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Selecting a fetch strategy Item item = (Item) session.get(Item.class, new Long(123)); This operation triggers the following SQL SELECT: select i.*, u.* from ITEM i left outer join USERS u on i.SELLER_ID = u.USER_ID where i.ITEM_ID = ? Obviously, the seller is no longer lazily loaded on demand, but immediately. Hence, a fetch=”join” disables lazy loading. If you only enable eager fetching with lazy=”false”, you see an immediate second SELECT. With fetch=”join”, you get the seller loaded in the same single SELECT. Look at the resultset from this query shown in figure 13.4. Figure 13.4 Two tables are joined to eagerly fetch associated rows. Hibernate reads this row and marshals two objects from the result. It connects them with a reference from Item to User, the seller association. If an Item doesn t have a seller all u.* columns are filled with NULL. This is why Hibernate uses an outer join, so it can retrieve not only Item objects with sellers, but all of them. But you know that an Item has to have a seller in CaveatEmptor. If you enable , Hibernate executes an inner join instead of an outer join. You can also set the eager join fetching strategy on a collection: … If you now load many Item objects, for example with createCriteria(Item. class).list(), this is how the resulting SQL statement looks:
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CHAPTER 13 Optimizing fetching and caching select i.* from ITEM i select b.* from BID b where b.ITEM_ID in (select i.ITEM_ID from ITEM i) In annotations, you again have to use a Hibernate extension to enable this optimization: @OneToMany @org.hibernate.annotations.Fetch( org.hibernate.annotations.FetchMode.SUBSELECT ) private Set bids = new HashSet();} Prefetching using a subselect is a powerful optimization; we ll show you a few more details about it later, when we walk through a typical scenario. Subselect fetching is, at the time of writing, available only for collections, not for entity proxies. Also note that the original query that is rerun as a subselect is only remembered by Hibernate for a particular Session. If you detach an Item instance without initializing the collection of bids, and then reattach it and start iterating through the collection, no prefetching of other collections occurs. All the previous fetching strategies are helpful if you try to reduce the number of additional SELECTs that are natural if you work with lazy loading and retrieve objects and collections on demand. The final fetching strategy is the opposite of on-demand retrieval. Often you want to retrieve associated objects or collections in the same initial SELECT with a JOIN. 13.2.3 Eager fetching with joins Lazy loading is an excellent default strategy. On other hand, you can often look at your domain and data model and say, Every time I need an Item, I also need the seller of that Item. If you can make that statement, you should go into your mapping metadata, enable eager fetching for the seller association, and utilize SQL joins: … Hibernate now loads both an Item and its seller in a single SQL statement. For example:
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Selecting a fetch strategy @org.hibernate.annotations.BatchSize(size = 10) private Set bids = new HashSet(); … } Prefetching proxies and collections with a batch strategy is really a blind guess. It s a smart optimization that can significantly reduce the number of SQL statements that are otherwise necessary to initialize all the objects you re working with. The only downside of prefetching is, of course, that you may prefetch data you won t need in the end. The trade-off is possibly higher memory consumption, with fewer SQL statements. The latter is often much more important: Memory is cheap, but scaling database servers isn t. Another prefetching algorithm that isn t a blind guess uses subselects to initialize many collections with a single statement. 13.2.2 Prefetching collections with subselects Let s take the last example and apply a (probably) better prefetch optimization: List allItems = session.createQuery(”from Item”).list(); processBids( (Item)allItems.get(0) ); processBids( (Item)allItems.get(1) ); processBids( (Item)allItems.get(2) ); You get one initial SQL SELECT to retrieve all Item objects, and one additional SELECT for each bids collection, when it s accessed. One possibility to improve this would be batch fetching; however, you d need to figure out an optimum batch size by trial. A much better optimization is subselect fetching for this collection mapping: … Hibernate now initializes all bids collections for all loaded Item objects, as soon as you force the initialization of one bids collection. It does that by rerunning the first initial query (slightly modified) in a subselect:
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CHAPTER 13 Optimizing fetching and caching right thing. As an example, imagine a batch size of 20 and a total number of 119 uninitialized proxies that have to be loaded in batches. At startup time, Hibernate reads the mapping metadata and creates 11 batch loaders internally. Each loader knows how many proxies it can initialize: 20, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1. The goal is to minimize the memory consumption for loader creation and to create enough loaders that every possible batch fetch can be produced. Another goal is to minimize the number of SQL SELECTs, obviously. To initialize 119 proxies Hibernate executes seven batches (you probably expected six, because 6 x 20 > 119). The batch loaders that are applied are five times 20, one time 10, and one time 9, automatically selected by Hibernate. Batch fetching is also available for collections: … If you now force the initialization of one bids collection, up to 10 more collections of the same type, if they re uninitialized in the current persistence context, are loaded right away: select items… select b.* from BID b where b.ITEM_ID in (?, ?, ?) In this case, you again have three Item objects in persistent state, and touching one of the unloaded bids collections. Now all three Item objects have their bids loaded in a single SELECT. Batch-size settings for entity proxies and collections are also available with annotations, but only as Hibernate extensions: @Entity @Table(name = “USERS”) @org.hibernate.annotations.BatchSize(size = 10) public class User { … } @Entity public class Item { … @OneToMany
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Selecting a fetch strategy select u.* from USERS u where u.USER_ID = ? … Hibernate offers some algorithms that can prefetch User objects. The first optimization we now discuss is called batch fetching, and it works as follows: If one proxy of a Usermust be initialized, go ahead and initialize several in the same SELECT. In other words, if you already know that there are three Item instances in the persistence context, and that they all have a proxy applied to their seller association, you may as well initialize all the proxies instead of just one. Batch fetching is often called a blind-guess optimization, because you don t know how many uninitialized User proxies may be in a particular persistence context. In the previous example, this number depends on the number of Item objects returned. You make a guess and apply a batch-size fetching strategy to your User class mapping: … You re telling Hibernate to prefetch up to 10 uninitialized proxies in a single SQL SELECT, if one proxy must be initialized. The resulting SQL for the earlier query and procedure may now look as follows: select items… select u.* from USERS u where u.USER_ID in (?, ?, ?) The first statement that retrieves all Item objects is executed when you list() the query. The next statement, retrieving three User objects, is triggered as soon as you initialize the first proxy returned by allItems.get(0).getSeller(). This query loads three sellers at once because this is how many items the initial query returned and how many proxies are uninitialized in the current persistence context. You defined the batch size as up to 10. If more than 10 items are returned, you see how the second query retrieves 10 sellers in one batch. If the application hits another proxy that hasn t been initialized, a batch of another 10 is retrieved and so on, until no more uninitialized proxies are left in the persistence context or the application stops accessing proxied objects. FAQ What is the real batch-fetching algorithm? You can think about batch fetching as explained earlier, but you may see a slightly different algorithm if you experiment with it in practice. It s up to you if you want to know and understand this algorithm, or if you trust Hibernate to do the
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CHAPTER 13 Optimizing fetching and caching By default, Hibernate fetches associated objects and collections lazily whenever you access them (we assume that you map all to-one associations as FetchType. LAZY if you use Java Persistence). Look at the following trivial code example: Item item = (Item) session.get(Item.class, new Long(123)); You didn t configure any association or collection to be nonlazy, and that proxies can be generated for all associations. Hence, this operation results in the following SQL SELECT: select item.* from ITEM item where item.ITEM_ID = ? (Note that the real SQL Hibernate produces contains automatically generated aliases; we ve removed them for readability reasons in all the following examples.) You can see that the SELECT queries only the ITEM table and retrieves a particular row. All entity associations and collections aren t retrieved. If you access any proxied association or uninitialized collection, a second SELECT is executed to retrieve the data on demand. Your first optimization step is to reduce the number of additional on-demand SELECTs you necessarily see with the default lazy behavior for example, by prefetching data. 13.2.1 Prefetching data in batches If every entity association and collection is fetched only on demand, many additional SQL SELECT statements may be necessary to complete a particular procedure. For example, consider the following query that retrieves all Item objects and accesses the data of each items seller: List allItems = session.createQuery(”from Item”).list(); processSeller( (Item)allItems.get(0) ); processSeller( (Item)allItems.get(1) ); processSeller( (Item)allItems.get(2) ); Naturally, you use a loop here and iterate through the results, but the problem this code exposes is the same. You see one SQL SELECT to retrieve all the Item objects, and an additional SELECT for every seller of an Item as soon as you process it. All associated User objects are proxies. This is one of the worst-case scenarios we ll describe later in more detail: the n+1 selects problem. This is what the SQL looks like: select items… select u.* from USERS u where u.USER_ID = ? select u.* from USERS u where u.USER_ID = ?
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Selecting a fetch strategy for Hibernate that a property or component should be lazy loaded through interception. To disable proxies and enable interception for associations with annotations, you have to rely on a Hibernate extension: @ManyToOne @JoinColumn(name=”SELLER_ID”, nullable = false, updatable = false) @org.hibernate.annotations.LazyToOne( org.hibernate.annotations.LazyToOneOption.NO_PROXY ) private User seller; To enable interception, the bytecode of your classes must be instrumented after compilation, before runtime. Hibernate provides an Ant task for that purpose: We leave it up to you if you want to utilize interception for lazy loading in our experience, good use cases are rare. Naturally, you not only want to define what part of your persistent object network must be loaded, but also how these objects are retrieved. In addition to creating a fetch plan, you want to optimize it with the right fetching strategies. 13.2 Selecting a fetch strategy Hibernate executes SQL SELECT statements to load objects into memory. If you load an object, a single or several SELECTs are executed, depending on the number of tables which are involved and the fetching strategy you ve applied. Your goal is to minimize the number of SQL statements and to simplify the SQL statements, so that querying can be as efficient as possible. You do this by applying the best fetching strategy for each collection or association. Let s walk through the different options step by step.
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CHAPTER 13 Optimizing fetching and caching Proxies and collection wrappers can only be used to lazy load entity associations and collections. They can t be used to lazy load individual scalar properties or components. We consider this kind of optimization to be rarely useful. For example, you usually don t want to lazy load the initialPrice of an Item. Optimizing at the level of individual columns that are selected in SQL is unnecessary if you aren t working with (a) a significant number of optional columns or (b) with optional columns containing large values that have to be retrieved on-demand. Large values are best represented with locator objects (LOBs); they provide lazy loading by definition without the need for interception. However, interception (in addition to proxies, usually) can help you to optimize column reads. Let s discuss interception for lazy loading with a few examples. Imagine that you don t want to utilize a proxy of User entity class, but you still want the benefit of lazy loading an association to User for example, as seller of an Item. You map the association with no-proxy: … … The default of the lazy attribute is proxy. By setting no-proxy, you re telling Hibernate to apply interception to this association: Item item = (Item) session.get(Item.class, new Long(123)); User seller = item.getSeller(); The first line retrieves an Item object into persistent state. The second line accesses the seller of that Item. This call to getSeller() is intercepted by Hibernate and triggers the loading of the User in question. Note how proxies are more lazy than interception: You can call item.getSeller().getId() without forcing initialization of the proxy. This makes interception less useful if you only want to set references, as we discussed earlier. You can also lazy load properties that are mapped with
or ; here the attribute that enables interception is lazy=”true”, in Hibernate XML mappings. With annotations, @Basic(fetch = FetchType.LAZY) is a hint
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Defining the global fetch plan @OneToOne associations default to FetchType.EAGER! This default was standardized to allow Java Persistence provider implementations without lazy loading (in practice, such a persistence provider wouldn t be very useful). We recommend that you default to the Hibernate lazy loading fetch plan by setting FetchType. LAZY in your to-one association mappings and only override it when necessary: @Entity public class Item { … @ManyToOne(fetch = FetchType.LAZY) private User seller; … } You now know how to create a fetch plan; that is, how you define what part of the persistent object network should be retrieved into memory. Before we show you how to define how these objects should be loaded and how you can optimize the SQL that will be executed, we d like to demonstrate an alternative lazy loading strategy that doesn t rely on proxies. 13.1.6 Lazy loading with interception Runtime proxy generation as provided by Hibernate is an excellent choice for transparent lazy loading. The only requirement that this implementation exposes is a package or public visible no-argument constructor in classes that must be proxied and nonfinal methods and class declarations. At runtime, Hibernate generates a subclass that acts as the proxy class; this isn t possible with a private constructor or a final entity class. On the other hand, many other persistence tools don t use runtime proxies: They use interception. We don t know of many good reasons why you d use interception instead of runtime proxy generation in Hibernate. The nonprivate constructor requirement certainly isn t a big deal. However, in two cases, you may not want to work with proxies: The only cases where runtime proxies aren t completely transparent are polymorphic associations that are tested with instanceof. Or, you may want to typecast an object but can t, because the proxy is an instance of a runtime-generated subclass. We show how to avoid this issue and how to work around the problem in chapter 7, section 7.3.1, Polymorphic many-to-one associations. Interception instead of proxies also makes these issues disappear.
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CHAPTER 13 Optimizing fetching and caching Figure 13.3 A larger graph fetched eagerly through disabled lazy associations and collections wasn t part of your fetch plan and wasn t initialized before the persistence context was closed. This also happens if you try to access a proxy for example, the User that approved the item. (Note that you can access this proxy two ways: through the approvedBy and bidder references.) With annotations, you switch the FetchType of an entity association or a collection to get the same result: @Entity public class Item { … @ManyToOne(fetch = FetchType.EAGER) private User seller; @OneToMany(fetch = FetchType.EAGER) private Set bids = new HashSet(); … } The FetchType.EAGER provides the same guarantees as lazy=”false” in Hibernate: the associated entity instance must be fetched eagerly, not lazily. We already mentioned that Java Persistence has a different default fetch plan than Hibernate. Although all associations in Hibernate are completely lazy, all @ManyToOne and
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