barcode vb.net 2010 Delivering Benefit in Software

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Delivering Benefit
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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.
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Part V
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PART V
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Performance
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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.
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Using Aggregates
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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.
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Writing (or Rewriting) Queries
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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:
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SELECT product, Sum(order_dollars) FROm day, product, order_facts WHERE day.month='January' AND day.year = 2009 AND product.product_key = order_facts.product_key AND day.day_key = order_facts.day_key GROuP BY product
Rewriting the query to take advantage of the aggregate requires no changes to the facts or dimensions in this SQL statement; all that is necessary is to replace the table names with
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those from the aggregate star. Within the time dimension, it will also be necessary to substitute month_key for day_key. The resulting query looks like this:
SELECT product, Sum(order_dollars) FROm month, product, order_facts_aggregate WHERE month.month='January' AND month.year = 2009 AND product.product_key = order_facts_aggregate.product_key AND month.month_key = order_facts_aggregate.month_key GROuP BY product
Changes from the original query are highlighted in bold. No facts or dimension attributes have changed; only the names of tables and, in the case of month, the name of the surrogate key. TiP The facts and dimension attributes in an aggregate star conform to those in the base star. Rewriting a query to take advantage of the aggregate involves replacing table names and key columns.
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