1) Introduction
While working with Hibernate web applications we will face so many problems in its performance due to database traffic. That to when the database traffic is very heavy . Actually hibernate is well used just because of its high performance only. So some
techniques are necessary to maintain its performance. Caching is the best technique to solve this problem. In this article we will discuss about, how we can improve the
performance of Hibernate web applications using caching.
The performance of Hibernate web applications is improved using caching by
optimizing the database applications. The cache actually stores the data already loaded from the database, so that the traffic between our application and the database will be reduced when the application want to access that data again. Maximum the application will works with the data in the cache only. Whenever some another data is needed, the
database will be accessed. Because the time needed to access the database is more when compared with the time needed to access the cache. So obviously the access time and traffic will be reduced between the application and the database. Here the cache stores only the data related to current running application. In order to do that, the cache must be cleared time to time whenever the applications are changing. Here are the
contents. • Introduction. ○ First-level cache. ○ Second-level cache. • Cache Implementations.
○
EHCache.○
OSCache.○
SwarmCache.○
JBoss TreeCache.•
Caching Stringategies. ○ Read-only. ○ Read-Write.○
Nonstriict read-write. ○ Transactional. • Configuration.•
<cache> element.• Caching the queries.
• Custom Cache. ○ Configuration.
○
Implementation :: ExampleCustomCache.• Something about Caching. ○ Performance.
○ About Caching.
Hibernate uses two different caches for objects: first-level cache and second-level cache..
1.1) First-level cache
First-level cache always Associates with the Session object. Hibernate uses this cache by default. Here, it processes one transaction after another one, means wont process one transaction many times. Mainly it reduces the number of SQL queries it needs to generate within a given transaction. That is instead of updating after every modification done in the transaction, it updates the transaction only at the end of the transaction.
1.2) Second-level cache
Second-level cache always associates with the Session Factory object. While running the transactions, in between it loads the objects at the Session Factory level, so that those objects will available to the entire application, don’t bounds to single user. Since the objects are already loaded in the cache, whenever an object is returned by the query, at that time no need to go for a database transaction. In this way the second level cache works. Here we can use query level cache also. Later we will discuss about it.
2) Cache Implementations
Hibernate supports four open-source cache implementations named EHCache (Easy Hibernate Cache), OSCache (Open Symphony Cache), Swarm Cache, and JBoss Tree Cache. Each cache has different performance, memory use, and configuration possibilities.
2.1) 2.1 EHCache (Easy Hibernate Cache) (org.hibernate.cache.EhCacheProvider)
•
It is fast.•
lightweight.•
Easy-to-use.•
Supports read-only and read/write caching.•
Supports memory-based and disk-based caching.•
Does not support clustering.2.2)OSCache (Open Symphony Cache) (org.hibernate.cache.OSCacheProvider)
•
It is a powerful .•
flexible package•
supports read-only and read/write caching.•
Supports memory- based and disk-based caching.•
Provides basic support for clustering via either JavaGroups or JMS. 2.3)SwarmCache (org.hibernate.cache.SwarmCacheProvider)•
is a cluster-based caching.•
supports read-only or nonstrict read/write caching .•
appropriate for applications those have more read operations than write operations.2.4)JBoss TreeCache (org.hibernate.cache.TreeCacheProvider)
•
is a powerful replicated and transactional cache.•
useful when we need a true transaction-capable caching architecture .3) Caching Stringategies
Important thing to remembered while studying this one is none of the cache providers support all of the cache concurrency strategies.
3.1) Read-only
•
Useful for data that is read frequently but never updated.•
It is Simple .• Best performer among the all.
Advantage if this one is, It is safe for using in a cluster. Here is an example for using the read-only cache strategy.
<class name="abc.mutable " mutable="true "> <cache usage="read-only"/>
.... </class> 3.2) Read-Write
•
Used when our data needs to be updated.•
It’s having more overhead than read-only caches.•
When Session.close() or Session.disconnect() is called the transaction should be completed in an environment where JTA is no used.•
It is never used if serializable transaction isolation level is required.•
In a JTA environment, for obtaining the JTA TransactionManager we must specify the property hibernate.transaction.manager_lookup_class.•
To use it in a cluster the cache implementation must support locking. Here is an example for using the read-write cache stringategy.<class name="abc.xyz" .... > <cache usage="read-write"/> …. <set name="yuv" ... > <cache usage="read-write"/> …. </set> </class> 3.3) Nonstrict read-write
•
Needed if the application needs to update data rarely.•
we must specify hibernate.transaction.manager_lookup_class to use this in a JTA environment .•
The transaction is completed when Session.close() or Session.disconnect() is called In other environments (except JTA) .Here is an example for using the nonstrict read-write cache stringategy.
<class name="abc.xyz" .... >
<cache usage=" nonstringict-read-write"/> ….
</class>
3.4) Transactional
•
only used in JTA environment.4) Configuration
For configuring cache the hibernate.cfg.xml file is used. A typical configuration file is shown below. <hibernate-configuration> <session-factory> ... <property name="hibernate.cache.provider_class"> org.hibernate.cache.EHCacheProvider </property> ... </session-factory> </hibernate-configuration>
The name in <property> tag must be hibernate.cache.provider_class for activating second-level cache. We can use hibernate.cache.use_second_level_cache property, which allows you to activate and deactivate the second-level cache. By default, the second-level cache is activated and uses the EHCache.
5) <cache> element
The <cache> element of a class has the following form:
<cache
usage=" caching `"
region="RegionName" include="all | non-lazy"/>
•
usage (mandatory) specifies the caching stringategy: transactional, read-write, nonstringict-read-write or read-only.•
region (optional) specifies the name of the second level cache region .•
include (optional) non-lazy specifies that properties of the entity mapped with lazy="true" may not be cached when attribute-level lazy fetching is enabled. The <cache> element of a class is also called as the collection mapping.6) Caching the queries
Until now we saw only caching the transactions. Now we are going to study about the caching the queries.Suppose some queries are running frequently with same set of parameters, those queries can be cached. We have to set
hibernate.cache.use_query_cache to true by calling Query.setCacheable(true) for enabling the query cache. Actually updates in the queries occur very often. So, for query caching, two cache regions are necessary.
•
For storing the results.( cache identifier values and results of value type only). • For storing the most recent updates.Query cache always used second-level cache only. Queries wont cached by default. Here is an example implementation of query cache.
List xyz = abc.createQuery("Query") .setEntity("…",….)
.setMaxResults(some integer) .setCacheable(true)
.setCacheRegion("region name") .list();
We can cache the exact results of a query by setting the
hibernate.cache.use_query_cache property in the hibernate.cfg.xml file to true as follows:
<property name="hibernate.cache.use_query_cache">true</property> Then, we can use the setCacheable() method on any query we wish to cache.
7) Custom Cache
To understand the relation between cache and the application the cache implementation must generate statistics of cache usage.
7.1) Custom Cache Configuration
In the hibernate.properties file set the property hibernate.cache.provider_class = examples.customCache.customCacheProvider.
7.2) Implementation :: ExampleCustomCache
Here is the implementation of ExampleCustomCache. Here it uses Hashtable for storing the cache statistics.
package examples.ExampleCustomCache; import net.sf.hibernate.cache;
import java.util;
import org.apache.commons.logging;
public class ExampleCustomCache implements Cache {
public Log log = LogFactory.getLog(ExapleCustomCache.class); public Map table = new Hashtable(100);
int hits, misses, newhits, newmisses, locks, unlocks, remhits, remmisses, clears, destroys;
public void statCount(StringBuffer input, String string1, int value) {
input.append(string1 + " " + value); }
public String lStats() {
StringBuffer res = new StringBuffer(); statCount(res, "hits", hits);
statCount(res, "misses", misses); statCount(res, "new hits", newhits); statCount(res, "new misses", newmisses); statCount(res, "locks", lock);
statCount(res, "unlocks", unlock); statCount(res, "rem hits ", remhits); statCount(res, "rem misses", remmisses); statCount(res, "clear", clears);
return res.toString(); }
public Object get(Object key) {
if (table.get(key) == null) {
log.info("get " + key.toString () + " missed"); misses++;
} else {
log.info("get " + key.toString () + " hit"); hits++;
}
return table.get(key); }
public void put(Object key, Object value) { log.info("put " + key.toString ()); if (table.containsKey(key)) { newhits++; } else { newmisses++; } table.put(key, value); }
public void remove(Object key) { log.info("remove " + key.toString ()); if (table.containsKey(key)) { remhits++; } else { remmisses++; } table.remove(key); }
public void clear() {
log.info("clear"); clears++;
table.clear(); }
public void destroy() {
log.info("destringoy "); destroys++;
public void lock(Object key) { log.info("lock " + key.toStringing()); locks++; }
public void unlock(Object key) {
log.info("unlock " + key.toStringing()); unlocks++;
}
Here is the example of Custom Cache. Package examples.ExapleCustomCache; import java.util;
import net.sf.hibernate.cache;
public class ExampleCustomCacheProvider implements CacheProvider {
public Hashtable cacheList = new Hashtable(); public Hashtable getCacheList()
{
return cacheList; }
public Stringing cacheInfo () {
StringingBuffer aa = new StringingBuffer(); Enumeration cList = cacheList.keys();
while (cList.hasMoreElements()) {
Stringing cName = cList.nextElement().toStringing(); aa.append(cName);
ExapleCustomCache myCache = (ExapleCustomCache)cacheList.get(cName); aa.append(myCache.lStats()); } return aa.toStringing(); } public ExampleCustomCacheProvider() { }
public Cache bCache(String string2, Properties properties) {
ExampleCustomCache nC = new ExapleCustomCache(); cacheList.put(string2, nC);
return nC; }
}
8) Something about Caching
8.1) PerformanceHibernate provides some metrics for measuring the performance of caching, which are all described in the Statistics interface API, in three categories:
•
Metrics related to the general Session usage.•
Metrics related to the entities, collections, queries, and cache as a whole.•
Detailed metrics related to a particular entity, collection, query or cache region. 8.2) About Caching•
All objects those are passed to methods save(), update() or saveOrUpdate() or those you get from load(), get(), list(), iterate() or scroll() will be saved into cache.•
flush() is used to synchronize the object with database and evict() is used to delete it from cache.•
contains() used to find whether the object belongs to the cache or not.•
Session.clear() used to delete all objects from the cache .•
Suppose the query wants to force a refresh of its query cache region, we should call Query.setCacheMode(CacheMode.REFRESH).9) Conclusion
Caching is good one and hibernate found a good way to implement it for improving its performance in web applications especially when more database traffic occurs. If we implement it very correctly, we will get our applications to be running at their maximum capacities. I will cover more about the caching implementations in my coming articles. Try to get full coding guidelines before going to implement this.
