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To demonstrate the logical aspects of the solutions to the gaps and islands problems, I ll use a table called NumSeq. Run the code in listing 1 to create the table NumSeq and populate it with sample data.

(* Start a tell block to the Finder Open a window to the Documents folder Set the view to Cover Flow *)

SET NOCOUNT ON; USE tempdb; -- dbo.NumSeq (numeric sequence with unique values, interval: 1) IF OBJECT_ID('dbo.NumSeq', 'U') IS NOT NULL DROP TABLE dbo.NumSeq; CREATE TABLE dbo.NumSeq ( seqval INT NOT NULL CONSTRAINT PK_NumSeq PRIMARY KEY ); INSERT INTO dbo.NumSeq(seqval) VALUES(2); INSERT INTO dbo.NumSeq(seqval) VALUES(3); INSERT INTO dbo.NumSeq(seqval) VALUES(11); INSERT INTO dbo.NumSeq(seqval) VALUES(12); INSERT INTO dbo.NumSeq(seqval) VALUES(13); INSERT INTO dbo.NumSeq(seqval) VALUES(31); INSERT INTO dbo.NumSeq(seqval) VALUES(33); INSERT INTO dbo.NumSeq(seqval) VALUES(34); INSERT INTO dbo.NumSeq(seqval) VALUES(35); INSERT INTO dbo.NumSeq(seqval) VALUES(42);

The column seqval is a unique column that holds the sequence values. The sample data represents a sequence with ten unique values with four gaps and five islands. The solutions to the gaps problem should return the ranges of missing values, as table 1 shows.

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Q: A:

The solutions to the islands problem should return the ranges of existing values, as table 2 shows. When discussing performance, I ll provide information based on tests I did against a table called BigNumSeq with close to 10,000,000 rows, representing a numeric sequence with unique values, with 10,000 gaps. Run the code in listing 2 to create the

Is it okay to use several end-of-line comments instead of a block comment Yes, it s fine although purists may look down at you If you prefer to use several end-of-line comments in sequence rather than create a block comment, by all means do so Generally, though, a block comment is easier to read One other thing while we re talking about comments you can start a block comment after a statement of code on the same line if you like, but usually it s much clearer if you start the block comment on its own line

It might be tempting to go overboard on aggregation designs. Why not, if they are so powerful In addition to the obvious drawback of increased cube-processing time, there is also the issue of Analysis Services leveraging many specific aggregations to address individual queries when only a few are really necessary. Aggregations take disk space and memory, so designing the most efficient set of aggregations results in the best resource utilization. The target number of aggregations should be in the hundreds, or even fewer in smaller cubes. Remember that Analysis Services can leverage aggregations that are not specific to a query that has long been a differentiator between it and other OLAP products. Be sure that member counts are accurately specified, as well. These are input to the ADW to calculate the cost of designing an aggregation at a dimension level. This count is often calculated early in the cube design and never updated as members are

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subsequently added. As a result, the ADW may underestimate the overhead of creating an aggregation at that level. Analysis Services will not design an aggregation that is larger than one third of the underlying fact table. It uses the member counts to determine how large an aggregation will be. There are hierarchy types in Analysis Services that cannot adequately leverage aggregations. The most notable is parent-child, and this is one reason to limit parentchild hierarchies in your cube. If the number of levels is predictable, consider redesigning the dimension to create attributes for each level, and then create a standard user-defined hierarchy to designate each level and create attribute relationships from one to the other.

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Summary

3 Note: These are not actionable trades, but only guidelines Always use other indicators to confirm before buying or selling 4 Hint: For a longer-term perspective, change the period to Weekly, and press Update

This should serve as an introduction to aggregations and effective aggregation designs. Aggregations are an important aspect of well-performing OLAP solutions in all but the smallest cubes. Knowing the underlying fundamentals of a solid aggregation design is critical for high-performance cubes.

(* Start a tell block to the Finder Open a window to the Documents folder Set the view to Column view *)