 documentation on the use of calling domains. The default value is SUBDOMAIN
.
cache.s3.optimize
- The default is false
. If true, put(Map)
operations replace the data stored at an Fqn rather than attempt to fetch and merge. (This option is fairly experimental at the moment.)
cache.s3.parentCache
- The default is true
. Set this value to false
if you are using multiple caches sharing the same S3 bucket, that remove parent nodes of nodes being created in other caches. (This is not a common use case.)
JBoss Cache stores nodes in a tree format and automatically creates intermediate parent nodes as necessary. The S3 cache loader must also create these parent nodes as well to allow for operations such as getChildrenNames
to work properly. Checking if all parent nodes exists for every put
operation is fairly expensive, so by default the cache loader caches the existence of these parent nodes.
cache.s3.location
- This choses a primary storage location for your data to reduce loading and retrevial latency. Set to EU
to store data in Europe. The default is null
, to store data in the United States.
This cache loader allows to delegate loads and stores to another instance of JBoss Cache, which could reside (a) in the same address space, (b) in a different process on the same host, or (c) in a different process on a different host.
A TcpDelegatingCacheLoader talks to a remote org.jboss.cache.loader.tcp.TcpCacheServer
, which can be a standalone process started on the command line, or embedded as an MBean inside JBoss AS. The TcpCacheServer
has a reference to another JBoss Cache instance, which it can create itself, or which is given to it (e.g. by JBoss, using dependency injection).
As of JBoss Cache 2.1.0, the TcpDelegatingCacheLoader transparently handles reconnects if the connection to the TcpCacheServer is lost.
The TcpDelegatingCacheLoader is configured with the host and port of the remote TcpCacheServer, and uses this to communicate to it. In addition, 2 new optional parameters are used to control transparent reconnecting to the TcpCacheServer. The timeout
property (defaults to 5000) specifies the length of time the cache loader must continue retrying to connect to the TcpCacheServer before giving up and throwing an exception. The reconnectWaitTime
(defaults to 500) is how long the cache loader should wait before attempting a reconnect if it detects a communication failure. The last two parameters can be used to add a level of fault tolerance to the cache loader, do deal with TcpCacheServer restarts.
The configuration looks as follows:
<attribute name="CacheLoaderConfiguration"> <config> <cacheloader> <class>org.jboss.cache.loader.TcpDelegatingCacheLoader</class> <properties> host=myRemoteServer port=7500 timeout=10000 reconnectWaitTime=250 </properties> </cacheloader> </config> </attribute>
This means this instance of JBoss Cache will delegate all load and store requests to the remote TcpCacheServer running on myRemoteServer:7500
.
A typical use case could be multiple replicated instances of JBoss Cache in the same cluster, all delegating to the same TcpCacheServer instance. The TcpCacheServer might itself delegate to a database via JDBCCacheLoader, but the point here is that - if we have 5 nodes all accessing the same dataset - they will load the data from the TcpCacheServer, which has do execute one SQL statement per unloaded data set. If the nodes went directly to the database, then we'd have the same SQL executed multiple times. So TcpCacheServer serves as a natural cache in front of the DB (assuming that a network round trip is faster than a DB access (which usually also include a network round trip)).
To alleviate single point of failure, we could configure several cache loaders. The first cache loader is a ClusteredCacheLoader, the second a TcpDelegatingCacheLoader, and the last a JDBCacheLoader, effectively defining our cost of access to a cache in increasing order.
The way cached data is written to FileCacheLoader
and JDBCCacheLoader
based cache stores has changed in JBoss Cache 2.0 in such way that these cache loaders now write and read data using the same marhalling framework used to replicate data accross the network. Such change is trivial for replication purpouses as it just requires the rest of the nodes to understand this format. However, changing the format of the data in cache stores brings up a new problem: how do users, which have their data stored in JBoss Cache 1.x.x format, migrate their stores to JBoss Cache 2.0 format?
With this in mind, JBoss Cache 2.0 comes with two cache loader implementations called org.jboss.cache.loader.TransformingFileCacheLoader
and org.jboss.cache.loader.TransformingJDBCCacheLoader
located within the optional jbosscache-cacheloader-migration.jar file. These are one-off cache loaders that read data from the cache store in JBoss Cache 1.x.x format and write data to cache stores in JBoss Cache 2.0 format.
The idea is for users to modify their existing cache configuration file(s) momentarily to use these cache loaders and for them to create a small Java application that creates an instance of this cache, recursively reads the entire cache and writes the data read back into the cache. Once the data is transformed, users can revert back to their original cache configuration file(s). In order to help the users with this task, a cache loader migration example has been constructed which can be located under the examples/cacheloader-migration
directory within the JBoss Cache distribution. This example, called examples.TransformStore
, is independent of the actual data stored in the cache as it writes back whatever it was read recursively. It is highly recommended that anyone interested in porting their data run this example first, which contains a readme.txt
file with detailed information about the example itself, and also use it as base for their own application.
A cache loader can be used to enforce node passivation and activation on eviction in a cache.
Cache Passivation is the process of removing an object from in-memory cache and writing it to a secondary data store (e.g., file system, database) on eviction. Cache Activation is the process of restoring an object from the data store into the in-memory cache when it's needed to be used. In both cases, the configured cache loader will be used to read from the data store and write to the data store.
When an eviction policy in effect evicts a node from the cache, if passivation is enabled, a notification that the node is being passivated will be emitted to the cache listeners and the node and its children will be stored in the cache loader store. When a user attempts to retrieve a node that was evicted earlier, the node is loaded (lazy loaded) from the cache loader store into memory. When the node and its children have been loaded, they're removed from the cache loader and a notification is emitted to the cache listeners that the node has been activated.
To enable cache passivation/activation, you can set passivation
to true. The default is false
. When passivation is used, only the first cache loader configured is used and all others are ignored.
When passivation is disabled, whenever an element is modified, added or removed, then that modification is persisted in the backend store via the cache loader. There is no direct relationship between eviction and cache loading. If you don't use eviction, what's in the persistent store is basically a copy of what's in memory. If you do use eviction, what's in the persistent store is basically a superset of what's in memory (i.e. it includes nodes that have been evicted from memory).
When passivation is enabled, there is a direct relationship between eviction and the cache loader. Writes to the persistent store via the cache loader only occur as part of the eviction process. Data is deleted from the persistent store when the application reads it back into memory. In this case, what's in memory and what's in the persistent store are two subsets of the total information set, with no intersection between the subsets.
Following is a simple example, showing what state is in RAM and in the persistent store after each step of a 6 step process:
Insert /A
Insert /B
Eviction thread runs, evicts /A
Read /A
Eviction thread runs, evicts /B
Remove /B
When passivation is disabled:
1) RAM: /A Disk: /A 2) RAM: /A, /B Disk: /A, /B 3) RAM: /B Disk: /A, /B 4) RAM: /A, /B Disk: /A, /B 5) RAM: /A Disk: /A, /B 6) RAM: /A Disk: /A
When passivation is enabled:
1) RAM: /A Disk: 2) RAM: /A, /B Disk: 3) RAM: /B Disk: /A 4) RAM: /A, /B Disk: 5) RAM: /A Disk: /B 6) RAM: /A Disk:
This section discusses different patterns of combining different cache loader types and configuration options to achieve specific outcomes.
This is the simplest case. We have a JBoss Cache instance, whose cache mode is LOCAL
, therefore no replication is going on. The cache loader simply loads non-existing elements from the store and stores modifications back to the store. When the cache is started, depending on the preload
element, certain data can be preloaded, so that the cache is partly warmed up.
The following figure shows 2 JBoss Cache instances sharing the same backend store:
Both nodes have a cache loader that accesses a common shared backend store. This could for example be a shared filesystem (using the FileCacheLoader), or a shared database. Because both nodes access the same store, they don't necessarily need state transfer on startup. [6] Rather, the FetchInMemoryState
attribute could be set to false, resulting in a 'cold' cache, that gradually warms up as elements are accessed and loaded for the first time. This would mean that individual caches in a cluster might have different in-memory state at any given time (largely depending on their preloading and eviction strategies).
When storing a value, the writer takes care of storing the change in the backend store. For example, if node1 made change C1 and node2 C2, then node1 would tell its cache loader to store C1, and node2 would tell its cache loader to store C2.
This is a similar case to the previous one, but here only one node in the cluster interacts with a backend store via its cache loader. All other nodes perform in-memory replication. The idea here is all application state is kept in memory in each node, with the existence of multiple caches making the data highly available. (This assumes that a client that needs the data is able to somehow fail over from one cache to another.) The single persistent backend store then provides a backup copy of the data in case all caches in the cluster fail or need to be restarted.
Note that here it may make sense for the cache loader to store changes asynchronously, that is not on the caller's thread, in order not to slow down the cluster by accessing (for example) a database. This is a non-issue when using asynchronous replication.
A weakness with this architecture is that the cache with access to the cache loader becomes a single point of failure. Furthermore, if the cluster is restarted, the cache with the cache loader must be started first (easy to forget). A solution to the first problem is to configure a cache loader on each node, but set the singletonStore
configuration to true
. With this kind of setup, one but only one node will always be writing to a persistent store. However, this complicates the restart problem, as before restarting you need to determine which cache was writing before the shutdown/failure and then start that cache first.
Here, each node has its own datastore. Modifications to the cache are (a) replicated across the cluster and (b) persisted using the cache loader. This means that all datastores have exactly the same state. When replicating changes synchronously and in a transaction, the two phase commit protocol takes care that all modifications are replicated and persisted in each datastore, or none is replicated and persisted (atomic updates).
Note that JBoss Cache is not an XA Resource, that means it doesn't implement recovery. When used with a transaction manager that supports recovery, this functionality is not available.
The challenge here is state transfer: when a new node starts it needs to do the following:
Tell the coordinator (oldest node in a cluster) to send it the state. This is always a full state transfer, overwriting any state that may already be present.
The coordinator then needs to wait until all in-flight transactions have completed. During this time, it will not allow for new transactions to be started.
Then the coordinator asks its cache loader for the entire state using loadEntireState()
. It then sends back that state to the new node.
The new node then tells its cache loader to store that state in its store, overwriting the old state. This is the CacheLoader.storeEntireState()
method
As an option, the transient (in-memory) state can be transferred as well during the state transfer.
The new node now has the same state in its backend store as everyone else in the cluster, and modifications received from other nodes will now be persisted using the local cache loader.
If you need to set up a hierarchy within a single JVM, you can use the LocalDelegatingCacheLoader
. This type of hierarchy can currently only be set up programmatically.
Hierarchical caches could also be set up spanning more than one JVM or server, using the TcpDelegatingCacheLoader
.
You can set up more than one cache loader in a chain. Internally, a delegating ChainingCacheLoader
is used, with references to each cache loader you have configured. Use cases vary depending on the type of cache loaders used in the chain. One example is using a filesystem based cache loader, colocated on the same host as the JVM, used as an overflow for memory. This ensures data is available relatively easily and with low cost. An additional remote cache loader, such as a TcpDelegatingCacheLoader
provides resilience between server restarts.
[6] Of course they can enable state transfer, if they want to have a warm or hot cache after startup.
Eviction policies control JBoss Cache's memory management by managing how many nodes are allowed to be stored in memory and their life spans. Memory constraints on servers mean cache cannot grow indefinitely, so policies need to be in place to restrict the size of the cache. Eviction policies are most often used alongside cache loaderscache loaders .
The basic eviction policy configuration element looks like:
... <attribute name="EvictionConfig"> <config> <attribute name="wakeUpIntervalSeconds">3</attribute> <!-- This defaults to 200000 if not specified --> <attribute name="eventQueueSize">100000</attribute> <!-- Name of the DEFAULT eviction policy class. --> <attribute name="policyClass">org.jboss.cache.eviction.LRUPolicy</attribute> <!-- Cache wide default --> <region name="/_default_"> <attribute name="maxNodes">100</attribute> </region> <!-- override policy used for this region --> <region name="/org/jboss/data" policyClass="org.jboss.cache.eviction.LRUPolicy"> <attribute name="maxNodes">250</attribute> <attribute name="minTimeToLiveSeconds">10</attribute> </region> <!-- We expect a lot of events for this region, so override the default event queue size --> <region name="/org/jboss/test/data" eventQueueSize="500000"> <attribute name="maxNodes">60000</attribute> </region> </config> </attribute> ...
wakeUpIntervalSeconds
- this required parameter defines how often the eviction thread runs
eventQueueSize
- this optional parameter defines the size of the queue which holds eviction events. If your eviction thread does not run often enough, you may need to increase this. This can be overridden on a per-region basis.
policyClass
- this is required, unless you set individual policyClass attributes on each and every region. This defines the eviction policy to use if one is not defined for a region.
The concept of regions and the Region
class were visited earlier when talking about marshalling. Regions also have another use, in that they are used to define the eviction policy used within the region. In addition to using a region-specific configuration, you can also configure a default, cache-wide eviction policy for nodes that do not fall into predefined regions or if you do not wish to define specific regions. It is important to note that when defining regions using the configuration XML file, all elements of the Fqn
that defines the region are java.lang.String
objects.
Looking at the eviction configuration snippet above, we see that a default region, _default_
, holds attributes which apply to nodes that do not fall into any of the other regions defined.
For each region, you can define parameters which affect how the policy which applies to the region chooses to evict nodes. In the example above, the LRUPolicy
allows a maxNodes
parameter which defines how many nodes can exist in the region before it chooses to start evicting nodes. See the javadocs for each policy for a list of allowed parameters. It also defines a minTimeToLiveSeconds
parameter, which defines a minimum time a node must exist in memory before being considered for eviction.
It's possible to define regions that overlap. In other words, one region can be defined for /a/b/c , and another defined for /a/b/c/d (which is just the d subtree of the /a/b/c sub-tree). The algorithm, in order to handle scenarios like this consistently, will always choose the first region it encounters. In this way, if the algorithm needed to decide how to handle /a/b/c/d/e , it would start from there and work its way up the tree until it hits the first defined region - in this case /a/b/c/d .
Nodes marked as resident (using Node.setResident()
API) will be ignored by the eviction policies both when checking whether to trigger the eviction and when proceeding with the actual eviction of nodes. E.g. if a region is configured to have a maximum of 10 nodes, resident nodes won't be counted when deciding whether to evict nodes in that region. In addition, resident nodes will not be considered for eviction when the region's eviction threshold is reached.
In order to mark a node as resident the Node.setResident()
API should be used. By default, the newly created nodes are not resident. The resident
attribute of a node is neither replicated, persisted nor transaction-aware.
A sample use case for resident nodes would be ensuring "path" nodes don't add "noise" to an eviction policy. E.g.,:
... Map lotsOfData = generateData(); cache.put("/a/b/c", lotsOfData); cache.getRoot().getChild("/a").setResident(true); cache.getRoot().getChild("/a/b").setResident(true); ...
In this example, the nodes /a
and /a/b
are paths which exist solely to support the existence of node /a/b/c
and don't hold any data themselves. As such, they are good candidates for being marked as resident. This would lead to better memory management as no eviction events would be generated when accessing /a
and/a/b
.
N.B. when adding attributes to a resident node, e.g. cache.put("/a", "k", "v")
in the above example, it would make sense to mark the nodes as non-resident again and let them be considered for eviction..
Configuring eviction using the Configuration
object entails the use of the org.jboss.cache.config.EvictionConfig
bean, which is passed into Configuration.setEvictionConfig()
. See the chapter on Configuration for more on building a Configuration
programatically.
The use of simple POJO beans to represent all elements in a cache's configuration also makes it fairly easy to programatically add eviction regions after the cache is started . For example, assume we had an existing cache configured via XML with the EvictionConfig element shown above. Now at runtime we wished to add a new eviction region named "/org/jboss/fifo", using LRUPolicy
but a different number of maxNodes
:
Fqn fqn = Fqn.fromString("/org/jboss/fifo"); // Create a configuration for an LRUPolicy LRUConfiguration lruc = new LRUConfiguration(); lruc.setMaxNodes(10000); // Create the region and set the config Region region = cache.getRegion(fqn, true); region.setEvictionPolicy(lruc);
org.jboss.cache.eviction.LRUPolicy
controls both the node lifetime and age. This policy guarantees a constant order ( O (1)
) for adds, removals and lookups (visits). It has the following configuration parameters:
maxNodes
- This is the maximum number of nodes allowed in this region. 0 denotes no limit.
timeToLiveSeconds
- The amount of time a node is not written to or read (in seconds) before the node is swept away. 0 denotes no limit.
maxAgeSeconds
- Lifespan of a node (in seconds) regardless of idle time before the node is swept away. 0 denotes no limit.
minTimeToLiveSeconds
- the minimum amount of time a node must be allowed to live after being accessed before it is allowed to be considered for eviction. 0 denotes that this feature is disabled, which is the default value.
org.jboss.cache.eviction.FIFOPolicy
controls the eviction in a proper first in first out order. This policy guarantees a constant order ( O (1)
) for adds, removals and lookups (visits). It has the following configuration parameters:
maxNodes
- This is the maximum number of nodes allowed in this region. 0 denotes no limit.
minTimeToLiveSeconds
- the minimum amount of time a node must be allowed to live after being accessed before it is allowed to be considered for eviction. 0 denotes that this feature is disabled, which is the default value.
org.jboss.cache.eviction.MRUPolicy
controls the eviction in based on most recently used algorithm. The most recently used nodes will be the first to evict with this policy. This policy guarantees a constant order ( O (1)
) for adds, removals and lookups (visits). It has the following configuration parameters:
maxNodes
- This is the maximum number of nodes allowed in this region. 0 denotes no limit.
minTimeToLiveSeconds
- the minimum amount of time a node must be allowed to live after being accessed before it is allowed to be considered for eviction. 0 denotes that this feature is disabled, which is the default value.
org.jboss.cache.eviction.LFUPolicy
controls the eviction in based on least frequently used algorithm. The least frequently used nodes will be the first to evict with this policy. Node usage starts at 1 when a node is first added. Each time it is visted, the node usage counter increments by 1. This number is used to determine which nodes are least frequently used. LFU is also a sorted eviction algorithm. The underlying EvictionQueue implementation and algorithm is sorted in ascending order of the node visits counter. This class guarantees a constant order ( O (1)
) for adds, removal and searches. However, when any number of nodes are added/visited to the queue for a given processing pass, a single quasilinear ( O (n * log n)
) operation is used to resort the queue in proper LFU order. Similarly if any nodes are removed or evicted, a single linear ( O (n)
) pruning operation is necessary to clean up the EvictionQueue. LFU has the following configuration parameters:
maxNodes
- This is the maximum number of nodes allowed in this region. 0 denotes no limit.
minNodes
- This is the minimum number of nodes allowed in this region. This value determines what the eviction queue should prune down to per pass. e.g. If minNodes is 10 and the cache grows to 100 nodes, the cache is pruned down to the 10 most frequently used nodes when the eviction timer makes a pass through the eviction algorithm.
minTimeToLiveSeconds
- the minimum amount of time a node must be allowed to live after being accessed before it is allowed to be considered for eviction. 0 denotes that this feature is disabled, which is the default value.
org.jboss.cache.eviction.ExpirationPolicy
is a policy that evicts nodes based on an absolute expiration time. The expiration time is indicated using the org.jboss.cache.Node.put()
method, using a String key expiration
and the absolute time as a java.lang.Long
object, with a value indicated as milliseconds past midnight January 1st, 1970 UTC (the same relative time as provided by java.lang.System.currentTimeMillis()
).
This policy guarantees a constant order ( O (1)
) for adds and removals. Internally, a sorted set (TreeSet) containing the expiration time and Fqn of the nodes is stored, which essentially functions as a heap.
This policy has the following configuration parameters:
expirationKeyName
- This is the Node key name used in the eviction algorithm. The configuration default is expiration
.
maxNodes
- This is the maximum number of nodes allowed in this region. 0 denotes no limit.
The following listing shows how the expiration date is indicated and how the policy is applied:
Cache cache = DefaultCacheFactory.createCache(); Fqn fqn1 = Fqn.fromString("/node/1"); Long future = new Long(System.currentTimeMillis() + 2000); // sets the expiry time for a node cache.getRoot().addChild(fqn1).put(ExpirationConfiguration.EXPIRATION_KEY, future); assertTrue(cache.getRoot().hasChild(fqn1)); Thread.sleep(5000); // after 5 seconds, expiration completes assertFalse(cache.getRoot().hasChild(fqn1));
Note that the expiration time of nodes is only checked when the region manager wakes up every wakeUpIntervalSeconds
, so eviction may happen a few seconds later than indicated.
org.jboss.cache.eviction.ElementSizePolicy
controls the eviction in based on the number of key/value pairs in the node. Nodes The most recently used nodes will be the first to evict with this policy. It has the following configuration parameters:
maxNodes
- This is the maximum number of nodes allowed in this region. 0 denotes no limit.
maxElementsPerNode
- This is the trigger number of attributes per node for the node to be selected for eviction. 0 denotes no limit.
minTimeToLiveSeconds
- the minimum amount of time a node must be allowed to live after being accessed before it is allowed to be considered for eviction. 0 denotes that this feature is disabled, which is the default value.
The design of the JBoss Cache eviction policy framework is based on an EvictionInterceptor
to handle cache events and relay them back to the eviction policies. During the cache start up, an EvictionInterceptor
will be added to the cache interceptor stack if the eviction policy is specified. Then whenever a node is added, removed, evicted, or visited, the EvictionInterceptor
will maintain state statistics and information will be relayed to each individual eviction region.
There is a single eviction thread (timer) that will run at a configured interval. This thread will make calls into each of the policy providers and inform it of any aggregated adds, removes and visits (gets) events to the cache during the configured interval. The eviction thread is responsible for kicking off the eviction policy processing (a single pass) for each configured eviction cache region.
In order to implement an eviction policy, the following interfaces must be implemented:
org.jboss.cache.eviction.EvictionPolicy
org.jboss.cache.eviction.EvictionAlgorithm
org.jboss.cache.eviction.EvictionQueue
org.jboss.cache.config.EvictionPolicyConfig
When compounded together, each of these interface implementations define all the underlying mechanics necessary for a complete eviction policy implementation.
Note that:
The EvictionPolicyConfig
implementation should maintain getter and setter methods for whatever configuration properties the policy supports (e.g. for LRUConfiguration
among others there is a int getMaxNodes()
and a setMaxNodes(int)
). When the "EvictionConfig" section of an XML configuration is parsed, these properties will be set by reflection.
Alternatively, the implementation of a new eviction policy provider can be simplified by extending BaseEvictionPolicy
and BaseEvictionAlgorithm
. Or for properly sorted EvictionAlgorithms (sorted in eviction order - see LFUAlgorithm
) extending BaseSortedEvictionAlgorithm
and implementing SortedEvictionQueue
takes care of most of the common functionality available in a set of eviction policy provider classes
Note that:
The BaseEvictionAlgorithm
class maintains a processing structure. It will process the ADD, REMOVE, and VISIT events queued by the region first. It also maintains an collection of items that were not properly evicted during the last go around because of held locks. That list is pruned. Finally, the EvictionQueue itself is pruned for entries that should be evicted based upon the configured eviction rules for the region.
The BaseSortedEvictionAlgorithm
class will maintain a boolean through the algorithm processing that will determine if any new nodes were added or visited. This allows the Algorithm to determine whether to resort the eviction queue items (in first to evict order) or to skip the potentially expensive sorting if there have been no changes to the cache in this region.
The SortedEvictionQueue
interface defines the contract used by the BaseSortedEvictionAlgorithm
abstract class that is used to resort the underlying queue. Again, the queue sorting should be sorted in first to evict order. The first entry in the list should evict before the last entry in the queue. The last entry in the queue should be the last entry that will require eviction.
JBoss Cache is a thread safe caching API, and uses its own efficient mechanisms of controlling concurrent access. It uses a pessimistic locking scheme by default for this purpose. Optimistic locking may alternatively be used, and is discussed later.
Locking is done internally, on a node-level. For example when we want to access "/a/b/c", a lock will be acquired for nodes "a", "b" and "c". When the same transaction wants to access "/a/b/c/d", since we already hold locks for "a", "b" and "c", we only need to acquire a lock for "d".
Lock owners are either transactions (call is made within the scope of an existing transaction) or threads (no transaction associated with the call). Regardless, a transaction or a thread is internally transformed into an instance of GlobalTransaction
, which is used as a globally unique identifier for modifications across a cluster. E.g. when we run a two-phase commit protocol across the cluster, the GlobalTransaction
uniquely identifies a unit of work across a cluster.
Locks can be read or write locks. Write locks serialize read and write access, whereas read-only locks only serialize read access. When a write lock is held, no other write or read locks can be acquired. When a read lock is held, others can acquire read locks. However, to acquire write locks, one has to wait until all read locks have been released. When scheduled concurrently, write locks always have precedence over read locks. Note that (if enabled) read locks can be upgraded to write locks.
Using read-write locks helps in the following scenario: consider a tree with entries "/a/b/n1" and "/a/b/n2". With write-locks, when Tx1 accesses "/a/b/n1", Tx2 cannot access "/a/b/n2" until Tx1 has completed and released its locks. However, with read-write locks this is possible, because Tx1 acquires read-locks for "/a/b" and a read-write lock for "/a/b/n1". Tx2 is then able to acquire read-locks for "/a/b" as well, plus a read-write lock for "/a/b/n2". This allows for more concurrency in accessing the cache.
By default, JBoss Cache uses pessimistic locking. Locking is not exposed directly to user. Instead, a transaction isolation level which provides different locking behaviour is configurable.
JBoss Cache supports the following transaction isolation levels, analogous to database ACID isolation levels. A user can configure an instance-wide isolation level of NONE, READ_UNCOMMITTED, READ_COMMITTED, REPEATABLE_READ, or SERIALIZABLE. REPEATABLE_READ is the default isolation level used.
NONE. No transaction support is needed. There is no locking at this level, e.g., users will have to manage the data integrity. Implementations use no locks.
READ_UNCOMMITTED. Data can be read anytime while write operations are exclusive. Note that this level doesn't prevent the so-called "dirty read" where data modified in Tx1 can be read in Tx2 before Tx1 commits. In other words, if you have the following sequence,
Tx1 Tx2 W R
using this isolation level will not prevent Tx2 read operation. Implementations typically use an exclusive lock for writes while reads don't need to acquire a lock.
READ_COMMITTED. Data can be read any time as long as there is no write. This level prevents the dirty read. But it doesn’t prevent the so-called ‘non-repeatable read’ where one thread reads the data twice can produce different results. For example, if you have the following sequence,
Tx1 Tx2 R W R
where the second read in Tx1 thread will produce different result.
Implementations usually use a read-write lock; reads succeed acquiring the lock when there are only reads, writes have to wait until there are no more readers holding the lock, and readers are blocked acquiring the lock until there are no more writers holding the lock. Reads typically release the read-lock when done, so that a subsequent read to the same data has to re-acquire a read-lock; this leads to nonrepeatable reads, where 2 reads of the same data might return different values. Note that, the write only applies regardless of transaction state (whether it has been committed or not).
REPEATABLE_READ. Data can be read while there is no write and vice versa. This level prevents "non-repeatable read" but it does not completely prevent the so-called "phantom read" where new data can be inserted into the tree from another transaction. Implementations typically use a read-write lock. This is the default isolation level used.
SERIALIZABLE. Data access is synchronized with exclusive locks. Only 1 writer or reader can have the lock at any given time. Locks are released at the end of the transaction. Regarded as very poor for performance and thread/transaction concurrency.
By default, before inserting a new node into the tree or removing an existing node from the tree, JBoss Cache will only attempt to acquire a read lock on the new node's parent node. This approach does not treat child nodes as an integral part of a parent node's state. This approach allows greater concurrency if nodes are frequently added or removed, but at a cost of lesser correctness. For use cases where greater correctness is necessary, JBoss Cache provides a configuration option LockParentForChildInsertRemove
. If this is set to true
, insertions and removals of child nodes require the acquisition of a write lock on the parent node.
In addition to the above, in version 2.1.0 and above, JBoss Cache offers the ability to override this configuration on a per-node basis. See Node.setLockForChildInsertRemove()
and it's corresponding javadocs for details.
The motivation for optimistic locking is to improve concurrency. When a lot of threads have a lot of contention for access to the data tree, it can be inefficient to lock portions of the tree - for reading or writing - for the entire duration of a transaction as we do in pessimistic locking. Optimistic locking allows for greater concurrency of threads and transactions by using a technique called data versioning, explained here. Note that isolation levels (if configured) are ignored if optimistic locking is enabled.
Optimistic locking treats all method calls as transactional [7] . Even if you do not invoke a call within the scope of an ongoing transaction, JBoss Cache creates an implicit transaction and commits this transaction when the invocation completes. Each transaction maintains a transaction workspace, which contains a copy of the data used within the transaction.
For example, if a transaction calls cache.getRoot().getChild( Fqn.fromString("/a/b/c") )
, nodes a, b and c are copied from the main data tree and into the workspace. The data is versioned and all calls in the transaction work on the copy of the data rather than the actual data. When the transaction commits, its workspace is merged back into the underlying tree by matching versions. If there is a version mismatch - such as when the actual data tree has a higher version than the workspace, perhaps if another transaction were to access the same data, change it and commit before the first transaction can finish - the transaction throws a RollbackException
when committing and the commit fails.
Optimistic locking uses the same locks we speak of above, but the locks are only held for a very short duration - at the start of a transaction to build a workspace, and when the transaction commits and has to merge data back into the tree.
So while optimistic locking may occasionally fail if version validations fail or may run slightly slower than pessimistic locking due to the inevitable overhead and extra processing of maintaining workspaces, versioned data and validating on commit, it does buy you a near-SERIALIZABLE degree of data integrity while maintaining a very high level of concurrency.
Optimistic locking makes use of the DataVersion
interface (and an internal and default DefaultDataVersion
implementation to keep a track of node versioning. In certain cases, where cached data is an in-memory representation of data from an external source such as a database, it makes sense to align the versions used in JBoss Cache with the versions used externally. As such, using the options API , it is possible to set the DataVersion
you wish to use on a per-invocation basis, allowing you to implement the DataVersion
interface to hold the versioning information obtained externally before putting your data into the cache.
Optimistic locking is enabled by using the NodeLockingScheme XML attribute, and setting it to "OPTIMISTIC":
... <!-- Node locking scheme: OPTIMISTIC PESSIMISTIC (default) --> <attribute name="NodeLockingScheme">OPTIMISTIC</attribute> ...
It is generally advisable that if you have an eviction policy defined along with optimistic locking, you define the eviction policy's minTimeToLiveSeconds
parameter to be slightly greater than the transaction timeout value set in your transaction manager. This ensures that data versions in the cache are not evicted while transactions are in progress [8] .
JBoss Cache can be configured to use and participate in JTA compliant transactions. Alternatively, if transaction support is disabled, it is equivalent to setting AutoCommit to on where modifications are potentially [9] replicated after every change (if replication is enabled).
What JBoss Cache does on every incoming call is:
Retrieve the current javax.transaction.Transaction
associated with the thread
If not already done, register a javax.transaction.Synchronization
with the transaction manager to be notified when a transaction commits or is rolled back.
In order to do this, the cache has to be provided with a reference to environment's javax.transaction.TransactionManager
. This is usually done by configuring the cache with the class name of an implementation of the TransactionManagerLookup
interface. When the cache starts, it will create an instance of this class and invoke its getTransactionManager()
method, which returns a reference to the TransactionManager
.
JBoss Cache ships with JBossTransactionManagerLookup
and GenericTransactionManagerLookup
. The JBossTransactionManagerLookup
is able to bind to a running JBoss AS instance and retrieve a TransactionManager
while the GenericTransactionManagerLookup
is able to bind to most popular Java EE application servers and provide the same functionality. A dummy implementation - DummyTransactionManagerLookup
- is also provided, primarily for unit tests. Being a dummy, this is just for demo and testing purposes and is not recommended for production use.
An alternative to configuring a TransactionManagerLookup
is to programatically inject a reference to the TransactionManager
into the Configuration
object's RuntimeConfig
element:
TransactionManager tm = getTransactionManager(); // magic method cache.getConfiguration().getRuntimeConfig().setTransactionManager(tm);
Injecting the TransactionManager
is the recommended approach when the Configuration
is built by some sort of IOC container that already has a reference to the TM.
When the transaction commits, we initiate either a one- two-phase commit protocol. See replicated caches and transactions for details.
[7] Because of this requirement, you must always have a transaction manager configured when using optimistic locking.
[8] See JBCACHE-1155
[9] Depending on whether interval-based asynchronous replication is used
This section contains technical references for easy look ups.
This is what a typical XML configuration file looks like. It is recommended that you use one of the configurations shipped with the JBoss Cache distribution and tweak according to your needs rather than write one from scratch.
<?xml version="1.0" encoding="UTF-8"?> <!-- ===================================================================== --> <!-- --> <!-- Sample JBoss Cache Service Configuration --> <!-- --> <!-- ===================================================================== --> <server> <!-- ==================================================================== --> <!-- Defines JBoss Cache configuration --> <!-- ==================================================================== --> <!-- Note the value of the 'code' attribute has changed since JBC 1.x --> <mbean code="org.jboss.cache.jmx.CacheJmxWrapper" name="jboss.cache:service=Cache"> <!-- Ensure JNDI and the TransactionManager are started before the cache. Only works inside JBoss AS; ignored otherwise --> <depends>jboss:service=Naming</depends> <depends>jboss:service=TransactionManager</depends> <!-- Configure the TransactionManager --> <attribute name="TransactionManagerLookupClass"> org.jboss.cache.transaction.GenericTransactionManagerLookup </attribute> <!-- Node locking level : SERIALIZABLE REPEATABLE_READ (default) READ_COMMITTED READ_UNCOMMITTED NONE --> <attribute name="IsolationLevel">REPEATABLE_READ</attribute> <!-- Lock parent before doing node additions/removes --> <attribute name="LockParentForChildInsertRemove">true</attribute> <!-- Valid modes are LOCAL (default) REPL_ASYNC REPL_SYNC INVALIDATION_ASYNC INVALIDATION_SYNC --> <attribute name="CacheMode">REPL_ASYNC</attribute> <!-- Name of cluster. Needs to be the same for all JBoss Cache nodes in a cluster in order to find each other. --> <attribute name="ClusterName">JBossCache-Cluster</attribute> <!--Uncomment next three statements to use the JGroups multiplexer. This configuration is dependent on the JGroups multiplexer being registered in an MBean server such as JBossAS. This type of dependency injection only works in the AS; outside it's up to your code to inject a ChannelFactory if you want to use one. --> <!-- <depends optional-attribute-name="MultiplexerService" proxy-type="attribute">jgroups.mux:name=Multiplexer</depends> <attribute name="MultiplexerStack">tcp</attribute> --> <!-- JGroups protocol stack properties. ClusterConfig isn't used if the multiplexer is enabled above. --> <attribute name="ClusterConfig"> <config> <!-- UDP: if you have a multihomed machine, set the bind_addr attribute to the appropriate NIC IP address --> <!-- UDP: On Windows machines, because of the media sense feature being broken with multicast (even after disabling media sense) set the loopback attribute to true --> <UDP mcast_addr="228.1.2.3" mcast_port="48866" ip_ttl="64" ip_mcast="true" mcast_send_buf_size="150000" mcast_recv_buf_size="80000" ucast_send_buf_size="150000" ucast_recv_buf_size="80000" loopback="false"/> <PING timeout="2000" num_initial_members="3"/> <MERGE2 min_interval="10000" max_interval="20000"/> <FD shun="true"/> <FD_SOCK/> <VERIFY_SUSPECT timeout="1500"/> <pbcast.NAKACK gc_lag="50" retransmit_timeout="600,1200,2400,4800" /> <UNICAST timeout="600,1200,2400",4800/> <pbcast.STABLE desired_avg_gossip="400000"/> <FC max_credits="2000000" min_threshold="0.10"/> <FRAG2 frag_size="8192"/> <pbcast.GMS join_timeout="5000" shun="true" print_local_addr="true"/> <pbcast.STATE_TRANSFER/> </config> </attribute> <!-- The max amount of time (in milliseconds) we wait until the initial state (ie. the contents of the cache) are retrieved from existing members in a clustered environment --> <attribute name="StateRetrievalTimeout">20000</attribute> <!-- Number of milliseconds to wait until all responses for a synchronous call have been received. --> <attribute name="SyncReplTimeout">20000</attribute> <!-- Max number of milliseconds to wait for a lock acquisition --> <attribute name="LockAcquisitionTimeout">15000</attribute> <!-- Shutdown hook behavior. Valid choices are: DEFAULT, REGISTER and DONT_REGISTER. If this element is omitted, DEFAULT is used. --> <attribute name="ShutdownHookBehavior">DEFAULT</attribute> <!-- Enables or disables lazy unmarshalling. If omitted, the default is that lazy unmarshalling is enabled. --> <attribute name="UseLazyDeserialization">true</attribute> <!-- Specific eviction policy configurations. This is LRU --> <attribute name="EvictionConfig"> <config> <attribute name="wakeUpIntervalSeconds">5</attribute> <!-- This defaults to 200000 if not specified --> <attribute name="eventQueueSize">200000</attribute> <attribute name="policyClass">org.jboss.cache.eviction.LRUPolicy</attribute> <!-- Cache wide default --> <region name="/_default_"> <attribute name="maxNodes">5000</attribute> <attribute name="timeToLiveSeconds">1000</attribute> </region> <region name="/org/jboss/data"> <attribute name="maxNodes">5000</attribute> <attribute name="timeToLiveSeconds">1000</attribute> </region> <region name="/org/jboss/test/data"> <attribute name="maxNodes">5</attribute> <attribute name="timeToLiveSeconds">4</attribute> </region> <region name="/test"> <attribute name="maxNodes">10000</attribute> <attribute name="timeToLiveSeconds">4</attribute> </region> <region name="/maxAgeTest"> <attribute name="maxNodes">10000</attribute> <attribute name="timeToLiveSeconds">8</attribute> <attribute name="maxAgeSeconds">10</attribute> </region> </config> </attribute> </mbean> </server>
A list of definitions of each of the XML attributes used above. If the description of an attribute states that it is dynamic , that means it can be changed after the cache is created and started.
Name |
Description |
BuddyReplicationConfig |
An XML element that contains detailed buddy replication configuration. See section on Buddy Replication for details. |
CacheLoaderConfig |
An XML element that contains detailed cache loader configuration. See chapter on Cache Loaders for details. |
CacheLoaderConfiguration |
Deprecated . Use |
CacheMode |
LOCAL, REPL_SYNC, REPL_ASYNC, INVALIDATION_SYNC or INVALIDATION_ASYNC. Defaults to LOCAL. See the chapter on Clustering for details. |
ClusterConfig |
The configuration of the underlying JGroups stack. Ignored if |
ClusterName |
Name of cluster. Needs to be the same for all nodes in a cluster in order for them to communicate with each other. |
EvictionPolicyConfig |
Configuration parameter for the specified eviction policy. See chapter on eviction policies for details. This property is dynamic . |
ExposeManagementStatistics |
Specifies whether interceptors that provide statistics should have statistics gathering enabled at startup. Also controls whether a |
FetchInMemoryState |
Whether or not to acquire the initial in-memory state from existing members. Allows for hot caches when enabled. Also see the |
InactiveOnStartup |
Whether or not the entire tree is inactive upon startup, only responding to replication messages after |
StateRetrievalTimeout |
Time in milliseconds to wait for state retrieval. This should be longer than |
IsolationLevel |
Node locking isolation level : SERIALIZABLE, REPEATABLE_READ (default), READ_COMMITTED, READ_UNCOMMITTED, and NONE. Note that this is ignored if NodeLockingScheme is OPTIMISTIC. Case doesn't matter. See documentation on Transactions and Concurrency for more details. |
LockAcquisitionTimeout |
Time in milliseconds to wait for a lock to be acquired. If a lock cannot be acquired an exception will be thrown. This property is dynamic . |
LockParentForChildInsertRemove |
Controls whether inserting or removing a node requires a write lock on the node's parent (when pessimistic locking is used) or whether it results in an update of the parent node's version (when optimistic locking is used). The default value is |
MarshallerClass |
An instance of |
MultiplexerService |
The JMX object name of the service that defines the JGroups multiplexer. In JBoss AS 5.0 this service is normally defined in the jgroups-multiplexer.sar. This XML attribute can only be handled by the JBoss AS MBean deployment services; if it is included in a file passed to a |
MultiplexerStack |
The name of the JGroups stack to be used with the cache cluster. Stacks are defined in the configuration of the external |
NodeLockingScheme |
May be PESSIMISTIC (default) or OPTIMISTIC. |
ReplicationVersion |
Tells the cache to serialize cluster traffic in a format consistent with that used by the given release of JBoss Cache. Different JBoss Cache versions use different wire formats; setting this attribute tells a cache from a later release to serialize data using the format from an earlier release. This allows caches from different releases to interoperate. For example, a 2.1.0 cache could have this value set to "2.0.0", allowing it to interoperate with a 2.0.0 cache. Valid values are a dot-separated release number, with any final qualifer also separated by a dot, e.g. "2.0.0" or "2.0.0.GA". Values that indicate a 1.x release are not supported in the 2.x series. |
ReplQueueInterval |
Time in milliseconds for elements from the replication queue to be replicated. Only used if |
ReplQueueMaxElements |
Max number of elements in the replication queue until replication kicks in. Only used if |
SyncCommitPhase |
This option is used to control the behaviour of the commit part of a 2-phase commit protocol, when using REPL_SYNC (does not apply to other cache modes). By default this is set to |
SyncReplTimeout |
For synchronous replication: time in milliseconds to wait until replication acks have been received from all nodes in the cluster. It is usually best that this is greater than |
SyncRollbackPhase |
This option is used to control the behaviour of the rollback part of a 2-phase commit protocol, when using REPL_SYNC (does not apply to other cache modes). By default this is set to |
TransactionManagerLookupClass |
The fully qualified name of a class implementing TransactionManagerLookup. Default is JBossTransactionManagerLookup. There is also an option of GenericTransactionManagerLookup for example. |
UseInterceptorMbeans |
Deprecated . Use |
UseRegionBasedMarshalling |
When unmarshalling replicated data, this option specifies whether or not to support use of different classloaders for different cache regions. This defaults to |
UseReplQueue |
For asynchronous replication: whether or not to use a replication queue. Defaults to |
ShutdownHookBehavior |
An optional parameter that controls whether JBoss Cache registers a shutdown hook with the JVM runtime. Allowed values are |
UseLazyDeserialization |
An optional parameter that can be used to enable or disable the use of lazy deserialization for cached objects. Defaults to |
ObjectInputStreamPoolSize and ObjectOutputStreamPoolSize |
Since JBoss Cache 2.1.0, object input and output streams - used to serialize and deserialize RPC calls in a cluster - are pooled to reduce the overhead of constructing such streams. They are reused by making use of special resettable stream implementations.
by default, these stream pools are set at |
The following table describes the statistics currently available and may be collected via JMX.
MBean Name | Attribute | Type | Description |
---|---|---|---|
ActivationInterceptor | Activations | long | Number of passivated nodes that have been activated. |
CacheLoaderInterceptor | CacheLoaderLoads | long | Number of nodes loaded through a cache loader. |
CacheLoaderInterceptor | CacheLoaderMisses | long | Number of unsuccessful attempts to load a node through a cache loader. |
CacheMgmtInterceptor | Hits | long | Number of successful attribute retrievals. |
CacheMgmtInterceptor | Misses | long | Number of unsuccessful attribute retrievals. |
CacheMgmtInterceptor | Stores | long | Number of attribute store operations. |
CacheMgmtInterceptor | Evictions | long | Number of node evictions. |
CacheMgmtInterceptor | NumberOfAttributes | int | Number of attributes currently cached. |
CacheMgmtInterceptor | NumberOfNodes | int | Number of nodes currently cached. |
CacheMgmtInterceptor | ElapsedTime | long | Number of seconds that the cache has been running. |
CacheMgmtInterceptor | TimeSinceReset | long | Number of seconds since the cache statistics have been reset. |
CacheMgmtInterceptor | AverageReadTime | long | Average time in milliseconds to retrieve a cache attribute, including unsuccessful attribute retrievals. |
CacheMgmtInterceptor | AverageWriteTime | long | Average time in milliseconds to write a cache attribute. |
CacheMgmtInterceptor | HitMissRatio | double | Ratio of hits to hits and misses. A hit is a get attribute operation that results in an object being returned to the client. The retrieval may be from a cache loader if the entry isn't in the local cache. |
CacheMgmtInterceptor | ReadWriteRatio | double | Ratio of read operations to write operations. This is the ratio of cache hits and misses to cache stores. |
CacheStoreInterceptor | CacheLoaderStores | long | Number of nodes written to the cache loader. |
InvalidationInterceptor | Invalidations | long | Number of cached nodes that have been invalidated. |
PassivationInterceptor | Passivations | long | Number of cached nodes that have been passivated. |
TxInterceptor | Prepares | long | Number of transaction prepare operations performed by this interceptor. |
TxInterceptor | Commits | long | Number of transaction commit operations performed by this interceptor. |
TxInterceptor | Rollbacks | long | Number of transaction rollbacks operations performed by this interceptor. |
The following table depicts the JMX notifications available for JBoss Cache as well as the cache events to which they correspond. These are the notifications that can be received through the CacheJmxWrapper
MBean. Each notification represents a single event published by JBoss Cache and provides user data corresponding to the parameters of the event.
Notification Type | Notification Data | CacheListener Event | |||
---|---|---|---|---|---|
org.jboss.cache.CacheStarted | String : cache service name | cacheStarted | |||
org.jboss.cache.CacheStopped | String : cache service name | cacheStopped | |||
org.jboss.cache.NodeCreated | String : fqn | NodeCreated | |||
org.jboss.cache.NodeEvicted | String : fqn | NodeEvicted | |||
org.jboss.cache.NodeLoaded | String : fqn | NodeLoaded | |||
org.jboss.cache.NodeModifed | String : fqn | NodeModifed | |||
org.jboss.cache.NodeRemoved | String : fqn | NodeRemoved | |||
org.jboss.cache.NodeVisited | String : fqn | NodeVisited | |||
org.jboss.cache.ViewChange | String : view | ViewChange | |||
org.jboss.cache.NodeActivate |
|
NodeActivate | |||
org.jboss.cache.NodeEvict |
|
NodeEvict | |||
org.jboss.cache.NodeModify |
|
NodeModify | |||
org.jboss.cache.NodePassivate |
|
NodePassivate | |||
org.jboss.cache.NodeRemove |
|
NodeRemove |