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Category: T-SQL

Common Table Expressions

Published 2016-01-07 by Kevin Feasel

Aaron Bertrand shows us Common Table Expressions:

A CTE is probably best described as a temporary inline view – in spite of its official name, it is not a table, and it is not stored (like a #temp table or @table variable). It operates more like a derived table or subquery, and can only be used for the duration of a single SELECT, UPDATE, INSERT, or DELETE statement (though it can be referenced multiple times within in that statement).

This is a great article on CTEs; give it a read, even if you’re familiar with them.

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Use Parentheses Wisely

Published 2016-01-04 by Kevin Feasel

Jen McCown plays around with the AND and OR operators:

Specifically, how is it evaluated when your where clause says “WHERE This AND That OR Something AND that”, without any clarifying parenthesis?

Let’s play around with this. The simplest test scenario is a SELECT 1. If I get a 1 back, that means my WHERE clause evaluated to true, right? Right.

Parentheses should clarify statements.  If I see an “AND” and an “OR” in a WHERE clause, I want to see parentheses, even if you’ve gotten it right.  It’s too easy to misinterpret precedence.

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Parameterizing Procedures

Published 2015-12-25 by Kevin Feasel

Monica Rathbun shows how to combine several report queries:

I try to parameterize as many stored procedures as possible. This not only minimizes the amount of procedures I need to maintain, it in my opinion is a much cleaner way to code. It disturbs me when I see multiple stored procedures that pull the exact same data, but may have slight differences between them. Whether it be a sort, a where clause, or even just an extra field or two that makes it different, some developers think you need a different procedure for each one . Why not consolidate and parameterize?

The next step might be using dynamic SQL to build a query if there’s as much overlap as we see in Monica’s example.

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Optimizing Update Queries

Published 2015-12-22 by Kevin Feasel

Paul White has an article.  Read it:

The point is that there is an awful lot more going on inside SQL Server than is exposed in execution plans. Hopefully some of the details discussed in this rather long article will be interesting or even useful to some people.

It is good to have expectations of performance, and to know what plan shapes and properties are generally beneficial. That sort of experience and knowledge will serve you well for 99% or more of the queries you will ever be asked to tune. Sometimes, though, it is good try something a little weird or unusual just to see what happens, and to validate those expectations.

Optimizing update queries seems trivial at first, but as Paul shows, we have a few more tools at our disposal than is apparent at first glance.

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Table Sampling

Published 2015-12-17 by Kevin Feasel

Ginger Grant shows a couple of techniques for sampling from tables:

The random sample that TABLESAMPLE provides is based on the number of data pages, not the number of records. If you want the number of rows to be specifically limited you will need to use Top(n) as well. I’ve written all my samples based upon AdventureWorksDW so you can run them for yourself later. I’ve listed the variety of ways to call TABLESAMPLE and shown the number of records returned.

TABLESAMPLE is useful for spelunking, but is somewhat limited otherwise.

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Dynamic Pivoting

Published 2015-12-16 by Kevin Feasel

Michael Bourgon has a pivot script:

Say you have records from your monitor that happens to Track EventLogs.
We’ll call it EventLog_Tracking for argument’s sake (hint hint http://thebakingdba.blogspot.com/2015/05/powershell-eventlogtracking-capturing.html) and want to look at trends over time.

Dynamic pivoting is possible (I have an example en passant in a tally table presentation I created a couple years back), but it’s not the easiest thing in the world.

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