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Be cautious when using SQL functions in WHERE conditions. Under most circumstances, a column with a function applied to it cannot be matched by an index. So, for large tables, using functions in WHERE conditions can lead to truly memorable performance problems. Did you notice that the order of the rows in the result set changed when the UPPER function was used in the WHERE clause I used Oracle for the preceding queries, so your results with another DBMS may vary. But why did it happen First, there was no ORDER BY clause, so the DBMS is not required to return the rows in any particular order. Second, it used an index to nd the rows in the rst example and simply scanned the table in the second example; obviously, the index isn t in the same order as the rows in the table. The lesson here is to always specify an ORDER BY if the order of rows in the result set matters to you.

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PRODUCTS CHAR(3) NOT NULL, CHAR(5) NOT NULL, VARCHAR(20) NOT NULL, MONEY NOT NULL, INTEGER NOT NULL, (MFR_ID, PRODUCT_ID))

Figures A-2 through A-6 show the contents of each of the five tables in the sample database. The query results in examples throughout the book are based on the data shown in these figures.

Appendix A:

The LOWER function does just the opposite of the UPPER function it shifts any letters in the character string to lowercase letters. Here are the same examples using the LOWER function: List the comedy movies (MOVIE_GENRE_CODE = Comdy ) with the titles in lowercase text. Note that a column alias is used to make sure the column name MOVIE_TITLE appears in the result set.

Figure A-2.

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If you live in a climate where sun is a rare treat and it is often overcast, you might like to experiment with a couple of additional cells in series to increase the power produced.

Figure A-3.

Figure A-4.

Figure A-5.

SELECT LOWER(MOVIE_TITLE) AS MOVIE_TITLE FROM MOVIE WHERE MOVIE_GENRE_CODE = 'Comdy'; MOVIE_TITLE ------------------------something's gotta give 50 first dates matchstick men the school of rock 4 rows selected.

Appendix A:

Figure A-6.

he database systems vendors profiled in this appendix have been selected because of their unique positions within the broader database industry. They include the providers of the leading enterprise-class DBMS products, some smaller companies that are leaders in new technology areas, pioneers in newer segments of the database market, and vendors that focus on embeddable database technology. Any compilation like this cannot possibly be exhaustive, and the omission of a company does not mean that its products or capabilities are inferior to those of the vendors profiled here. Collectively, these companies and their profiles as presented, illustrate the landscape of today s multibillion-dollar database software and services market. The vendors are:

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I A2i, Inc. I Arbor Software (now Hyperion Solutions Corporation) I Birdstep Technology I Computer Associates (Jasmine, Ingres) I Computer Corporation of America (Model 204) I Empress Software I eXcelon (ObjectStore, XIS) I Gupta Technologies (SQLBase) I Hewlett-Packard (NonStop SQL) I IBM Corporation (DB2, Informix, Cloudscape) I Informix Software (now part of IBM) I Microsoft Corporation (SQL Server) I MySQL AB I Objectivity I Oracle Corporation (Oracle, Rdb/VMS) I Persistence Software I Pervasive Software I PointBase I PostgreSQL I Quadbase Systems I Red Brick Systems (now part of Informix Software) I Sybase, Inc. I TimesTen Performance Software I Versant Corporation

As with the UPPER function, you can use the LOWER function in a WHERE clause when you aren t sure about the case of the text you are trying to match. List movies that have the word of in the title, regardless of whether it is capitalized or not. Note the combined use of the LIKE operator and LOWER function. Also note that you must handle special cases where the word of could be the rst word or last word in the title (that is, where it might not have a space before it or after it). These cases don t actually exist in the sample database, but they could, and you cannot simply use LIKE %of% or you might select a title because it had a word like often in it. The lesson here is that you have to know something about what might be in the data in order to write SQL that will always produce the expected result.

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