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Given the options that have been selected for this example, the production exported images and saved them in a subfolder named IMAGES001. If there had been more than 500 images in the production, images 501 through 1,000 would have been saved in a folder named IMAGES002. This production comprised nine individual TIFFs that define two database records. The produced images are named PROD0001.TIF through PROD0009.TIF. The first six images correspond to the Declaration of Independence database record, while the last three images correspond to the Emancipation Proclamation. Figure 14-17 shows the folder structure and files as created by the production.

Type --------------VARCHAR2(4) NUMBER(2) NUMBER(3) VARCHAR2(40)

One important thing about following the fat model design pattern (see Figure 1-2 in 1) is that it makes it easy to run parts of your application independently of Catalyst. Recall from 6 the discussion about not actually allowing a user to delete him- or herself, but marking the user as deleted for later deletion by an administrator. This is much better done without having to run your full application.

Listing 12-9 shows the next step of creating the nested table based on the ERRATA_TAB_T type. Just as we did in the previous section with the EMPLOYEES table, we first create a copy C of the COURSES table, to keep that table unimpaired.

Using the Production Wizard, options were selected from the Header & Footer dialog to stamp document numbers (Document n of m), page numbers (Page n of m), production numbers (PROD0001, PROD0002, and so on), and a statement (IMPORTANT HISTORICAL DOCUMENT) onto images. Other options from the Redlines dialog were selected to burn redlines directly onto images. As the production progressed, Opticon calculated this data or retrieved it from Concordance accordingly, and permanently wrote this data onto each image. The first image exported by the production, PROD0001.TIF, is displayed in Figure 14-18, and is compared with the original image.

Listing 12-9. Creating a Table with a Nested Table Column create table c as select * from courses; alter table c add (errata errata_tab_t) nested table errata store as errata_tab; update c set errata = errata_tab_t(); In Listing 12-9, the ALTER TABLE command adds an ERRATA nested table column to the C table, and the UPDATE command assigns an empty nested table to the ERRATA column for every row. Note that we use the ERRATA_TAB_T table type constructor method for that purpose.

In this recipe, we ll consider a stand-alone script that lives in an application s script directory. Using the application itself to get the model, the script looks like this: #!usr/bin/env perl use warnings; use strict; use FindBin qw($Bin); use lib "$Bin/../lib"; use MyApp; my $schema = MyApp->model->('DB'); my $result = $schema->resultset('Users')->search({ marked_deleted => 1} ); # and so on ... This creates substantial overhead and will really gum up system resources if it runs regularly. Depending on the architecture of the application, this script could cause other problems, too. It s much better to rely on the database schema alone in this instance. #!usr/bin/env perl use warnings; use strict; use FindBin qw($Bin); use lib "$Bin/../lib"; use MyApp::DB; my $dsn = get_dsn(); my $schema = MyApp::DB->connect($dsn); my $result = $schema->resultset('Users')->search({ marked_deleted => 1} ); # and so on ... use Config::General; sub get_dsn { $config = ParseConfig("$Bin/../myapp.conf"); return $config->{Model::DB} } It s good practice to make sure that you always write stand-alone scripts in the second way, with the independent model, rather than the first way, where you depend on MyApp.

Figure 14-18. A comparison of the original image and produced image corresponding to the first page of the first database record. The original image is on the left. The produced image is on the right.