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Use the Analysis Services ADW to create an aggregation design for a 5 to 20 percent improvement. In general, the larger the cube, the lower the aggregation design percentage because of the increased overhead of creating aggregations on large cubes during processing. Remember that aggregation design occurs at the partition level, so be sure to apply the design to all appropriate partitions. Turn on query logging to capture a good representation of queries against the database. Preferably do this in a QA or test environment before end users initially start validating the cube, or for short intervals in production, if necessary. Logging has an overhead, so do not leave it on continually. Use the Aggregation Management tool in Analysis Services 2005 or usage-based optimization (UBO) in Analysis Services 2008 to design aggregations that will benefit the lengthiest queries from the previous step. When using UBO, increase the design goal to roughly 70 percent and only include longer running queries. Apply the aggregations designed in previous steps to all relevant partitions in the cube. This can be done in BIDS, the Aggregation Management tool, or via XML for Analysis (XMLA). Reprocess the partitions, either individually or as a whole, noting the processing time. Remember, the tradeoff for more aggregations is increased processing time. If the processing time is not feasible for your production environment, you will need to back off some of the aggregations. Repeat steps 2 5 periodically, perhaps monthly or quarterly, depending on your environment. Query patterns in an OLAP environment are prone to change over time, and revisiting the aggregation design compensates for this.

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Hugo Kornelis is co-founder and R&D lead of perFact BV, a Dutch company that strives to improve analysis methods and develop computer-aided tools that will generate completely functional applications from the analysis deliverable. The chosen platform for this development is SQL Server. In his spare time, Hugo likes to share and enhance his knowledge of SQL Server by frequenting newsgroups and forums, reading and writing books and blogs, and attending and speaking at conferences.

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1 Overbought: If the RSI line rises above 70, that s an overbought signal 2 Oversold: If the RSI line drops below 30, that s an oversold signal

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This chapter describes problems known as gaps and islands and their solutions. I start out with a description of gaps and islands problems, describe the common variations on the problems, and provide sample data and desired results. Then I move on to ways of handling gaps and islands problems, covering multiple solutions to each problem and discussing both their logic and performance. The chapter concludes with a summary of the solutions.

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Gaps and islands problems involve missing values in a sequence. Solving the gaps problem requires finding the ranges of missing values, whereas solving the islands problem involves finding the ranges of existing values. The sequences of values in gaps and islands problems can be numeric, such as a sequence of order IDs, some of which were deleted. An example of the gaps problem in this case would be finding the ranges of deleted order IDs. An example of the islands problem would be finding the ranges of existing IDs. The sequences involved can also be temporal, such as order dates, some of which are missing due to inactive periods (weekends, holidays). Finding periods of inactivity is an example of the gaps problem, and finding periods of activity is an example of the islands problem. Another example of a temporal sequence is a process that needs to report every fixed interval of time that it is online (for example, every 4 hours). Finding unavailability and availability periods is another example of gaps and islands problems. Besides varying in terms of the data type of the values (numeric and temporal), sequences can also vary in terms of the uniqueness of values. For example, the sequence can have unique values, that is, unique keys, or non-unique values, that is, order dates. When discussing solutions, for simplicity's sake I ll present them against a numeric sequence with unique values. I ll explain the changes you need to make to apply the solution to the variants.

Instead of an end-of-line comment, you can create a block comment A block comment is a comment that appears as its own block normally on multiple lines rather than a single line, although you can create single-line block comments if you want Block comments are good for presenting chunks of information without the distraction of having the two hyphens at the beginning of each line To create a block comment, type an opening parenthesis and an asterisk, the text of the comment, and another asterisk and a closing parenthesis For example:

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