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Capítulo 19. Mejorando el rendimiento

19.1. Estrategias de recuperación
19.1.1. Trabajando con asociaciones perezosas
19.1.2. Afinando las estrategias de recuperación
19.1.3. Proxies de asociaciones de un solo extremo
19.1.4. Inicializando colecciones y proxies
19.1.5. Usando recuperación en lotes
19.1.6. Usando recuperación por subselección
19.1.7. Usando recuperación perezosa de propiedades
19.2. El Caché de Segundo Nivel
19.2.1. Mapeos de caché
19.2.2. Estrategia: sólo lectura (read only)
19.2.3. Estrategia: lectura/escritura (read/write)
19.2.4. Estrategia: lectura/escritura no estricta (nonstrict read/write)
19.2.5. Estrategia: transaccional
19.2.6. Cache-provider/concurrency-strategy compatibility
19.3. Gestionando los cachés
19.4. El Caché de Consultas
19.5. Entendiendo el rendimiento de Colecciones
19.5.1. Taxonomia
19.5.2. Las listas, mapas, idbags y conjuntos son las colecciones más eficientes de actualizar
19.5.3. Los Bags y las listas son las colecciones inversas más eficientes
19.5.4. Borrado de un solo tiro
19.6. Monitoreando el rendimiento
19.6.1. Monitoreando una SessionFactory
19.6.2. Métricas

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 define las siguientes estrategias de recuperación:

Hibernate también distingue entre:

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.

La recuperación por selección (la preestablecida) es extremadamente vulnerable a problemas de selección N+1, de modo querríamos habilitar la recuperación por unión (join fetching) en el documento de mapeo:

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

La estrategia de recuperación definida en el documento de mapeo afecta a:

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">

Primero, las instancias de Cat nunca serán objeto de un cast a DomesticCat, incluso aunque la instancia subyacente sea instancia de 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

Sin embargo, la situación no en absoluta tan mala como parece. Aunque tenemos ahora dos referencias a objetos proxy diferentes, la instancia subyacente será aún el mismo objeto:

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();

Las relaciones también son inicializadas perezosamente. Esto significa que debes declarar cualquier propiedad como de tipo Cat, no CatImpl.

Certain operations do not require proxy initialization:

Hibernate detectará las clase persistentes que sobrescriban equals() o 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:

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.

Puedes usar un filtro de colecciones para obtener el tamaño de una colección sin inicializarla:

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

El método createFilter() se usa también para recuperar eficientemente subconjuntos de una colección sin necesidad de inicializar toda la colección:

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"

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">

Con un batch-size de 3, Hibernate cargará 3, 3, 3, 1 colecciones en cuatro SELECTs. Una vez más, el valor del atributo depende del número esperado de colecciones sin inicializar en una Session en particular.

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.

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.

Para habilitar la carga perezosa de propiedades, establece el atributo lazy en tus mapeos de propiedades:

<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.

Para la instrumentación del bytecode, usa la siguiente tarea Ant:

<target name="instrument" depends="compile">
    <taskdef name="instrument" classname="org.hibernate.tool.instrument.InstrumentTask">
        <classpath path="${jar.path}"/>
        <classpath path="${classes.dir}"/>
        <classpath refid="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.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 below. You can also implement your own and plug it in as outlined above. Note that versions prior to 3.2 use EhCache as the default cache provider.

El elemento <cache> de una mapeo de clase o colección tiene la siguiente forma:

    usage="transactional|read-write|nonstrict-read-write|read-only"  (1)

usage especifica la estrategia de caching: transactional, read-write, nonstrict-read-write o read-only


region (optional: defaults to the class or collection role name): specifies the name of the second level cache region


include (optional: defaults to all) non-lazy: specifies that properties of the entity mapped with lazy="true" cannot be cached when attribute-level lazy fetching is enabled

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

El atributo usage especifica una estrategia de concurrencia al caché.

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.

ScrollableResult cats = sess.createQuery("from Cat as cat").scroll(); //a huge result set
while ( cats.next() ) {
    Cat cat = (Cat) cats.get(0);

La Session también provee un método contains() para determinar si una instancia pertenece al caché de la sesión.

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

Para el caché de segundo nivel, hay métodos definidos en SessionFactory para desahuciar el estado en caché de una instancia, clase entera, instancia de colección o rol enter de colección.

sessionFactory.evict(Cat.class, catId); //evict a particular Cat
sessionFactory.evict(Cat.class);  //evict all Cats
sessionFactory.evictCollection("Cat.kittens", catId); //evict a particular collection of kittens
sessionFactory.evictCollection("Cat.kittens"); //evict all kitten collections

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

Para navegar por los contenidos de una región de caché de segundo nivel o de consultas, usa la API de Statistics:

Map cacheEntries = sessionFactory.getStatistics()

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

hibernate.generate_statistics true
hibernate.cache.use_structured_entries true

Query result sets can also be cached. This is only useful for queries that are run frequently with the same parameters. You will first need to enable the query cache:

hibernate.cache.use_query_cache true

This setting creates two new cache regions: one holding cached query result sets (org.hibernate.cache.StandardQueryCache), the other holding timestamps of the most recent updates to queryable tables (org.hibernate.cache.UpdateTimestampsCache). Note that the query cache does not cache the state of the actual entities in the result set; it caches only identifier values and results of value type. The query cache should always be used in conjunction with the second-level cache.

Most queries do not benefit from caching, so by default, queries are not cached. To enable caching, call 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.

If you require fine-grained control over query cache expiration policies, you can specify a named cache region for a particular query by calling Query.setCacheRegion().

List blogs = sess.createQuery("from Blog blog where blog.blogger = :blogger")
    .setEntity("blogger", blogger)

Si la consulta debe forzar un refresco de si región del caché de consultas, debes llamar a Query.setCacheMode(CacheMode.REFRESH). Esto es particularmente útil en casos donde los datos subyacentes pueden haber sido actualizados por medio de un proceso separado (es decir, no modificados a través de Hibernate) y permite a la aplicación refrescar selectivamente conjuntos resultado de consultas en particular. Esto es una alternativa más eficient al desahuciamiento de una región del caché de consultas vía SessionFactory.evictQueries().

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 define tres tipos básicos de colecciones:

Esta clasificación distingue las varias tablas y relaciones de clave foránea pero no nos dice absolutamente todo lo que necesitamos saber sobre el modelo relacional. Para entender completamente la estructura relacional y las características de rendimiento, debemos considerar la estructura de la clave primaria que es usada por Hibernate para actualizar o borrar filas de colección. Esto sugiere la siguiente clasificación:

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.

La optimización no es de mucho uso sin el monitoreo y el acceso a números de rendimiento. Hibernate provee un rango completo de figuras sobre sus operaciones internas. Las estadísticas en Hibernate están disponibles por SessionFactory.

Puedes acceder a las métricas de SessionFactory de dos formas. Tu primera opción es llamar a sessionFactory.getStatistics() y leer o mostrar por pantalla la Statistics por ti mismo.

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:

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:

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().