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Part II
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Note Due to the randomness introduced by using rand, the results will vary every time you run the
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Listing 11-3 contains a query in which we use the BETWEEN predicate on the partitioning column.
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Iterative approaches apply some form of loops or recursion. Many iterative algorithms traverse graphs. Some traverse graphs a node at a time and are usually implemented with cursors, but these are typically very slow. I will focus on algorithms that traverse graphs one level at a time using a combination of iterative or recursive logic and set-based queries. Given a set of nodes U, the next level of subordinates refers to the set V, which consists of the direct subordinates (children) of the nodes in U. In my experience, implementations of iterative algorithms that traverse a graph one level at a time perform much better than the ones that traverse a graph one node at a time. Using iterative solutions has several advantages over the other methods. First, you don t need to materialize any extra information describing the graph to the database besides the node IDs in the edges. In other words, you don t need to redesign your tables. The solutions traverse the graph by relying solely on the stored edge information for example, (mgrid, empid), (assemblyid, partid), (city1, city2), and so on. Second, most of the solutions that apply to trees also apply to the more generic digraphs. In other words, most solutions that apply to graphs where only one path can lead to a given node also apply to graphs where multiple paths may lead to a given node. Finally, most of the solutions that I will describe in this section support a virtually unlimited number of levels. I will use two main tools to implement solutions in my examples: user-de ned functions (UDFs) with loops and recursive common table expressions (CTEs). The core algorithms are similar in both versions. In my solutions, I focused on UDFs and CTEs, but note that in some cases when performance of a UDF or CTE is not satisfactory, you might get better performance by implementing a solution with a stored procedure. Stored procedures give you more control for example, you can materialize and index interim sets in temporary tables. However, I used UDFs and CTEs because I wanted to focus on the algorithms and the clarity of the solutions.
Figure 5-13 : The files created by Visual Studio .NET for the ControlShowAndTell example Listing 5-10 shows the Global.asax.vb file for the ControlShowAndTell example, a file that contains the code elements somewhat analogous to the event handlers in Global.asa in classic ASP. Listing 5-10 Global.asax.vb, generated by Visual Studio .NET
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Joins and Set Operations
s If you are running the Server Edition of the Mac OS, note that MySQL comes preinstalled. To access Tip
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