CMP has better performance through better key management in Java

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CMP has better performance through better key management
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CMP resolves
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the n + 1 performance problem because the container is responsible for both executing the full query and creating the findByPrimaryKey() method. So, the container has the opportunity to perform database queries that return multiple results efficiently, only executing a single SQL query for a given EJB QL statement.
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EJB QL provides a standard query language The CMP specification defines EJB QL as a standardized declarative query language that can be used to
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find objects that match a given filter. A bean developer needs only to define an abstract finder method and a corresponding EJB QL definition in the bean s deployment descriptor. The container then creates a concrete implementation of the finder method that translates the EJB QL definition to an SQL query. This improves code readability and maintenance by providing a standard that everyone on a team understands and uses, and improves the portability of queries. From a performance standpoint, when using EJB QL, the container has the opportunity to do advanced caching of queries, potentially resulting in significant performance improvements. Using a cache for queries when possible will make your application faster, because it will spend less time communicating with the database, and more scalable, because the overall load on the database will be lessened. For many reasons, the case for CMP is now convincing. Perhaps the most compelling reason to use CMP is a much simpler one: CMP code is easier to write, easier
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Bitter entities
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to manage, and easier to maintain. It decouples your application code from the database; you don t have to specify the individual table and field names in your application code.
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7.4 Antipattern: Application Joins
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Enterprise applications often involve relationships between different entity beans. For example, a system might have a one-to-many relation between Person and Address a Person entity can relate to multiple Address entities. When you persist those beans to a data store, you can let the database or the application manage the relationship. The application usually can t process the relationship nearly as fast as the database. A relational database can evaluate joins in concise, efficient terms, but we often implement them in the application tier instead, leading to poor performance. Java is simply not optimized for data lookups. Performing a join in Java kills any possibility of database tuning and indexing that might otherwise accelerate the query. When a relational database processes a join, it uses sophisticated technology to optimize query access plans and, consequently, minimize the number of direct data comparisons.
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7.4.1 Solution: Delegate joins to the database
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The problem caused by application joins can often be addressed by pushing the joining operations down to the database tier. For example, if you want to find all Person beans who have a certain type of account, you don t want to load all instances into memory and loop through, doing a string comparison on each instance s account s type. A far better approach would be to translate the join into SQL (or whatever underlying query language your database supports) and let the database do the filtering work. When you see this antipattern, it s usually related to the old EJB 1.x specification, which did not support CMR. Many legacy EJB programs use these techniques, and many programmers still do application joins, often by habit. The CMR and EJB QL support added to CMP entity beans has done wonders to reduce the occurrence of application joins. These new additions to the specification provide bean developers with higher-level tools for creating joins, so the developer can rely on the EJB container to create efficient SQL to perform the necessary, low-level database work.
Antipattern: Application Joins
7.4.2 Common examples of application joins
Some situations that commonly lead to application joins are obvious and simple to avoid; others like those listed below are subtler and sometimes not possible to resolve.
Application-defined relation in CMP entity bean Whenever possible, applications that use CMP should express any relations between entity beans in terms of a CMR field. By doing this, the entity bean has maximum opportunity to take advantage of any optimizations in the container to cache relations or otherwise ensure optimal materialization of the relationship. Cross-data-store relation One major service provided by an EJB container is the capability to execute transactions that span multiple data stores. This means that, for example, a custom inventory system can perform transactions with a third-party procurement system or with a sales database. However, the cross-data-store transactions are often limited a database cannot usually create relations to data in a different data store. So while you can perform transactions that span multiple databases, you typically cannot create CMR that span databases. Therefore, you must create and maintain such relations in the application logic of the bean. This type of an application join is usually unavoidable. In this situation, the performance hits associated with application joins must be accepted, because no lower level exists that can be used to express this relation. When creating cross-data-store relations, bear in mind that your application must handle the relationship properly. Consider both lazy-load of the relation, and caching the relation information, if possible, to minimize the frequency of joins. Eager loading is typically only helpful if, by loading multiple parts of an object at the same time, you can achieve efficiencies of scale. Because relations between different data stores are typically handled on a one-off basis, usually no advantage exists to eager loading. Further, eager loading will impose a performance penalty if an object is loaded when the eager-loading relation is not necessary. BMP relation You must implement relations between BMP entity beans in the application logic; absolutely no mechanism exists to delegate this work to the container. Relations among BMP entity beans behave in the same way as cross-data-store relations because it s unlikely that the database can be used to help out with these types of relations. As with cross-data-store relations, caching and lazy loading of BMP relations can significantly help performance issues. Better yet, migrate the BMP entity bean to use CMP, if possible.
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