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Paul White: Page Free Space

A technical SQL Server blog from New Zealand. See also my articles on SQLperformance.com

February 2011 - Posts

  • SQL Server Bug: Slow T-SQL Sums and Averages

    It’s a curious thing about SQL that the SUM or AVG of no items is not zero, it’s NULL. In this post, you’ll see how this means your SUM and AVG calculations might run at half speed, or worse. As with most of my blog entries though, today’s instalment is not so much about the result, but the journey we take to get there. Before we get started on that, I just want to mention that there’s a problem with the Google Reader feed for this blog, so those of you that use that will have missed two recent entries: Seeking Without Indexes and Advanced TSQL Tuning: Why Internals Knowledge Matters. Accessing the site directly always works of course :) Ok, on to today’s story. Take a look at this query: Read More...
  • Advanced TSQL Tuning: Why Internals Knowledge Matters

    There is much more to query tuning than reducing logical reads and adding covering nonclustered indexes. Query tuning is not complete as soon as the query returns results quickly in the development or test environments. In production, your query will compete for memory, CPU, locks, I/O and other resources on the server. Today’s entry looks at some tuning considerations that are often overlooked, and shows how deep internals knowledge can help you write better TSQL. As always, we’ll need some example data. In fact, we are going to use three tables today, each of which is structured like this: Read More...
  • I see no LOBs!

    Is it possible to see LOB (large object) logical reads from STATISTICS IO output on a table with no LOB columns? I was asked this question today by someone who had spent a good fraction of their afternoon trying to work out why this was occurring – even going so far as to re-run DBCC CHECKDB to see if any corruption had taken place. The table in question wasn’t particularly pretty – it had grown somewhat organically over time, with new columns being added every so often as the need arose. Nevertheless, it remained a simple structure with no LOB columns – no TEXT or IMAGE, no XML, no MAX types – nothing aside from ordinary INT, MONEY, VARCHAR, and DATETIME types. To add to the air of mystery, not every query that ran against the table would report LOB logical reads – just sometimes – but when it did, the query often took much longer to execute. Ok, enough of the pre-amble. I can’t reproduce the exact structure here, but the following script creates a table that will serve to demonstrate the effect: Read More...
  • Seeking Without Indexes

    A seek can contain one or more seek predicates – each of which can either identify at most one row in a unique index (a singleton lookup) or a range of values (a range scan). When looking at a query plan, we will often need to look at the details of the seek operator in the Properties window to see how many operations it is performing, and what type of operation each one is. As you saw in the first post in this mini-series, the number of hidden seeking operations can have an appreciable impact on performance. Measuring Seeks and Scans I mentioned in my last post that there is no way to tell from a graphical query plan whether you are seeing a singleton lookup or a range scan. You can work it out – if you happen to know that the index is defined as unique and the seek predicate is an equality comparison, but there’s no separate property that says ‘singleton lookup’ or ‘range scan’. This is a shame, and if I had my way, the query plan would show different icons for range scans and singleton lookups – perhaps also indicating whether the operation was one or more of those operations underneath the covers. In light of all that, you might be wondering if there is another way to measure how many seeks of either type are occurring in your system, or for a particular query. As is often the case, the answer is yes – we can use a couple of dynamic management views (DMVs): sys.dm_db_index_usage_stats and sys.dm_db_index_operational_stats. Read More...
  • So…is it a Seek or a Scan?

    You’re probably most familiar with the terms ‘Seek’ and ‘Scan’ from the graphical plans produced by SQL Server Management Studio (SSMS). The image to the left shows the most common ones, with the three types of scan at the top, followed by four types of seek. You might look to the SSMS tool-tip descriptions to explain the differences between them: Not hugely helpful are they? Both mention scans and ranges (nothing about seeks) and the Index Seek description implies that it will not scan the index entirely (which isn’t necessarily true). Recall also yesterday’s post where we saw two Clustered Index Seek operations doing very different things. The first Seek performed 63 single-row seeking operations; and the second performed a ‘Range Scan’ (more on those later in this post). I hope you agree that those were two very different operations, and perhaps you are wondering why there aren’t different graphical plan icons for Range Scans and Seeks? I have often wondered about that, and the first person to mention it after yesterday’s post was Erin Stellato (twitter | blog): Read More...
  • When is a Seek not a Seek?

    The following script creates a single-column clustered table containing the integers from 1 to 1,000 inclusive. IF OBJECT_ID(N'tempdb..#Test', N'U') IS NOT NULL DROP TABLE #Test ; GO CREATE TABLE #Test ( id INTEGER PRIMARY KEY CLUSTERED ); ; INSERT #Test (id) SELECT V.number FROM master.dbo.spt_values AS V WHERE V.[type] = N'P' AND V.number BETWEEN 1 AND 1000 ; Let’s say we need to find the rows with values from 100 to 170, excluding any values that divide exactly by 10. One way to write that query would be: SELECT T.id FROM #Test AS T WHERE T.id IN ( 101,102,103,104,105,106,107,108,109, 111,112,113,114,115,116,117,118,119, 121,122,123,124,125,126,127,128,129, 131,132,133,134,135,136,137,138,139, 141,142,143,144,145,146,147,148,149, 151,152,153,154,155,156,157,158,159, 161,162,163,164,165,166,167,168,169 ) ; That query produces a pretty efficient-looking query plan: Read More...
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