Had this problem this morning fixed from stackoverflow than found this. As long as the persistence context is opened, navigating the LAZY association results in fetching those as well, through additionally executed queries.
The best advice I can give you is to favor the manual fetching strategy defined in JPQL queries using the fetch operator. Most of the associations are marked as LAZY because there is no need to fetch all of them every time we load a Product. The warehouse is only needed when displaying the stock information. The Importer is used in certain displays only, and we will fetch it when necessary. The images are lazy since not all views require displaying those images.
Only the company is fetched eagerly because all our views need it, and in our application, a Product always must be considered in the context of a given Company. Every time we load through the entity manager the default fetching strategy comes into play, meaning the Company gets fetched along with the Product we are selecting.
JPQL queries may override the default fetching strategy. The default fetch strategy is overridden by the JPQL query. It loads only Customer when we request the Customer, it will not load the addresses until we request for it. It will load all the addresses only when we explicitly request the addresses to use in our application.
First Select statement to retrieve the Customer records — session. Second Select statement to retrieve its related collections — when we iterate addresses using enhanced for loop FetchMode SELECT with Batch Size No change in above xml as we have specified the batch size as 10 already. No change in above annotated class as we have specified the batch size as 10 already. Now when we load one Customer , Hibernate loads the address collection for additional 10 Customers which are currently in the session.
Suppose, We have 20 Customers in the session and batch size is set as In this case, when we load one Customer, 3 queries will be executed. Another query to load the Address collections for other 10 Customers. If we have only one User then queries generated with batch size is same as without batch size as below.
Suppose we have 10 users and we load all of them using below query. Now see the queries generated by Hibernate with Batch size of In case,If we have 20 Customers in the session and batch size is Select query to retrieve all the customer records 2.
Note:The batch-size fetching strategy is not specifying how many records in the collections are loaded. Instead, it specifies how many collections should be loaded at a time. 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.
Second-level cache eviction via SessionFactoty. The CacheMode controls how a particular session interacts with the second-level cache:.
GET : will read items from the second-level cache. Do not write to the second-level cache except when updating data.
PUT : will write items to the second-level cache. Do not read from the second-level cache. Bypass the effect of hibernate. To browse the contents of a second-level or query cache region, use the Statistics API:. Browsing the second-level cache entries via 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:. StandardQueryCache , holding the cached query results. 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. 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. 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.
If you want to force the query cache to refresh one of its regions disregard any cached results it finds there you can use org. In conjunction with the region you have defined for the given query, Hibernate will selectively force the results cached in that particular region to be refreshed. This is particularly useful in cases where underlying data may have been updated via a separate process and is a far more efficient alternative to bulk eviction of the region via org.
Hibernate internally needs an entry org. EntityEntry to tell the current state of an object with respect to its persistent state, when the object is associated with a Session. However, maintaining this association was kind of heavy operation due to lots of other rules must by applied, since 4.
Basically, the idea is, instead of having a customized kind of heavy and which was usually identified as hotspot map to do the look up, we change it to. More info about org. ManagedEntity please find from its javadoc. Sometimes, you probably don't want to implement an intrusive interface, maybe due to portable concern, which is fine and Hibernate will take care of this internally with a wrapper class which implements that interface, and also an internal cache that maps this entity instance and the wrapper together.
Obviously, this is the easiest way to choose, since it doesn't require any change of the project source code, but it also cost more memory and CUP usage, comparing to the first one. Besides the above two approaches, Hibernate also provides a third choice which is build time bytecode enhancement. Applications can use enhanced entity classes, annotated with either javax.
Entity or composite javax. To use the task org. EnhancementTask define a taskdef and call the task, as shown below. This code uses a pre-defined classpathref and a property referencing the compiled classes directory. The EnhancementTask is intended as a total replacement for InstrumentTask. Further, it is also incompatible with InstrumentTask , so any existing instrumented classes will need to be built from source again. The Maven Plugin uses a Mojo descriptor to attach the Mojo to the compile phase for your project.
The Gradle plugin adds an enhance task using the output directory of the compile task as the source location of entity class files to enhance. 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.
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:. 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.
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. 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.
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. 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. This is because, unlike a set , Collection. This can make the following common code much faster:. 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. Suppose you added a single element to a collection of size twenty and then remove two elements.
This is certainly desirable. However, suppose that we remove eighteen elements, leaving two and then add thee new elements.
There are two possible ways to proceed. 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. 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. You can enable a single MBean for all your SessionFactory or one per factory. See the following code for minimalistic configuration examples:.
Hibernate Vs. JDBC A comparison. Sun Green Building Research Center. Types of inheritence models in Hibernate. What is component mapping in hibernate? Paging Through the Result Set in Hibernate. Download Hibernate latest version.
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