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To remove a field from a layout, users can highlight it, then press the Delete key, or click and drag the field off the list entirely Removing a field in the Table Layout tool doesn t delete the field from the database Rather, it causes the field to be hidden in Table view To add a field to the list, users can drag and drop from the list of remaining field names on the right to the desired position in the layout on the left..

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Figure 4-5. The SQL Developer Preferences dialog box Listing 4-39. Comparing Two Complementary Queries select empno, ename, comm from employees where comm > 400; EMPNO -------7521 7654 ENAME COMM -------- -------WARD 500 MARTIN 1400

Figure 8-14. Specifying a table layout. The fields displayed on the left appear in Concordance s Table view. The fields in the Available fields list box are not displayed.

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__PACKAGE__->meta->make_immutable; 1; The use Moose line sets us up as a class with a superclass of Moose::Object, so there s still no need for a new() method. Loading Acme::LOLCAT with () prevents the translate sub from being imported into our namespaces, which we need in order not to clash with the translate method we re going to write. Then we ask namespace::clean to remove everything that s currently in our namespace except for meta when we get to the end of the file. That means that the Moose directives like has, before, and so forth that have been shoved into our namespace will be removed without the requirement for an explicit no Moose call. If we later need to import other directives (e.g., if we have a MooseX::Types-based library of types per project that we import type symbols from), they will also be automatically cleaned out for us, provided we use the other libraries before the namespace::clean line.

select empno, ename, comm from employees where comm <= 400;

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EMPNO ENAME COMM -------- -------- -------7499 ALLEN 300 7844 TURNER 0 The first query in Listing 4-39 returns 2 employees, so you might expect to see the other 12 employees in the result of the second query, because the two WHERE clauses complement each other. However, the two query results actually are not complementary. If Oracle evaluates a condition, there are three possible outcomes: the result can be TRUE, FALSE, or UNKNOWN. In other words, the SQL language is using three-valued logic. Only those rows for which the condition evaluates to TRUE will appear in the result no problem. However, the EMPLOYEES table contains several rows for which both conditions in Listing 4-39 evaluate to UNKNOWN. Therefore, these rows (ten, in this case) will not appear in either result. Just to stress the nonintuitive nature of null values in SQL, you could say the following: In SQL, NOT is not not The explanation of this (case-sensitive) statement is that in three-valued logic, the NOT operator is not the complement operator anymore: NOT TRUE is equivalent with FALSE not TRUE is equivalent with FALSE OR UNKNOWN

To add a new layout with its own collection of fields, users highlight a database name, right-click, and then select the New Layout option. If no layout has been created for a database, the Table view displays all fields by default, in the order in which the fields were created. When one or more layouts have been created, users may select among them by right-clicking anywhere in the Table view, and by selecting the name of the layout they wish to view.

n Note We use namespace::clean in this example. Elsewhere in the book we use namespace::autoclean,

Suppose you are looking for all employees except the lucky ones with a commission greater than 400. In that case, the second query in Listing 4-39 does not give you the correct answer, because you would expect to see 12 employees instead of 2. To fix this query, you need the SQL IS NULL operator, as shown in Listing 4-40. Listing 4-40. Using the IS NULL Operator select from where or empno, ename, comm employees comm <= 400 comm is null; ENAME COMM -------- -------SMITH ALLEN 300 JONES BLAKE CLARK SCOTT KING TURNER 0 ADAMS JONES FORD MILLER

Table view offers the ability to select a field, and then count the number of unique instances of values in that field across all records in the currently active query. For example, in a database that has a field LASTNAME, you might wish to know how many SMITHS, how many JONES, and how many other names appear in the field, as well as the count of each name. This process is known as tallying.

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