Hibernate.orgCommunity Documentation

Chapter 20. Improving performance

Table of Contents

20.1. Fetching strategies
20.1.1. Working with lazy associations
20.1.2. Tuning fetch strategies
20.1.3. Single-ended association proxies
20.1.4. Initializing collections and proxies
20.1.5. Using batch fetching
20.1.6. Using subselect fetching
20.1.7. Fetch profiles
20.1.8. Using lazy property fetching
20.2. The Second Level Cache
20.2.1. Cache mappings
20.2.2. Strategy: read only
20.2.3. Strategy: read/write
20.2.4. Strategy: nonstrict read/write
20.2.5. Strategy: transactional
20.2.6. Cache-provider/concurrency-strategy compatibility
20.3. Managing the caches
20.4. The Query Cache
20.4.1. Enabling query caching
20.4.2. Query cache regions
20.5. Understanding Collection performance
20.5.1. Taxonomy
20.5.2. Lists, maps, idbags and sets are the most efficient collections to update
20.5.3. Bags and lists are the most efficient inverse collections
20.5.4. One shot delete
20.6. Monitoring performance
20.6.1. Monitoring a SessionFactory
20.6.2. Metrics

Hibernate uses a fetching strategy to retrieve associated objects if the application needs to navigate the association. Fetch strategies can be declared in the O/R mapping metadata, or over-ridden by a particular HQL or Criteria query.

Hibernate3 defines the following fetching strategies:

  • Join fetching: Hibernate retrieves the associated instance or collection in the same SELECT, using an OUTER JOIN.

  • Select fetching: a second SELECT is used to retrieve the associated entity or collection. Unless you explicitly disable lazy fetching by specifying lazy="false", this second select will only be executed when you access the association.

  • Subselect fetching: a second SELECT is used to retrieve the associated collections for all entities retrieved in a previous query or fetch. Unless you explicitly disable lazy fetching by specifying lazy="false", this second select will only be executed when you access the association.

  • Batch fetching: an optimization strategy for select fetching. Hibernate retrieves a batch of entity instances or collections in a single SELECT by specifying a list of primary or foreign keys.

Hibernate also distinguishes between:

  • Immediate fetching: an association, collection or attribute is fetched immediately when the owner is loaded.

  • Lazy collection fetching: a collection is fetched when the application invokes an operation upon that collection. This is the default for collections.

  • "Extra-lazy" collection fetching: individual elements of the collection are accessed from the database as needed. Hibernate tries not to fetch the whole collection into memory unless absolutely needed. It is suitable for large collections.

  • Proxy fetching: a single-valued association is fetched when a method other than the identifier getter is invoked upon the associated object.

  • "No-proxy" fetching: a single-valued association is fetched when the instance variable is accessed. Compared to proxy fetching, this approach is less lazy; the association is fetched even when only the identifier is accessed. It is also more transparent, since no proxy is visible to the application. This approach requires buildtime bytecode instrumentation and is rarely necessary.

  • Lazy attribute fetching: an attribute or single valued association is fetched when the instance variable is accessed. This approach requires buildtime bytecode instrumentation and is rarely necessary.

We have two orthogonal notions here: when is the association fetched and how is it fetched. It is important that you do not confuse them. We use fetch to tune performance. We can use lazy to define a contract for what data is always available in any detached instance of a particular class.

By default, Hibernate3 uses lazy select fetching for collections and lazy proxy fetching for single-valued associations. These defaults make sense for most associations in the majority of applications.

If you set hibernate.default_batch_fetch_size, Hibernate will use the batch fetch optimization for lazy fetching. This optimization can also be enabled at a more granular level.

Please be aware that access to a lazy association outside of the context of an open Hibernate session will result in an exception. For example:

s = sessions.openSession();
Transaction tx = s.beginTransaction();
User u = (User) s.createQuery("from User u where u.name=:userName")
    .setString("userName", userName).uniqueResult();
Map permissions = u.getPermissions();


Integer accessLevel = (Integer) permissions.get("accounts");  // Error!

Since the permissions collection was not initialized when the Session was closed, the collection will not be able to load its state. Hibernate does not support lazy initialization for detached objects. This can be fixed by moving the code that reads from the collection to just before the transaction is committed.

Alternatively, you can use a non-lazy collection or association, by specifying lazy="false" for the association mapping. However, it is intended that lazy initialization be used for almost all collections and associations. If you define too many non-lazy associations in your object model, Hibernate will fetch the entire database into memory in every transaction.

On the other hand, you can use join fetching, which is non-lazy by nature, instead of select fetching in a particular transaction. We will now explain how to customize the fetching strategy. In Hibernate3, the mechanisms for choosing a fetch strategy are identical for single-valued associations and collections.

Select fetching (the default) is extremely vulnerable to N+1 selects problems, so we might want to enable join fetching in the mapping document:

<set name="permissions"
    <key column="userId"/>
    <one-to-many class="Permission"/>
<many-to-one name="mother" class="Cat" fetch="join"/>

The fetch strategy defined in the mapping document affects:

  • retrieval via get() or load()

  • retrieval that happens implicitly when an association is navigated

  • Criteria queries

  • HQL queries if subselect fetching is used

Irrespective of the fetching strategy you use, the defined non-lazy graph is guaranteed to be loaded into memory. This might, however, result in several immediate selects being used to execute a particular HQL query.

Usually, the mapping document is not used to customize fetching. Instead, we keep the default behavior, and override it for a particular transaction, using left join fetch in HQL. This tells Hibernate to fetch the association eagerly in the first select, using an outer join. In the Criteria query API, you would use setFetchMode(FetchMode.JOIN).

If you want to change the fetching strategy used by get() or load(), you can use a Criteria query. For example:

User user = (User) session.createCriteria(User.class)
                .setFetchMode("permissions", FetchMode.JOIN)
                .add( Restrictions.idEq(userId) )

This is Hibernate's equivalent of what some ORM solutions call a "fetch plan".

A completely different approach to problems with N+1 selects is to use the second-level cache.

Lazy fetching for collections is implemented using Hibernate's own implementation of persistent collections. However, a different mechanism is needed for lazy behavior in single-ended associations. The target entity of the association must be proxied. Hibernate implements lazy initializing proxies for persistent objects using runtime bytecode enhancement which is accessed via the CGLIB library.

At startup, Hibernate3 generates proxies by default for all persistent classes and uses them to enable lazy fetching of many-to-one and one-to-one associations.

The mapping file may declare an interface to use as the proxy interface for that class, with the proxy attribute. By default, Hibernate uses a subclass of the class. The proxied class must implement a default constructor with at least package visibility. This constructor is recommended for all persistent classes.

There are potential problems to note when extending this approach to polymorphic classes.For example:

<class name="Cat" proxy="Cat">
    <subclass name="DomesticCat">

Firstly, instances of Cat will never be castable to DomesticCat, even if the underlying instance is an instance of DomesticCat:

Cat cat = (Cat) session.load(Cat.class, id);  // instantiate a proxy (does not hit the db)
if ( cat.isDomesticCat() ) {                  // hit the db to initialize the proxy
    DomesticCat dc = (DomesticCat) cat;       // Error!

Secondly, it is possible to break proxy ==:

Cat cat = (Cat) session.load(Cat.class, id);            // instantiate a Cat proxy
DomesticCat dc = 
        (DomesticCat) session.load(DomesticCat.class, id);  // acquire new DomesticCat proxy!
System.out.println(cat==dc);                            // false

However, the situation is not quite as bad as it looks. Even though we now have two references to different proxy objects, the underlying instance will still be the same object:

cat.setWeight(11.0);  // hit the db to initialize the proxy
System.out.println( dc.getWeight() );  // 11.0

Third, you cannot use a CGLIB proxy for a final class or a class with any final methods.

Finally, if your persistent object acquires any resources upon instantiation (e.g. in initializers or default constructor), then those resources will also be acquired by the proxy. The proxy class is an actual subclass of the persistent class.

These problems are all due to fundamental limitations in Java's single inheritance model. To avoid these problems your persistent classes must each implement an interface that declares its business methods. You should specify these interfaces in the mapping file where CatImpl implements the interface Cat and DomesticCatImpl implements the interface DomesticCat. For example:

<class name="CatImpl" proxy="Cat">
    <subclass name="DomesticCatImpl" proxy="DomesticCat">

Then proxies for instances of Cat and DomesticCat can be returned by load() or iterate().

Cat cat = (Cat) session.load(CatImpl.class, catid);
Iterator iter = session.createQuery("from CatImpl as cat where cat.name='fritz'").iterate();
Cat fritz = (Cat) iter.next();


list() does not usually return proxies.

Relationships are also lazily initialized. This means you must declare any properties to be of type Cat, not CatImpl.

Certain operations do not require proxy initialization:

  • equals(): if the persistent class does not override equals()

  • hashCode(): if the persistent class does not override hashCode()

  • The identifier getter method

Hibernate will detect persistent classes that override equals() or hashCode().

By choosing lazy="no-proxy" instead of the default lazy="proxy", you can avoid problems associated with typecasting. However, buildtime bytecode instrumentation is required, and all operations will result in immediate proxy initialization.

A LazyInitializationException will be thrown by Hibernate if an uninitialized collection or proxy is accessed outside of the scope of the Session, i.e., when the entity owning the collection or having the reference to the proxy is in the detached state.

Sometimes a proxy or collection needs to be initialized before closing the Session. You can force initialization by calling cat.getSex() or cat.getKittens().size(), for example. However, this can be confusing to readers of the code and it is not convenient for generic code.

The static methods Hibernate.initialize() and Hibernate.isInitialized(), provide the application with a convenient way of working with lazily initialized collections or proxies. Hibernate.initialize(cat) will force the initialization of a proxy, cat, as long as its Session is still open. Hibernate.initialize( cat.getKittens() ) has a similar effect for the collection of kittens.

Another option is to keep the Session open until all required collections and proxies have been loaded. In some application architectures, particularly where the code that accesses data using Hibernate, and the code that uses it are in different application layers or different physical processes, it can be a problem to ensure that the Session is open when a collection is initialized. There are two basic ways to deal with this issue:

  • In a web-based application, a servlet filter can be used to close the Session only at the end of a user request, once the rendering of the view is complete (the Open Session in View pattern). Of course, this places heavy demands on the correctness of the exception handling of your application infrastructure. It is vitally important that the Session is closed and the transaction ended before returning to the user, even when an exception occurs during rendering of the view. See the Hibernate Wiki for examples of this "Open Session in View" pattern.

  • In an application with a separate business tier, the business logic must "prepare" all collections that the web tier needs before returning. This means that the business tier should load all the data and return all the data already initialized to the presentation/web tier that is required for a particular use case. Usually, the application calls Hibernate.initialize() for each collection that will be needed in the web tier (this call must occur before the session is closed) or retrieves the collection eagerly using a Hibernate query with a FETCH clause or a FetchMode.JOIN in Criteria. This is usually easier if you adopt the Command pattern instead of a Session Facade.

  • You can also attach a previously loaded object to a new Session with merge() or lock() before accessing uninitialized collections or other proxies. Hibernate does not, and certainly should not, do this automatically since it would introduce impromptu transaction semantics.

Sometimes you do not want to initialize a large collection, but still need some information about it, like its size, for example, or a subset of the data.

You can use a collection filter to get the size of a collection without initializing it:

( (Integer) s.createFilter( collection, "select count(*)" ).list().get(0) ).intValue()

The createFilter() method is also used to efficiently retrieve subsets of a collection without needing to initialize the whole collection:

s.createFilter( lazyCollection, "").setFirstResult(0).setMaxResults(10).list();

Using batch fetching, Hibernate can load several uninitialized proxies if one proxy is accessed. Batch fetching is an optimization of the lazy select fetching strategy. There are two ways you can configure batch fetching: on the class level and the collection level.

Batch fetching for classes/entities is easier to understand. Consider the following example: at runtime you have 25 Cat instances loaded in a Session, and each Cat has a reference to its owner, a Person. The Person class is mapped with a proxy, lazy="true". If you now iterate through all cats and call getOwner() on each, Hibernate will, by default, execute 25 SELECT statements to retrieve the proxied owners. You can tune this behavior by specifying a batch-size in the mapping of Person:

<class name="Person" batch-size="10">...</class>

Hibernate will now execute only three queries: the pattern is 10, 10, 5.

You can also enable batch fetching of collections. For example, if each Person has a lazy collection of Cats, and 10 persons are currently loaded in the Session, iterating through all persons will generate 10 SELECTs, one for every call to getCats(). If you enable batch fetching for the cats collection in the mapping of Person, Hibernate can pre-fetch collections:

<class name="Person">
    <set name="cats" batch-size="3">

With a batch-size of 3, Hibernate will load 3, 3, 3, 1 collections in four SELECTs. Again, the value of the attribute depends on the expected number of uninitialized collections in a particular Session.

Batch fetching of collections is particularly useful if you have a nested tree of items, i.e. the typical bill-of-materials pattern. However, a nested set or a materialized path might be a better option for read-mostly trees.

Another way to affect the fetching strategy for loading associated objects is through something called a fetch profile, which is a named configuration associated with the org.hibernate.SessionFactory but enabled, by name, on the org.hibernate.Session. Once enabled on a org.hibernate.Session, the fetch profile will be in affect for that org.hibernate.Session until it is explicitly disabled.

So what does that mean? Well lets explain that by way of an example which show the different available approaches to configure a fetch profile:

Now normally when you get a reference to a particular customer, that customer's set of orders will be lazy meaning we will not yet have loaded those orders from the database. Normally this is a good thing. Now lets say that you have a certain use case where it is more efficient to load the customer and their orders together. One way certainly is to use "dynamic fetching" strategies via an HQL or criteria queries. But another option is to use a fetch profile to achieve that. The following code will load both the customer andtheir orders:


@FetchProfile definitions are global and it does not matter on which class you place them. You can place the @FetchProfile annotation either onto a class or package (package-info.java). In order to define multiple fetch profiles for the same class or package @FetchProfiles can be used.

Currently only join style fetch profiles are supported, but they plan is to support additional styles. See HHH-3414 for details.

Hibernate3 supports the lazy fetching of individual properties. This optimization technique is also known as fetch groups. Please note that this is mostly a marketing feature; optimizing row reads is much more important than optimization of column reads. However, only loading some properties of a class could be useful in extreme cases. For example, when legacy tables have hundreds of columns and the data model cannot be improved.

To enable lazy property loading, set the lazy attribute on your particular property mappings:

<class name="Document">
       <id name="id">
        <generator class="native"/>
    <property name="name" not-null="true" length="50"/>
    <property name="summary" not-null="true" length="200" lazy="true"/>
    <property name="text" not-null="true" length="2000" lazy="true"/>

Lazy property loading requires buildtime bytecode instrumentation. If your persistent classes are not enhanced, Hibernate will ignore lazy property settings and return to immediate fetching.

For bytecode instrumentation, use the following Ant task:

<target name="instrument" depends="compile">
    <taskdef name="instrument" classname="org.hibernate.tool.instrument.InstrumentTask">
        <classpath path="${jar.path}"/>
        <classpath path="${classes.dir}"/>
        <classpath refxml:id="lib.class.path"/>

    <instrument verbose="true">
        <fileset dir="${testclasses.dir}/org/hibernate/auction/model">
            <include name="*.class"/>

A different way of avoiding unnecessary column reads, at least for read-only transactions, is to use the projection features of HQL or Criteria queries. This avoids the need for buildtime bytecode processing and is certainly a preferred solution.

You can force the usual eager fetching of properties using fetch all properties in HQL.

A Hibernate Session is a transaction-level cache of persistent data. It is possible to configure a cluster or JVM-level (SessionFactory-level) cache on a class-by-class and collection-by-collection basis. You can even plug in a clustered cache. Be aware that caches are not aware of changes made to the persistent store by another application. They can, however, be configured to regularly expire cached data.

You have the option to tell Hibernate which caching implementation to use by specifying the name of a class that implements org.hibernate.cache.spi.CacheProvider using the property hibernate.cache.provider_class. Hibernate is bundled with a number of built-in integrations with the open-source cache providers that are listed in Table 20.1, “Cache Providers”. You can also implement your own and plug it in as outlined above. Note that versions prior to Hibernate 3.2 use EhCache as the default cache provider.

As we have done in previous chapters we are looking at the two different possibiltites to configure caching. First configuration via annotations and then via Hibernate mapping files.

By default, entities are not part of the second level cache and we recommend you to stick to this setting. However, you can override this by setting the shared-cache-mode element in your persistence.xml file or by using the javax.persistence.sharedCache.mode property in your configuration. The following values are possible:

  • ENABLE_SELECTIVE (Default and recommended value): entities are not cached unless explicitly marked as cacheable.

  • DISABLE_SELECTIVE: entities are cached unless explicitly marked as not cacheable.

  • ALL: all entities are always cached even if marked as non cacheable.

  • NONE: no entity are cached even if marked as cacheable. This option can make sense to disable second-level cache altogether.

The cache concurrency strategy used by default can be set globaly via the hibernate.cache.default_cache_concurrency_strategy configuration property. The values for this property are:

  • read-only

  • read-write

  • nonstrict-read-write

  • transactional


It is recommended to define the cache concurrency strategy per entity rather than using a global one. Use the @org.hibernate.annotations.Cache annotation for that.

Hibernate also let's you cache the content of a collection or the identifiers if the collection contains other entities. Use the @Cache annotation on the collection property.

Example 20.7, “@Cache annotation with attributes”shows the @org.hibernate.annotations.Cache annotations with its attributes. It allows you to define the caching strategy and region of a given second level cache.

Let's now take a look at Hibernate mapping files. There the <cache> element of a class or collection mapping is used to configure the second level cache. Looking at Example 20.8, “The Hibernate <cache> mapping element” the parallels to anotations is obvious.

Alternatively to <cache>, you can use <class-cache> and <collection-cache> elements in hibernate.cfg.xml.

Let's now have a closer look at the different usage strategies

Whenever you pass an object to save(), update() or saveOrUpdate(), and whenever you retrieve an object using load(), get(), list(), iterate() or scroll(), that object is added to the internal cache of the Session.

When flush() is subsequently called, the state of that object will be synchronized with the database. If you do not want this synchronization to occur, or if you are processing a huge number of objects and need to manage memory efficiently, the evict() method can be used to remove the object and its collections from the first-level cache.

The Session also provides a contains() method to determine if an instance belongs to the session cache.

To evict all objects from the session cache, call Session.clear()

For the second-level cache, there are methods defined on SessionFactory for evicting the cached state of an instance, entire class, collection instance or entire collection role.

The CacheMode controls how a particular session interacts with the second-level cache:

  • CacheMode.NORMAL: will read items from and write items to the second-level cache

  • CacheMode.GET: will read items from the second-level cache. Do not write to the second-level cache except when updating data

  • CacheMode.PUT: will write items to the second-level cache. Do not read from the second-level cache

  • CacheMode.REFRESH: will write items to the second-level cache. Do not read from the second-level cache. Bypass the effect of hibernate.cache.use_minimal_puts forcing a refresh of the second-level cache for all items read from the database

To browse the contents of a second-level or query cache region, use the Statistics API:

You will need to enable statistics and, optionally, force Hibernate to keep the cache entries in a more readable format:

Query result sets can also be cached. This is only useful for queries that are run frequently with the same parameters.

Caching of query results introduces some overhead in terms of your applications normal transactional processing. For example, if you cache results of a query against Person Hibernate will need to keep track of when those results should be invalidated because changes have been committed against Person. That, coupled with the fact that most applications simply gain no benefit from caching query results, leads Hibernate to disable caching of query results by default. To use query caching, you will first need to enable the query cache:

hibernate.cache.use_query_cache true

This setting creates two new cache regions:

  • org.hibernate.cache.internal.StandardQueryCache, holding the cached query results

  • org.hibernate.cache.spi.UpdateTimestampsCache, holding timestamps of the most recent updates to queryable tables. These are used to validate the results as they are served from the query cache.


If you configure your underlying cache implementation to use expiry or timeouts is very important that the cache timeout of the underlying cache region for the UpdateTimestampsCache be set to a higher value than the timeouts of any of the query caches. In fact, we recommend that the the UpdateTimestampsCache region not be configured for expiry at all. Note, in particular, that an LRU cache expiry policy is never appropriate.

As mentioned above, most queries do not benefit from caching or their results. So by default, individual queries are not cached even after enabling query caching. To enable results caching for a particular query, call org.hibernate.Query.setCacheable(true). This call allows the query to look for existing cache results or add its results to the cache when it is executed.


The query cache does not cache the state of the actual entities in the cache; it caches only identifier values and results of value type. For this reaso, the query cache should always be used in conjunction with the second-level cache for those entities expected to be cached as part of a query result cache (just as with collection caching).

In the previous sections we have covered collections and their applications. In this section we explore some more issues in relation to collections at runtime.

Hibernate defines three basic kinds of collections:

  • collections of values

  • one-to-many associations

  • many-to-many associations

This classification distinguishes the various table and foreign key relationships but does not tell us quite everything we need to know about the relational model. To fully understand the relational structure and performance characteristics, we must also consider the structure of the primary key that is used by Hibernate to update or delete collection rows. This suggests the following classification:

  • indexed collections

  • sets

  • bags

All indexed collections (maps, lists, and arrays) have a primary key consisting of the <key> and <index> columns. In this case, collection updates are extremely efficient. The primary key can be efficiently indexed and a particular row can be efficiently located when Hibernate tries to update or delete it.

Sets have a primary key consisting of <key> and element columns. This can be less efficient for some types of collection element, particularly composite elements or large text or binary fields, as the database may not be able to index a complex primary key as efficiently. However, for one-to-many or many-to-many associations, particularly in the case of synthetic identifiers, it is likely to be just as efficient. If you want SchemaExport to actually create the primary key of a <set>, you must declare all columns as not-null="true".

<idbag> mappings define a surrogate key, so they are efficient to update. In fact, they are the best case.

Bags are the worst case since they permit duplicate element values and, as they have no index column, no primary key can be defined. Hibernate has no way of distinguishing between duplicate rows. Hibernate resolves this problem by completely removing in a single DELETE and recreating the collection whenever it changes. This can be inefficient.

For a one-to-many association, the "primary key" may not be the physical primary key of the database table. Even in this case, the above classification is still useful. It reflects how Hibernate "locates" individual rows of the collection.

Optimization is not much use without monitoring and access to performance numbers. Hibernate provides a full range of figures about its internal operations. Statistics in Hibernate are available per SessionFactory.

You can access SessionFactory metrics in two ways. Your first option is to call sessionFactory.getStatistics() and read or display the Statistics yourself.

Hibernate can also use JMX to publish metrics if you enable the StatisticsService MBean. You can enable a single MBean for all your SessionFactory or one per factory. See the following code for minimalistic configuration examples:

// MBean service registration for a specific SessionFactory
Hashtable tb = new Hashtable();
tb.put("type", "statistics");
tb.put("sessionFactory", "myFinancialApp");
ObjectName on = new ObjectName("hibernate", tb); // MBean object name

StatisticsService stats = new StatisticsService(); // MBean implementation
stats.setSessionFactory(sessionFactory); // Bind the stats to a SessionFactory
server.registerMBean(stats, on); // Register the Mbean on the server
// MBean service registration for all SessionFactory's
Hashtable tb = new Hashtable();
tb.put("type", "statistics");
tb.put("sessionFactory", "all");
ObjectName on = new ObjectName("hibernate", tb); // MBean object name

StatisticsService stats = new StatisticsService(); // MBean implementation
server.registerMBean(stats, on); // Register the MBean on the server

You can activate and deactivate the monitoring for a SessionFactory:

  • at configuration time, set hibernate.generate_statistics to false

  • at runtime: sf.getStatistics().setStatisticsEnabled(true) or hibernateStatsBean.setStatisticsEnabled(true)

Statistics can be reset programmatically using the clear() method. A summary can be sent to a logger (info level) using the logSummary() method.

Hibernate provides a number of metrics, from basic information to more specialized information that is only relevant in certain scenarios. All available counters are described in the Statistics interface API, in three categories:

  • Metrics related to the general Session usage, such as number of open sessions, retrieved JDBC connections, etc.

  • Metrics related to the entities, collections, queries, and caches as a whole (aka global metrics).

  • Detailed metrics related to a particular entity, collection, query or cache region.

For example, you can check the cache hit, miss, and put ratio of entities, collections and queries, and the average time a query needs. Be aware that the number of milliseconds is subject to approximation in Java. Hibernate is tied to the JVM precision and on some platforms this might only be accurate to 10 seconds.

Simple getters are used to access the global metrics (i.e. not tied to a particular entity, collection, cache region, etc.). You can access the metrics of a particular entity, collection or cache region through its name, and through its HQL or SQL representation for queries. Please refer to the Statistics, EntityStatistics, CollectionStatistics, SecondLevelCacheStatistics, and QueryStatistics API Javadoc for more information. The following code is a simple example:

Statistics stats = HibernateUtil.sessionFactory.getStatistics();

double queryCacheHitCount  = stats.getQueryCacheHitCount();
double queryCacheMissCount = stats.getQueryCacheMissCount();
double queryCacheHitRatio =
  queryCacheHitCount / (queryCacheHitCount + queryCacheMissCount);

log.info("Query Hit ratio:" + queryCacheHitRatio);

EntityStatistics entityStats =
  stats.getEntityStatistics( Cat.class.getName() );
long changes =
        + entityStats.getUpdateCount()
        + entityStats.getDeleteCount();
log.info(Cat.class.getName() + " changed " + changes + "times"  );

You can work on all entities, collections, queries and region caches, by retrieving the list of names of entities, collections, queries and region caches using the following methods: getQueries(), getEntityNames(), getCollectionRoleNames(), and getSecondLevelCacheRegionNames().