Mike Keith Merrick Schincariol - Pro JPA 2 in Java EE 8

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Mike Keith, Merrick Schincariol, Massimo Nardone 2018

Mike Keith , Merrick Schincariol and Massimo Nardone Pro JPA 2 in Java EE 8

1. Introduction

Mike Keith 1, Merrick Schincariol 2 and Massimo Nardone 3

(1)

Ottawa, Ontario, Canada

(2)

RR 3, RR 3, Almonte, Ontario, Canada

(3)

Helsinki, Finland

Electronic supplementary material

The online version of this chapter ( https://doi.org/10.1007/978-1-4842-3420-4_1 ) contains supplementary material, which is available to authorized users.

Enterprise applications are defined by their need to collect, process, transform, and report on vast amounts of information. And, of course, that information has to be kept somewhere. Storing and retrieving data is a multibillion dollar business, evidenced in part by the growth of the database market as well as the emergence of cloud-based storage services. Despite all the available technologies for data management, application designers still spend much of their time trying to efficiently move their data to and from storage.

Despite the success the Java platform has had in working with database systems, for a long time it suffered from the same problem that has plagued other object-oriented programming languages. Moving data back and forth between a database system and the object model of a Java application was a lot harder than it needed to be. Java developers either wrote lots of code to convert row and column data into objects, or found themselves tied to proprietary frameworks that tried to hide the database from them. Fortunately, a standard solution, the Java Persistence API (JPA), was introduced into the platform to bridge the gap between object-oriented domain models and relational database systems.

This book introduces version 2.2 of the Java Persistence API as part of the Java EE 8 and explores everything that it has to offer developers.

Maintenance release of JPA 2.2 started during 2017 under JSR 338 and was finally approved on June 19, 2017.

Here is the official Java Persistence 2.2 Maintenance release statement:

The Java Persistence 2.2 specification enhances the Java Persistence API with support for repeating annotations; injection into attribute converters; support for mapping of the java.time.LocalDate , java.time.LocalTime , java.time.LocalDateTime , java.time.OffsetTime , and java.time.OffsetDateTime types; and methods to retrieve the results of Query and TypedQuery as streams.

One of its strengths is that it can be slotted into whichever layer, tier, or framework an application needs it to be in. Whether you are building client-server applications to collect form data in a Swing application or building a website using the latest application framework, JPA can help you provide persistence more effectively.

To set the stage for JPA, this chapter first takes a step back to show where weve been and what problems we are trying to solve. From there, we will look at the history of the specification and give you a high-level view of what it has to offer.

Relational Databases

Many ways of persisting data have come and gone over the years, and no concept has more staying power than the relational database. Even in the age of the cloud, when Big Data and NoSQL regularly steal the headlines, relational database services are in consistent demand to enable today's enterprise applications running in the cloud. While key-value and document-oriented NoSQL stores have their place, relational stores remain the most popular general-purpose databases in existence, and they are where the vast majority of the worlds corporate data is stored. They are the starting point for every enterprise application and often have a lifespan that continues long after the application has faded away.

Understanding relational data is key to successful enterprise development. Developing applications to work well with database systems is a commonly acknowledged hurdle of software development. A good deal of Javas success can be attributed to its widespread adoption for building enterprise database systems. From consumer websites to automated gateways, Java applications are at the heart of enterprise application development. Figure shows an example of a relational database of user to car .

Figure 1-1

User to car relational database

Object-Relational Mapping

The domain model has a class. The database has a table. They look pretty similar. It should be simple to convert one to the other automatically. This is a thought weve probably all had at one point or another while writing yet another Data Access Object (DAO) to convert Java Database Connectivity (JDBC) result sets into something object-oriented. The domain model looks similar enough to the relational model of the database that it seems to cry out for a way to make the two models talk to each other.

The technique of bridging the gap between the object model and the relational model is known as object-relational mapping , often referred to as O-R mapping or simply ORM. The term comes from the idea that we are in some way mapping the concepts from one model onto another, with the goal of introducing a mediator to manage the automatic transformation of one to the other.

Before going into the specifics of object-relational mapping, lets define a brief manifesto of what the ideal solution should be.

• Objects, not tables : Applications should be written in terms of the domain model, not bound to the relational model. It must be possible to operate on and query against the domain model without having to express it in the relational language of tables, columns, and foreign keys.
• Convenience, not ignorance : Mapping tools should be used only by someone familiar with relational technology. O-R mapping is not meant to save developers from understanding mapping problems or to hide them altogether. It is meant for those who have an understanding of the issues and know what they need, but who dont want to have to write thousands of lines of code to deal with a problem that has already been solved.
• Unobtrusive, not transparent : It is unreasonable to expect that persistence be transparent because an application always needs to have control of the objects that it is persisting and be aware of the entity lifecycle. The persistence solution should not intrude on the domain model, however, and domain classes must not be required to extend classes or implement interfaces in order to be persistable.
• Legacy data, new objects : It is far more likely that an application will target an existing relational database schema than create a new one. Support for legacy schemas is one of the most relevant use cases that will arise, and it is quite possible that such databases will outlive every one of us.
• Enough, but not too much : Enterprise developers have problems to solve, and they need features sufficient to solve those problems. What they dont like is being forced to eat a heavyweight persistence model that introduces large overhead because it is solving problems that many do not even agree are problems.
• Local, but mobile : A persistent representation of data does not need to be modeled as a full-fledged remote object. Distribution is something that exists as part of the application, not part of the persistence layer. The entities that contain the persistent state, however, must be able to travel to whichever layer needs them so that if an application is distributed, then the entities will support and not inhibit a particular architecture.

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