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Unfortunately, there is no document that lists all the different display_as values you can use. But you can effectively generate this yourself via the APEX Dictionary. For example, to get a list of all the page item types we are using in our Buglist application, we could run the query shown in Listing 16-8. Listing 16-8. Querying the Different Page Item Types apexdemo@DBTEST> select 2 distinct(display_as) 3 from 4 apex_application_page_items 5 where 6 application_name = 'Buglist Application'; DISPLAY_AS ---------------------------------------------Hidden Display as Text (does not save state) File Browse... Password Text Field (always submits page when Enter pressed) Text Field Password (submits when Enter pressed) Date Picker (MM/DD/YYYY) Select List with Submit Select List Display as Text (saves state) 11 rows selected. As you can see, the names correspond to what you would select via the Application Builder interface for the item type. Remember that this is not a full list of available page item types; it is just a list of the ones currently in use in the Buglist application. We could make this query arguably even more useful by showing where each of those page item types are used, as shown in Listing 16-9. Listing 16-9. Querying the Different Page Item Types and Where They Are Used 1 2 3 4 5 6 7 8 9 10 select count(*) as count, page_id as page, display_as from apex_application_page_items where application_name = 'Buglist Application' group by display_as,page_id

NUHBER_OF_ARGUMENTS => 4 , START_DATE - > SYSDATE + 1, REPEATJNTERVAL => 'FREOrOAILY', END^DATE => SYSDATE + 3 0 , 30B_CLASS => BATCH_CLASS', -

> ENABLED => TRUE, > AUTO_DRDP -> FALSE);

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11 order by 12* count desc, page COUNT PAGE DISPLAY_AS ------ ----- ------------------------------------------------4 2 Select List 4 3 Select List 4 15 Text Field 3 3 Hidden 2 1 Hidden 2 2 Text Field 2 3 Text Field 2 15 Password 1 1 Text Field (always submits page when Enter pressed) 1 1 Display as Text (does not save state) 1 2 Hidden 1 2 File Browse... 1 2 Date Picker (MM/DD/YYYY) 1 3 Date Picker (MM/DD/YYYY) 1 3 Display as Text (saves state) 1 14 Hidden 1 19 Hidden 1 19 Select List with Submit 1 101 Password (submits when Enter pressed) 1 101 Text Field 20 rows selected. So we can now clearly see which item types we use most frequently and on which pages those types are. Now, the original purpose of this example was to perform a QA check to determine whether the field alignment was correct for the application, and you can see just how easily that can be done. We could perhaps schedule a job that runs once a day (or at the end of every week) to ensure that all the applications in the workspace have correctly aligned labels. This would ensure that all newly created fields had correctly aligned labels and would also check to make sure someone had not changed the alignment of an existing label.

The job class will be used to identify^ which database service should be used to run the job. This, in turn, will be used to determine on which instances the job should run. If a primary (PREFERRED) instance is not available, then the job will be run on a secondary (AVAILABLE) instance. If the service has been assigned to a resource consumer group, then Resource Manager will enforce the resource limits specified for that group.

Parallel Execution is aware of database services. When a parallel job coordinator process creates a job slave, that slave inherits the database service from the coordinator. However, depending on the workload, the job coordinator can execute slaves on any instance in the cluster. In other words, the slaves are not restricted to running on the set of PREFERRED or AVAILABLE instances. Therefore, if you choose to take advantage of Parallel Execution, you should be aware that the distribution of workload across the nodes in the cluster may be affected. At first sight, the ability of the job coordinator to allocate nodes outside the set assigned to the database service may appear to be an error. However, without this mechanism, it would not be possible to query the global (GV$) dynamic performance views, as these views are implemented using Parallel Execution, where the parallel job coordinator executes a job slave on each instance in the cluster. A process querying the global dynamic performance view must be able to access all instances, irrespective of any database service to which it might be connected.

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