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asp.net pdf 417

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To deliver a performance benefit, an aggregate schema need not have a grain that exactly matches the grain of the query to be optimized. This may be obvious, but is worth noting. As long as the aggregate contains the dimensionality necessary to formulate the query, it can be used to answer the question. Data within the aggregate may be further summarized at query time. The query will still benefit from the pre-summarization performed when the aggregate was created. For example, the aggregate schema in Figure 15-1 stores order_dollars by month, product, and salesrep. It can be used for any query that requires this level of detail or less. A report that lists order dollars by product for January 2009 can leverage the aggregate star, even though it does not require information about the salesperson. The DBMS will have to do some aggregation, but it will be far less work than would be required if it were using the original order_facts star. Obviously, a single aggregate cannot provide a performance benefit for every query. Multiple aggregates can summarize the same base schema in different ways. Rather than represent successive levels of summarization, each aggregate pre-summarizes data across a different set of dimensions. This maximizes the number of queries that can be supported by aggregate tables.

asp.net pdf 417

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The problem lies in sudden sellouts and profit-taking. Stocks with large institutional ownership might have adequate shares for trading in normal, steady markets, but markets can change suddenly. If 50 or 70 percent of the stockholders are institutions and they begin selling, their quick exit can be devastating to the stock price. How Much Is Too Much To begin with, it s not as easy to find stocks without any institutional ownership. It s estimated that institutions own at least 50 percent of the entire stock market. So how much is enough, and what constitutes too much institutional ownership If the problem caused by institutions is price volatility, perhaps that should become the issue rather than the amount of ownership.

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There will always be queries that cannot be optimized through the use of aggregates. Any query that requires access to the granular data must be directed at the original star. For example, limiting query results to order lines with a dollar amount over $500 cannot be done without the granular data. In this case, an aggregate star will not help. If performance is an issue here, the report may be run during a batch window, or a derived table may be designed to store precomputed results. Also note the presence of aggregates to support other queries may make more system resources available to answer this one, even if it must make use of the base schema.

asp.net pdf 417

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The State of Wisconsin Investment Board (SWIB) took on the issue of corporate governance and executive compensation with a September 2002 conference that brought together institutional shareholders, public policymakers, and corporate leaders Findings at the conference included changes in the way stock options are typically granted; specifically advocating a longer vesting period and requiring that once options were exercised, the stock should be held for a minimum of one to two years The group also believed one of the primary reasons for excessive executive compensation was the lack of good succession planning by companies and their boards The chorus of criticism on the issue of executive compensation has widened to include government and public officials Former New York Federal Reserve President William J McDonough, who was regarded as the second most powerful person at the Fed behind Chairman Alan Greenspan, called on US corporate executives to take pay cuts.

To reap the benefit of an aggregate table, it is necessary to rewrite a query to access it. When a summary conforms with the original schema, this is a relatively simple process at least for technical personnel. For any given query, optimal performance will depend on choosing the most summarized schema capable of responding.

12,000 Dow Industrial Average Levels 11,000 June 2, 2001, Change in Trend Long-term Trend lines 10,000 5,000,000,000 4,500,000,000 4,000,000,000 9,000 3,500,000,000 3,000,000,000 8,000 Dow Industrials Volume 7,000 2,500,000,000 2,000,000,000 1,500,000,000 6,000

Conformance of the aggregate star to the base star makes it relatively simple to write queries to take advantage of the aggregate. Because the two stars have a very similar structure and content, a query against the aggregate is structured in the same way it would be against the base star. The result sets are identical. It is also quite simple to rewrite a preexisting query to make use of an aggregate. Facts and dimension attributes share the same names in both stars; all that is necessary is to replace table names from the base schema with those from the aggregate. If any conformed rollup dimensions are present, it will be necessary to replace surrogate keys in the SQL statement as well. For example, using the base star in Figure 15-1, determining order dollars by product for January 2009 would require the following SQL statement:

asp.net pdf 417

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