- 19.1. Stratégies de chargement
- 19.1.1. Travailler avec des associations chargées tardivement
- 19.1.2. Personnalisation des stratégies de chargement
- 19.1.3. Proxys pour des associations vers un seul objet
- 19.1.4. Initialisation des collections et des proxys
- 19.1.5. Utiliser le chargement par lot
- 19.1.6. Utilisation du chargement par sous select
- 19.1.7. Utiliser le chargement tardif des propriétés
- 19.2. Le cache de second niveau
- 19.3. Gérer les caches
- 19.4. Le cache de requêtes
- 19.5. Comprendre les performances des Collections
- 19.6. Moniteur de performance
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 définit les stratégies de chargement suivantes :
Join fetching: Hibernate retrieves the associated instance or collection in the same
SELECT, using anOUTER JOIN.Select fetching: a second
SELECTis used to retrieve the associated entity or collection. Unless you explicitly disable lazy fetching by specifyinglazy="false", this second select will only be executed when you access the association.Subselect fetching: a second
SELECTis used to retrieve the associated collections for all entities retrieved in a previous query or fetch. Unless you explicitly disable lazy fetching by specifyinglazy="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
SELECTby specifying a list of primary or foreign keys.
Hibernate fait également la distinction entre :
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();
tx.commit();
s.close();
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.
Le chargement par select (mode par défaut) est très vulnérable au problème du N+1 selects, du coup vous pouvez avoir envie d'activer le chargement par jointure dans les fichiers de mapping :
<set name="permissions"
fetch="join">
<key column="userId"/>
<one-to-many class="Permission"/>
</set<many-to-one name="mother" class="Cat" fetch="join"/>
La stratégie de chargement définie à l'aide du mot fetch dans les fichiers de mapping affecte :
La récupération via
get()ouload()La récupération implicite lorsque l'on navigue à travers une association
Les requêtes de type
CriteriaLes requêtes HQL si l'on utilise le chargement par
subselect
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) )
.uniqueResult();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">
.....
</subclass>
</class>Tout d'abord, les instances de Cat ne pourront jamais être "castées" en DomesticCat, même si l'instance sous jacente est une instance 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); // falseCette situation n'est pas si mauvaise qu'il n'y parait. Même si nous avons deux références à deux objets proxys différents, l'instance de base sera quand même le même objet :
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">
.....
</subclass>
</class>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();Note
list() does not usually return proxies.
Les relations sont aussi initialisées tardivement. Ceci signifie que vous devez déclarer chaque propriété comme étant de type Cat, et non CatImpl.
Certain operations do not require proxy initialization:
equals(): if the persistent class does not overrideequals()hashCode(): if the persistent class does not overridehashCode()Le getter de l'identifiant
Hibernate détectera les classes qui surchargent equals() ou 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
Sessiononly 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 theSessionis 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 aFETCHclause or aFetchMode.JOINinCriteria. 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
Sessionwithmerge()orlock()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.
Vous pouvez utiliser un filtre de collection pour récupérer sa taille sans l'initialiser :
( (Integer) s.createFilter( collection, "select count(*)" ).list().get(0) ).intValue()
La méthode createFilter() est également utilisée pour récupérer de manière efficace des sous ensembles d'une collection sans avoir besoin de l'initialiser dans son ensemble.
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">
...
</set>
</class>Avec une taille de lot (batch-size) de 3, Hibernate chargera respectivement 3, 3, 3, et 1 collections en quatre SELECTs. Encore une fois, la valeur de l'attribut dépend du nombre de collections non initialisées dans une Session particulière.
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.
If one lazy collection or single-valued proxy has to be fetched, Hibernate will load all of them, re-running the original query in a subselect. This works in the same way as batch-fetching but without the piecemeal loading.
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.
Pour activer le chargement tardif d'une propriété, il faut mettre l'attribut lazy sur une propriété particulière du mapping :
<class name="Document">
<id name="id">
<generator class="native"/>
</id>
<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"/>
</class>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.
Pour l'instrumentation du bytecode vous pouvez utiliser la tâche Ant suivante :
<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"/>
</taskdef>
<instrument verbose="true">
<fileset dir="${testclasses.dir}/org/hibernate/auction/model">
<include name="*.class"/>
</fileset>
</instrument>
</target>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.
Tableau 19.1. Fournisseur de cache
| Cache | Classe pourvoyeuse | Type | Support en Cluster | Cache de requêtes supporté |
|---|---|---|---|---|
| Hashtable (not intended for production use) | org.hibernate.cache.HashtableCacheProvider | mémoire | yes | |
| EHCache | org.hibernate.cache.EhCacheProvider | mémoire, disque | yes | |
| OSCache | org.hibernate.cache.OSCacheProvider | mémoire, disque | yes | |
| SwarmCache | org.hibernate.cache.SwarmCacheProvider | en cluster (multicast ip) | oui (invalidation de cluster) | |
| JBoss Cache 1.x | org.hibernate.cache.TreeCacheProvider | en cluster (multicast ip), transactionnel | oui (replication) | oui (horloge sync. nécessaire) |
| JBoss Cache 2 | org.hibernate.cache.jbc2.JBossCacheRegionFactory | en cluster (multicast ip), transactionnel | yes (replication or invalidation) | oui (horloge sync. nécessaire) |
L'élément <cache> d'une classe ou d'une collection à la forme suivante :
<cache
usage="transactional|read-write|nonstrict-read-write|read-only" 
region="RegionName" 
include="all|non-lazy" 
/> |
|
|
|
|
|
Alternatively, you can specify <class-cache> and <collection-cache> elements in hibernate.cfg.xml.
L'attribut usage spécifie une stratégie de concurrence d'accès au cache.
If your application needs to read, but not modify, instances of a persistent class, a read-only cache can be used. This is the simplest and optimal performing strategy. It is even safe for use in a cluster.
<class name="eg.Immutable" mutable="false">
<cache usage="read-only"/>
....
</class>If the application needs to update data, a read-write cache might be appropriate. This cache strategy should never be used if serializable transaction isolation level is required. If the cache is used in a JTA environment, you must specify the property hibernate.transaction.manager_lookup_class and naming a strategy for obtaining the JTA TransactionManager. In other environments, you should ensure that the transaction is completed when Session.close() or Session.disconnect() is called. If you want to use this strategy in a cluster, you should ensure that the underlying cache implementation supports locking. The built-in cache providers do not support locking.
<class name="eg.Cat" .... >
<cache usage="read-write"/>
....
<set name="kittens" ... >
<cache usage="read-write"/>
....
</set>
</class>If the application only occasionally needs to update data (i.e. if it is extremely unlikely that two transactions would try to update the same item simultaneously), and strict transaction isolation is not required, a nonstrict-read-write cache might be appropriate. If the cache is used in a JTA environment, you must specify hibernate.transaction.manager_lookup_class. In other environments, you should ensure that the transaction is completed when Session.close() or Session.disconnect() is called.
The transactional cache strategy provides support for fully transactional cache providers such as JBoss TreeCache. Such a cache can only be used in a JTA environment and you must specify hibernate.transaction.manager_lookup_class.
Important
None of the cache providers support all of the cache concurrency strategies.
The following table shows which providers are compatible with which concurrency strategies.
Tableau 19.2. Stratégie de concurrence du cache
| Cache | read-only (lecture seule) | nonstrict-read-write (lecture-écriture non stricte) | read-write (lecture-ériture) | transactional (transactionnel) |
|---|---|---|---|---|
| Hashtable (not intended for production use) | yes | yes | yes | |
| EHCache | yes | yes | yes | |
| OSCache | yes | yes | yes | |
| SwarmCache | yes | yes | ||
| JBoss Cache 1.x | yes | yes | ||
| JBoss Cache 2 | yes | yes |
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);
doSomethingWithACat(cat);
sess.evict(cat);
}La Session dispose aussi de la méthode contains() pour déterminer si une instance appartient au cache de la session.
To evict all objects from the session cache, call Session.clear()
Pour le cache de second niveau, il existe des méthodes définies dans SessionFactory pour retirer des instances du cache, la classe entière, une instance de collection ou le rôle entier d'une collection.
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 collectionsThe 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 cacheCacheMode.GET: will read items from the second-level cache. Do not write to the second-level cache except when updating dataCacheMode.PUT: will write items to the second-level cache. Do not read from the second-level cacheCacheMode.REFRESH: will write items to the second-level cache. Do not read from the second-level cache. Bypass the effect ofhibernate.cache.use_minimal_putsforcing a refresh of the second-level cache for all items read from the database
Pour parcourir le contenu du cache de second niveau ou la région du cache dédiée au requêtes, vous pouvez utiliser l'API Statistics API:
Map cacheEntries = sessionFactory.getStatistics()
.getSecondLevelCacheStatistics(regionName)
.getEntries();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)
.setMaxResults(15)
.setCacheable(true)
.setCacheRegion("frontpages")
.list();Si une requête doit forcer le rafraîchissement de sa région de cache, vous devez appeler Query.setCacheMode(CacheMode.REFRESH). C'est particulièrement utile lorsque les données peuvent avoir été mises à jour par un processus séparé (e.g. elles n'ont pas été modifiées par Hibernate). Cela permet à l'application de rafraîchir de manière sélective les résultats d'une requête particulière. Il s'agit d'une alternative plus efficace à l'éviction d'une région du cache à l'aide de la méthode 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 définit trois types de collections :
les collections de valeurs
one-to-many associations
many-to-many associations
Cette classification distingue les différentes relations entre les tables et les clés étrangères mais ne nous apprend rien de ce que nous devons savoir sur le modèle relationnel. Pour comprendre parfaitement la structure relationnelle et les caractéristiques des performances, nous devons considérer la structure de la clé primaire qui est utilisée par Hibernate pour mettre à jour ou supprimer les éléments des collections. Celà nous amène aux classifications suivantes :
collections indexées
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.
From the discussion above, it should be clear that indexed collections and sets allow the most efficient operation in terms of adding, removing and updating elements.
There is, arguably, one more advantage that indexed collections have over sets for many-to-many associations or collections of values. Because of the structure of a Set, Hibernate does not UPDATE a row when an element is "changed". Changes to a Set always work via INSERT and DELETE of individual rows. Once again, this consideration does not apply to one-to-many associations.
After observing that arrays cannot be lazy, you can conclude that lists, maps and idbags are the most performant (non-inverse) collection types, with sets not far behind. You can expect sets to be the most common kind of collection in Hibernate applications. This is because the "set" semantics are most natural in the relational model.
However, in well-designed Hibernate domain models, most collections are in fact one-to-many associations with inverse="true". For these associations, the update is handled by the many-to-one end of the association, and so considerations of collection update performance simply do not apply.
There is a particular case, however, in which bags, and also lists, are much more performant than sets. For a collection with inverse="true", the standard bidirectional one-to-many relationship idiom, for example, we can add elements to a bag or list without needing to initialize (fetch) the bag elements. This is because, unlike a set, Collection.add() or Collection.addAll() must always return true for a bag or List. This can make the following common code much faster:
Parent p = (Parent) sess.load(Parent.class, id); Child c = new Child(); c.setParent(p); p.getChildren().add(c); //no need to fetch the collection! sess.flush();
Deleting collection elements one by one can sometimes be extremely inefficient. Hibernate knows not to do that in the case of an newly-empty collection (if you called list.clear(), for example). In this case, Hibernate will issue a single DELETE.
Suppose you added a single element to a collection of size twenty and then remove two elements. Hibernate will issue one INSERT statement and two DELETE statements, unless the collection is a bag. This is certainly desirable.
Cependant, supposons que nous enlevions dix huit éléments, laissant ainsi deux éléments, puis que nous ajoutions trois nouveaux éléments. Il y a deux moyens de procéder.
effacer dix huit enregistrements un à un puis en insérer trois
remove the whole collection in one SQL
DELETEand insert all five current elements one by one
Hibernate cannot know that the second option is probably quicker. It would probably be undesirable for Hibernate to be that intuitive as such behavior might confuse database triggers, etc.
Fortunately, you can force this behavior (i.e. the second strategy) at any time by discarding (i.e. dereferencing) the original collection and returning a newly instantiated collection with all the current elements.
One-shot-delete does not apply to collections mapped inverse="true".
L'optimisation n'est pas d'un grand intérêt sans le suivi et l'accès aux données de performance. Hibernate fournit toute une panoplie de rapport sur ses opérations internes. Les statistiques dans Hibernate sont fournies par SessionFactory.
Vous pouvez accéder au métriques d'une SessionFactory de deux manières. La première option est d'appeler sessionFactory.getStatistics() et de lire ou d'afficher les Statistics vous même.
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 serverYou can activate and deactivate the monitoring for a SessionFactory:
au moment de la configuration en mettant
hibernate.generate_statisticsàfalse
à chaud avec
sf.getStatistics().setStatisticsEnabled(true)ouhibernateStatsBean.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:
Les métriques relatives à l'usage général de la
Sessioncomme le nombre de sessions ouvertes, le nombre de connexions JDBC récupérées, etc...Metrics related to the entities, collections, queries, and caches as a whole (aka global metrics).
Les métriques détaillées relatives à une entité, une collection, une requête ou une région de cache particulière.
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.getInsertCount()
+ 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().