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Many application developers simply write SQL statements off the top of their heads without giving much thought to designing them for ef cient processing. This is an easy trap to fall into because SQL is a nonprocedural language that gives the false impression that the form of the statement does not matter provided it produces the correct result set. Statements that are not designed can introduce enormous performance issues. For example, I recently reviewed an SQL statement that retrieved about six million rows of data each time it was executed. The application that issued the SQL only required the rst row found. When this statement was run, the entire database seized until the processing was complete. It felt like the lights dimmed in the building from all the resources this one query consumed. It took the developer who xed the problem only about an hour to turn the query into a very ef cient one, but a little bit of thought by the original developer would have avoided the crisis entirely. Here are some considerations regarding query design: Know your data. When writing the SQL statement, you should have some idea of how many rows are in each table, how selective your WHERE predicates are, and how many rows you expect in the result set. The larger the number of rows involved, the more time you should spend thinking about the best way to write the SQL statement. Minimize returned rows. The fewer the rows in the result set, the more ef ciently the query will run. Avoid scans of large tables. For tables over 1000 rows or so, scanning all the rows in the table instead of using an index can be expensive in

An operation that maps characters from one character set to characters in another set Transliterations can include such operations as translating characters from uppercase to lowercase or from one alphabet into another A mechanism for generating successive numeric data values (integers), one at a time Sequence generators retain a current base value, which is used as the basis for generating the next sequential value..

There are two major issues to consider when you re trying to increase security. The first is authentication, and the other is encryption. Authentication is designed to determine whether a user is who he or she claims to be. Encryption, on the other hand, is used to prevent the usability of data in case the wrong people intercept it. Most forms of security measures use these two concepts to prevent the unauthorized use of information.

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ANY The XML data is of any of the types supported by the SQL implementation. XMLSCHEMA The XMLSCHEMA type refers to a registered XML schema that has been made known to the database server. The three most common are:

terms of resources required. And, of course, the larger the table, the more expensive a table scan becomes. Full table scans occur in the following situations: The query does not contain a WHERE clause to limit rows. None of the columns referenced in the WHERE clause matches the leading column of an index on the table. Index and table statistics have not been updated. Most RDBMS query optimizers use statistics to evaluate available indexes, and without statistics, a table scan may be seen as more ef cient than using an index. At least one column in the WHERE clause does match the rst column of an available index, but the comparison used obviates the use of an index. These cases include the following: Use of the NOT operator (for example, WHERE NOT CITY = New York ). In general, indexes can be used to nd what is in a table, but cannot be used to nd what is not in a table. Use of the NOT EQUAL operator (for example, WHERE CITY <> New York ). Use of a wildcard in the rst position of a comparison string (for example, WHERE CITY LIKE %York% ). Use of an SQL function in the comparison (for example, WHERE UPPER(CITY) = NEW YORK ). Avoid unnecessary columns. The wider the data in each row in the result set, the more disk space and memory that is required for intermediate operations such as sorts and to hold the result set. Avoid unnecessary tables. query. The fewer the tables, the more ef cient the

Target Namespace URI (Uniform Resource Identifier)

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http://www.w3.org/2001/XMLSchema http://www.w3.org/2001/XMLSchema-instance http://standards.iso.org/iso/9075/2003/sqlxml

For SQL implementations that do not support the secondary type modifier, ANY is assumed as a default.

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Avoid sorts of large result sets. Sorts are expensive, especially when the rows being sorted will not t in memory. When the result set is expected to be very large, sorts should be avoided. Most optimizers will use an index if it can eliminate the need for a sort, but creating an index solely to avoid a sort of a large number of rows is probably not wise because of the overhead required to maintain the index. Match data types in predicates. Whether a predicate compares two column values as is done with joins, or a column value and a literal as is done when ltering rows, it is important for the data types to match. When

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