Database Design Issues in Java

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8 Database Design Issues
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In this chapter, you learn important details about the relationships between database tables and how to apply these relationships to real world data modeling. You typically end up with correctly normalized data by following the layered data modeling approach that you learn in this chapter, but if the world throws a poorly normalized database your way, you can use the data-normalization steps that we also discuss to give it the correct structure. Remember to always define column defaults and constraints where possible in your tables, as such definitions prevent invalid data from entering your database. Pay special attention to preventing zero-length strings from entering NOT NULL columns by checking the length of trimmed values, because Web forms submit empty fields as zero-length strings that actually pass the NOT NULL test. You also learn some important details about indexes that can help you visualize how they work internally, which guide you on how and when they should be applied in your database. Careful index design and regular maintenance keeps your database running quickly and smoothly. Finally, don t try to produce analysis or complicated reports from transactional data; instead, transform transactional data into summary data, store it in a separate database, and produce reports from this database. 9 can further help you visualize how an SQL statement is processed, which also helps you write error-free SQL. You learn easy-to-follow rules for writing statements containing GROUP BY, HAVING, and DISTINCT clauses and aggregate functions, which are commonly misunderstood and misused.
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Putting Databases to Work
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his chapter can help you better understand complicated SQL containing multitable joins, group-related clauses, and aggregate functions by far the most problematic topics for most database developers. You also learn the correct way to handle database exceptions and incorporate them as actual functionality in your ColdFusion application. You learn, too, how to increase performance by caching queries in memory for fast access. You can memorize SQL clauses and Bachus-Naur forms until you re blue in the face, but you still end up playing ready-fire-aim trying to write complicated SQL that actually works unless you have a clear picture of exactly how SQL processes statements. Your first step in clearly visualizing SQL is to understand the nature of relational result sets.
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Visualizing complicated relational result sets Understanding what your database can and cannot do Leveraging database exceptions in your application Knowing how and when to cache queries
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The code in this chapter is not supported by Access, so if you want to follow along with the listings in this chapter, run the files 9DDL.sql and 9Data.sql on a new SQL Server 2000 database, and setup a data source named CFMXBible that connects to this new database. This new database contains additional data and tables to help illustrate the various types of joins and the results that they produce.
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Understanding All Relational Result Sets
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We added All to the title of this section for an important reason that was already stated in 5: All SQL query results are in the form of a single table of rows and columns. Whether the result is from the query of a single table or a complicated relational query involving 15 tables doesn t matter all query results are in the form of a single table of rows and columns. Consider Listing 9-1, which produces a relational query result that, like all query results, is in the form of a single table.
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Part II Using ColdFusion MX with Databases
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Listing 9-1: A SELECT statement that produces a relational query result
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SELECT c.CompanyID, c.CompanyName, e.Lastname, e.Firstname, e.Salary FROM Company c INNER JOIN Employee e ON c.CompanyID = e.CompanyID
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Listing 9-1 is conceptualized in Figure 9-1. Notice that the result of joining these two tables results in a single table. What s this Isn t this one of those Venn diagrams Remember when Mr. Suber, your junior high school math teacher, told you that you really would use them one day in the real world, and you balked Time to call him up and apologize! An INNER JOIN is the intersection of the two data sets contained in the two tables being joined, as shown in Figure 9-1. Why is this conceptualization critical to writing flawless SQL Because we now can easily visualize any type of join between two tables, as shown in Figure 9-2: Considering Figure 9-2, we can now easily describe what is really happening with each of these types of JOINs. An INNER JOIN result consists of the columns selected from both tables, but it contains only those rows that match the JOIN key values (specified in the ON clause) in both joined tables, as you can see from Listing 9-1 and Figure 9-1. A LEFT OUTER JOIN result consists of the columns selected from both tables, and it contains all the rows in the left-side table regardless of whether any of them match the JOIN key values in the right-side table. The query columns selected from the left-side table contain data from that table. For each row in the query result, if a JOIN key value from the left-side table matches a JOIN key value from the right-side table, the query columns selected from the right-side table contain column data from that table; if not, those columns contain nulls. Listing 9-2 is Listing 9-1 modified to produce a LEFT OUTER JOIN, and Figure 9-3 displays the query result.
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