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We already defined jBPM in the previous section, so most of the jBPM configurations are already done. However, if you skipped ahead or were implementing only page flow, you are going to have to reference the jBPM configuration we did previously. There is only one additional change. All you have to do is add a line to components.xml, as in Listing 7-24.

You can see that even for a small table such as employee, you ll still save about 46 pages (184KB) of storage by compression. You can also see that the total size of the associated dictionaries will be 23KB, meaning that even for a trivially small table, it can be worth compressing.

Figure 3-1. The left image shows an enlargment of 20 using the Nearest Neighbor method. Note the poor quality of the edges where blocks of pixels are visible. On the right side, the same image was resized using the Cubic method producing a much better image.

<component class="org.jboss.seam.core.Jbpm"> <property name="processDefinitions">ticketing-system.jpdl.xml</property> <property name="pageflowDefinitions">new-ticket.jpdl.xml</property> </component>

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Now that you re satisfied that compression will do you some good, you can instruct DB2 to perform the necessary compression steps This is a two-part process, in which you first enable a table for compression and then actually reorganize the storage to implement compression To enable (or disable) compression, use the compress {yes | no } clause of the create table or alter table statement In the current example, to enable compression on the existing employee table, it s as simple as running the relevant alter table command: db2 => alter table employee compress yes Upon successful completion, the table is ready for compression If you ever need to determine which tables have compression, you can inspect the COMPRESSION column of the sysibmsystables table.

As you can see, there is only the addition of one line. Note that if you decided to implement only the page flow without the process definitions, you could have eliminated the process definition line. However, you would still need the JAR file reference.

It either reports N for no compression, V for individual value compression enabled, R for row compression enabled, or B for both possible compression types You can see that row compression is now enabled for the employee table, as follows: db2 => select name, compression from sysibmsystables where name = 'EMPLOYEE' and creator = 'FUZZY' NAME COMPRESSION -------------------------------- ----------EMPLOYEE R You re now ready to actually perform the compression work against the data in the underlying table For this, you use the reorg command, which is a very powerful utility allowing the physical data and associated indexes of a table to be manipulated at the storage level DB2 v95 can begin compilation of the compression dictionary without a reorg, but can work only with new values The reorganization is required to ensure that all old values are also considered for compression.

Gimp offers a simple selection of resizing algorithms. If you need to resize a couple of photographs, this is the easiest way to do it. Open your image and select Image Scale Image. In the Scale Image dialog box (see Figure 3-2), you can define the new size of the image in pixels, percentage, or any other metrics shown in the menu. The method that Gimp will use for the resize is the one that you select under Interpolation.

As you should have been able to see from the page flow definitions, the code was not overly complex, requiring us to identify tasks and definitions. Most of the items were simply transferring from page to page and calling Seam components. The regular expressions we defined previously will work like the Seam components we defined previously for action listeners. In reality, the only thing to do is to start the conversation. Because these are longrunning conversations, we are going to use the @Begin annotation that we used in 6, except now we are going to set the parameter pageflow to the page flow definition name. You can see this in Listing 7-25.

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