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With this method, each assembly has its own folder that contains each named version of the assembly, as shown in Figure 5-3.



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For example, Berkeley DB is a set of client libraries and is not a stand-alone database system MySQL is a mature database server with a proven track record of stability Some open source database systems may not have the install base of MySQL or may not offer the features you need in an enterprise database server Clearly, the challenges are going to be unique to the development needs and the environment in which the modifications take place Whatever your needs are, you can be sure that you have complete access to all of the source code and that your modifications are limited only by your imagination..





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When you want to reset, say, the right leg, you must set the Rreset variable to true, unblocking the realignment task. In fact, the AlignRightLeg task hangs at the while (!Rreset) Wait(100) statement until the RealignLegs function sets Rreset to true (see Listing 5-6). Once free to do its duty, the task acquires the right leg mutex and aligns the leg as described before. When the realignment is completed, the Rreset variable is set to false, so that at the next loop iteration the task will stop, waiting for the Rreset variable to be set to true again. Finally, the Sight task implements, in its last lines, the hysteresis cycle described in the previous paragraph (see Listing 5-9).

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This allows the developer to select a specific version of an assembly that does not change. This means the impact from version upgrades is minimal, but of course it could lead to a confused situation in terms of the deployed assemblies. Without some kind of progression, over a significant period of time it may not be possible to integrate newer versions of assemblies into solutions without extensive development and regression work. For this reason, you may prefer to use the next method, which gives the process a few more teeth.

Listing 12-6. Example Inner Join Result Set +-----------+----------------+ | last_name | dept_name | +-----------+----------------+ | Borg | Headquarters | | Hill | Administration | | Wallace | Administration | | Wallace | Administration | | Bell | Research | | Marrow | Research | | English | Research | | Smith | Research | +-----------+----------------+

Outer joins are similar to inner joins but in this case, we are interested in obtaining all of the rows from the left, right, or both tables. That is, we include the rows from the table indicated (left, right, or both also called full) regardless of whether there is a matching row in the other table. Each of these operations can be represented by a slight variance of the general outer join algorithm. Users specify outer joins in a SQL SELECT command by listing the desired conditions in the FROM clause and invoking one of the options (left, right, full). Some database systems default to using left if the option is omitted. For example, the following command joins the result set from the staff table to the directorate table, returning a result set of all employees and the directorate: SELECT staff.last_name, directorate.dept_name FROM staff LEFT OUTER JOIN directorate on staff.dept_id = directorate.id Note that this differs from the inner join as no rows from the left table are omitted. Listing 12-7 shows the basic outer join algorithm. The following sections describe how the algorithm implements each of the three types of outer joins. Listing 12-7. The Outer Join Algorithm begin sort relation a as rel_a on join column(s) sort relation b as rel_b on join column(s) do get next tuple from rel_a get next tuple from rel_b if type is FULL if join column values match join conditions write attribute data from both tuples to client else if rel_a has data write NULLS for rel_b

Under a more aggressive library management, each assembly has its own folder that contains three more folders, as shown in Figure 5-4.

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