A technical blog about my projects, challenges, and discoveries in the world of data warehousing using SQL Server, Power BI Desktop, DevExpress, and more.

Tuesday, October 18, 2011

Top Ten Things I Learned at SQL PASS Summit on 10/14/2011

Travel and busy-ness with my baby Destiny have prevented my posting this last installment in my list of top lessons learned at SQL PASS, but now here it is:

1. Buck Woody and Rob Farley are not only superstars in SQL technologies, they are talented as singer/songwriters too. Check out the video of the opening of the keynote session for proof. Cue it up at 00:02:27 to skip to the song. Their song was my favorite moment of the week.

2. On Wednesday I wrote that I wanted to learn more about Hadoop since it was part of a new feature of SQL Server 2012, and today I learned more about it than I really wanted to know, but the presentation by Dr. DeWitt was fascinating. Hadoop is a method of "divide and conquer" applied to massive amounts of unstructured (or more accurately loosely structured) data, the kind collected by websites such as Facebook, eBay, and Google.

3. If you add NOSPLASH after the path to SSMS executable in the shortcut properties, the application will open a few seconds faster. It does not seem like much, but it's a handy tip that I put in place right away.

4. If there are more than a couple of OR conjunctions in any given WHERE clause, using UNION ALL is probably a better approach. The query optimizer in SQL Server is much better at streamlining two or more small query conditions rather than one huge, complex one.

5. When possible, replace correlated subqueries in the SELECT clause with joins in the FROM clause. This is because the correlated subquery must execute once for every row in the main results, eliminating any optimization that is possible when the data are correlated in the FROM clause.

6. I learned how to create a "temporal snapshot fact table" for a data warehouse solution. This improves the efficiency of a "daily summary" fact table by using date ranges instead of individual days as the granularity level, ranges during which nothing changes in the data. I suspect this may come in handy when constructing fact tables for pledges and donations. It is definitely a nice concept to keep in the toolbox of report design.

7. I learned that the query optimizer can anticipate the best query plan even when part of the query statement has been "refactored" into a common table expression (CTE).

8. Thanks to Audrey Hammonds, I learned some great techniques for explaining CTEs effectively. I plan to use some of her presentation style and content ideas when I present an introduction to CTEs at SQL Saturday #96 in Washington, DC.

9. CROSS APPLY is comparable to an inner join and OUTER APPLY is comparable to a left join. In that same context, I learned that there is no difference in query efficiency to move a CROSS APPLY table valued expression into a correlated subquery within the SELECT clause. This is reassuring, since I have already made such a move with the FOR XML technique of turning row values into delimited strings.

10. Snow Crash by Neal Stephenson is a book I need to read. When Audrey referenced it in her presentation, about half the audience recognized it and praised it as a great read. She mentioned a few other books throughout her talk, but this one definitely stirred the strongest positive response.

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