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JNDI as a component registry
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that you won t even know that JNDI lookups are happening behind the scenes, even for remote lookups. DI is discussed in chapters 2, 3, 4, and 5. You can find more about JNDI from Sun s website at http://java.sun.com/ products/jndi/.
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Reviewing relational databases
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Database tables, columns, rows, and schema
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Relational databases have been an integral part of enterprise development for a few decades now. The fact that these business data storage mainstays are backed by their own body of mathematical theory (relational algebra) speaks to the elegance and robustness of this mature technology. E. F. Codd first introduced the theory of relational databases in 1970 while working at IBM. This groundbreaking research eventually led to the creation of today s database products, including IBM s own highly successful DB2 database. Oracle is the most popular database in existence today, in vibrant competition with products like Microsoft SQL Server, Sybase, MySQL, and many others, in addition to IBM s DB2. Fundamentally, relational databases store and organize related data into a hierarchy of schemas, tables, columns, and rows. Other types of databases exist, including flat-file, hierarchical, network, and object-oriented databases. Each of these is worthy of study on its own merits. However, the EJB 3 specification only supports relational databases, and that will be where we draw the line with regard to the database discussions in this book. The focus of this appendix is to briefly discuss each of the relational concepts.
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B.1 Database tables, columns, rows, and schema
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Tables are the most basic logical unit in a relational database. A table stores conceptually related data into rows and columns. Essentially, tables are the objectoriented (OO) counterparts of objects. Hence, we might imagine that the ActionBazaar database contains tables like CATEGORIES, ITEMS, ORDERS, and so forth. A column is a particular domain of data, and a table is a set of related columns. If tables are the equivalent of objects, columns are the equivalent of object attributes. Consequently, the CATEGORIES table probably has columns such as CATEGORY_ID, CATEGORY_NAME, MODIFICATION_DATE, and CREATION_DATE, as seen in figure B.1. As with object attributes in Java, each relational table column has a data type. Table B.1 lists some column data types commonly used across various databases and their Java equivalents.
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Table B.1 Common column data types and their Java equivalents Java Type java.lang.String char, Char continued on next page
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Relational Database Type CHAR, VARCHAR2, VARCHAR, LONG Char
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APPENDIX B
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Reviewing relational databases
Table B.1 Common column data types and their Java equivalents (continued) Java Type int, Integer, BigInteger double, float, BigDecimal, Double, Float java.sql.Blob, byte[] java.sql.Clob, char[],java.lang.String
Relational Database Type INTEGER, NUMBER NUMBER Raw, BLOB CLOB
A row is a record saved in the database composed of related data in each column of a table. A row, in effect, is equivalent to an instance of a particular object, in contrast to the class definition. For most OO developers it s not a big leap to imagine an instance of the Category object being saved into a row of the CATEGORIES table. A schema can be compared to a Java package. In other words, a schema is a collection of related tables, similar to how a Java package contains a set of related classes. Usually, all of the tables used in a particular application are organized under a single schema. All the tables used in our example application might be stored under a schema called ACTIONBAZAAR. Typically, a schema stores much more than just tables. It might also have views, triggers, and stored procedures. A detailed discussion of these database features is beyond the scope of this appendix. For coverage of these and other database topics, feel free to investigate a good reference book such as An Introduction to Database Systems, 7th edition, by C. J. Date (Addison Wesley Longman, 1999).
Figure B.1 Rows and columns in the CATEGORIES table. While columns store a domain of data, rows contain a record composed of a set of related columns in a table.
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