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Throughout this book, the acceptable forms of a SQL statement are illustrated by a syntax diagram, such as the one shown in Figure 5-2. A valid SQL statement or clause is constructed by "following the line" through the syntax diagram to the dot that marks the end of the diagram. Keywords in the syntax diagram and in the examples (such as DELETE and FROM in Figure 5-2) are always shown in UPPERCASE, but almost all SQL implementations accept both uppercase and lowercase keywords, and it's often more convenient to actually type them in lowercase.

The optimizer for a warehousing database may make a quite different decision, based on information accumulated during the load process about the distribution of data values within the database..

11:

As with load-time performance, maximizing the runtime performance of a warehouse is an ongoing task for the database administrator. Newer revisions of DBMS software often provide performance benefits, as do higher-performance processors or more processors.

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6 View updating rule All views that are theoretically updateable are also updateable by the system 7 High-level insert, update, and delete The capability of handling a base relation or a derived relation as a single operand applies not only to the retrieval of data, but also to the insertion, update, and deletion of data 8 Physical data independence Application programs and terminal activities remain logically unimpaired whenever any changes are made in either storage representations or access methods 9 Logical data independence Application programs and terminal activities remain logically unimpaired when information-preserving changes of any kind that theoretically permit unimpairment are made to the base tables 10 Integrity independence Integrity constraints specific to a particular relational database must be definable in the relational data sublanguage and storable in the catalog, not in the application programs 11 Distribution independence A relational DBMS has distribution independence 12 Nonsubversion rule.

If a relational system has a low-level (single record at a time) language, that low level cannot be used to subvert or bypass the integrity rules and constraints expressed in the higher-level relational language (multiple records at a time) Although the controversy has long since died out, the 12 rules are interesting from a historical perspective, because they resolved the issue once and for all, and they do offer a good informal working definition Rule 1 is basically the single-sentence fundamental definition presented earlier in this chapter; the others provide additional refinement and requirements Rule 2 stresses the importance of primary keys for locating data in the database The table name locates the correct table, the column name finds the correct column, and the primary key value finds the row containing an individual data item of interest.

Summary

Rule 3 requires support for missing data through NULL values, which are described in 5 Rule 4 requires that a relational database be self-describing, through system tables whose columns describe the structure of the database itself These tables are described in 16 Rule 5 mandates using a relational database language, such as SQL, although SQL is not specifically required The language must be able to support all the central functions of a DBMS, not just database queries Rule 6 deals with views, which are virtual tables used to give various users of a database different views of its structure Views are described in 14 Rule 7 stresses the set-oriented nature of a relational database It requires that rows be treated as sets in insert, delete, and update operations It prohibits systems that support only row-at-a-time, navigational modification of the database.

Data warehousing is a rapidly growing part of the market for SQL-based relational databases and is one with a set of specialized requirements: I Warehouse databases are optimized for the workload of typical business analysis queries, which is quite different from OLTP workloads. I Specialized utility programs provide high-performance loading of the warehouse and analysis tools for taking advantage of warehoused data. I Specialized database schema structures, such as the star schema, are typically used in warehouse applications to support typical business analysis queries and optimize performance. I SQL extensions are frequently used to support typical business analysis queries involving time series and trend analysis, rank orderings, and time-based comparisons. I Careful design of a large warehouse is required to provide the correct balance between load-time performance and runtime performance.

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