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< xml version="1.0" encoding="ISO-8859-1" standalone="no" > <!DOCTYPE database SYSTEM "http://jakarta.apache.org/turbine/dtd/database.dtd"> <database name="default" package="org.example.antbook.model" defaultIdMethod="native" baseClass="BaseObject" basePeer="BasePeer"> <table name="USER" javaName="User"> <column name="USER_ID" javaName="UserId" primaryKey="true" required="true" type="INTEGER" /> <column name="USERNAME" javaName="Username" required="true" type="VARCHAR" size="64"/> <column name="PASSWORD" javaName="Password" required="true" type="VARCHAR" size="64"/> <column name="FULLNAME" javaName="Fullname" required="true" type="VARCHAR" size="128"/> </table> </database>

In this example, the u.lastname isn t inside an aggregate function; you use it to group the result. You also don t need to specify the property you like to count. The generated SQL automatically uses the primary key, if you use an alias that has been set in the FROM clause. The next query finds the average bid amount for each item:

This single representation is responsible for generating several other pieces during the stages of our build process:

This query returns ordered pairs of Item identifier and average bid amount values. Notice how you use the id special property to refer to the identifier of a

Prior to compilation, we use the TorqueObjectModelTask (<torque-om> is our mapping to it) to generate Java code representing our data as base and peer objects, providing abstraction to hide the persistence mechanism. The code is generated into a gensrc subdirectory of build. Later in the build process SQL files are generated using the <torque-sql> task. Again, the output goes to the build directory in an sql subdirectory. A data document type definition (DTD) is generated for use in the next step from a sample data XML file in order to ship our application with built-in data. The <torque-datadtd> task takes care of this. The generated DTD and a sample data XML file are used by <torquedatasql> to generate Structured Query Language (SQL) commands for populating the database with the data defined in the XML file. Ant s built-in <sql> task constructs a new database with the schema SQL generated in step 2. The <sql> task is used again, this time to populate the database with sample data.

persistent class, no matter what the real property name of the identifier is. (Again, this special property isn t standardized in JPA QL.) The next query counts the number of bids and calculates the average bid per unsold item:

select bid.item.id, count(bid), avg(bid.amount) from Bid bid where bid.item.successfulBid is null group by bid.item.id

It is unlikely that most Torque-based projects need all of these steps. We have the added steps for generating an embedded prepopulated sample database. These steps can be optimized with clever use of <uptodate> to prevent regeneration of files that will not change until the schema itself changes. We are using the lightweight HypersonicSQL database, which allows us to run a complete database within our web application (no separate server process is needed). The Torque project is still working

That query uses an implicit association join. For an explicit ordinary join in the FROM clause (not a fetch join), you can re-express it as follows:

on a 3.0 release at the time of writing, so we used a development version. Because some of the details may change, it is best for us not to show the specifics of Torque s Ant task syntax. The Torque distribution provides detailed documentation and examples, and the user community is helpful and responsive.

select bidItem.id, count(bid), avg(bid.amount) from Bid bid join bid.item bidItem where bidItem.successfulBid is null group by bidItem.id

A great benefit of having a single source representation of schema metadata surfaced while writing this chapter. The original table was named SEARCH_USER during some experimentation. For example purposes, we wanted it shortened to USER. Simply changing it in one place in antbookschema.xml was all it took, combined with a clean build, to ensure the old generated code and SQL files were eradicated. Many database-driven projects have serious domino effect nightmares if a table or column changes name or type. Torque and Ant make such issues much less severe and more easily managed.

Sometimes, you want to further restrict the result by selecting only particular values of a group. Restricting groups with having The WHERE clause is used to perform the relational operation of restriction upon rows. The HAVING clause performs restriction upon groups. For example, the next query counts users with each last name that begins with A :