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exist, that s an exceptional situation. Java s Map classes handle this situation by returning null, which has two drawbacks. First, you have to null-test the result of every Map access. Second, it means you can t store a null in a Map. Scala has a kinder and gentler mechanism for dealing with this situation. The get() method on Map returns an Option (Some or None) that contains the result:

begin return description||to_char(active_date, 'YYYYMMDDHH24MISS'); end to_varchar2;

scala> p.get(88)

CONSTRUCTOR FUNCTION worker_type_o( self in out worker_type_o) return self as result is begin id := code := description := active_date := inactive_date := return; end worker_type_o;

scala> p.get(9)

try { if( conn != null) conn.close(); } catch( SQLException e ) { log.log(Level.SEVERE,"Problem closing connection",e); } } } Compare this with Listing 4-4, which shows the implementation taking advantage of the helper classes.

NULL; NULL; NULL; NULL; NULL;

res11: Option[java.lang.String] = Some(Elwood)

CONSTRUCTOR FUNCTION worker_type_o( self in out aiv_code in aiv_description in return begin id := code := description := active_date := inactive_date := return; end worker_type_o;

You can return a default value if the key is not found:

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public void delete(final Long id) { getTemplate().update(DELETE_BY_ID, id); } By obtaining a JdbcTemplate object from the supporting superclass, we have access to methods that encapsulate the necessary resource management logic. Calls to these methods will ensure that the connection is closed regardless of any exceptions that may be thrown. The update method is one of the simplest methods, but it is in select (read) methods that the worst cases of duplication tend to occur. In traditional JDBC logic, it is usually necessary to iterate over a result set, building objects as we go. There is a real risk that this logic will at best be moved out into helper methods (still requiring duplication of the result-set iteration logic) but still left verbatim in a large number of methods. The Spring framework allows the logic behind this population of the entity objects from the result set to be encapsulated in implementations of a variety of wrapper interfaces. The most useful of these is the ParameterizedRowMapper interface. The API for this mapper is shown in Listing 4-5.

get_id(); aiv_code; aiv_description; SYSDATE; NULL;

scala> p.getOrElse(99, "Nobody")

Just think, you are able to test the TYPE, yet you haven t even created a view or table that utilizes it. Speaking of that, why don t we create an object view next!

scala> p.getOrElse(1, "Nobody")

It s time to turn a sow s ear into a silk purse! OK, maybe just a whole pig. Think of this as a cloning project. You can seamlessly transition into the use of user-defined objects by intelligently

public interface ParameterizedRowMapper<T> extends RowMapper<T> { public T mapRow(ResultSet rs, int rowNum); } As you can see, the interface requires you to implement a single method, and is parameterizable with a single type-parameter, which is the type of the entity that can be populated by the mapRow() implementation. Listing 4-6 shows my implementation of this for the UserAccount entity.

We can also use flatMap with Options to find all the values with keys between 1 and 5:

C HA PTER 6 JUS T LIK E IT IS IN THE REA L WORLD!

scala> 1 to 5 flatMap(p.get)

overlaying your relational database structure with a set of object views. An object view takes the columns from one or more relational tables and morphs them into a pseudo-table of userdefined objects, complete with attributes and behavior. Sorry, no I m not smoking anything funny here. I don t blow smoke.

res53: Seq.Projection[java.lang.String] = RangeG(David)

final ParameterizedRowMapper<UserAccount> userMapper = new ParameterizedRowMapper<UserAccount>() { public UserAccount mapRow(ResultSet rs, int rowNum) throws SQLException { UserAccount account = new UserAccount(); account.setId(rs.getLong("id")); account.setAccountName(rs.getString("accountName")); return account; } }; The implementation in Listing 4-6 receives a populated result set and creates a single instance of the entity in question. Typically, the row number is not used, although it is sometimes useful when ordered selections require an associated surrogate index. The mapper abstracts the population of the entity from a set of columns into a single well-defined implementation. We can then use this with other helper methods from the JdbcTemplate class, as shown in Listing 4-7.

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