Filtered Statistics

William Wolf shows us the value of filtered statistics:

Wolf only had 700 complaints, but 166,900 records were estimated for return. He is looking much worse than reality shows.

So, what is happening is that there are 3 possible employee results for complaints. It is rather simple. CE is taking the total amount of records(500,701) and dividing by 3 assuming that all 3 will have roughly the same amount of records. We see that along with the estimated number of records being the same, the execution plan operators are the same. For such a variation in amount of records, there must be a better way.

I rarely create filtered statistics, in part because I don’t have a good idea of exactly which values people will use when searching.  But one slight change to Wolf’s scenario might help:  having a filter where name = Sunshine and a filter where name <> Sunshine (or name is null).  That might help a case where there’s extreme skew with one value and the rest are much closer to uniformly distributed.

Related Posts

The Value Of Auto-Created Statistics

Brent Ozar is here to praise statistics auto-creation: Let me rephrase: before you even start playing around with statistics, make sure you haven’t taken away SQL Server’s ability to do this for you. I like to make fun of a lot of SQL Server’s built-in “auto-tuning” capabilities that do a pretty terrible job. Cost Threshold for […]

Read More

Configuring An Azure Runbook For Index Maintenance

Jim Donahoe explains how to perform index and statistics maintenance for Azure SQL Database, where you don’t have SQL Agent available: I had a lot of issues when I created my first one, and after discussing with some folks, they had the same issues.  I searched for the best blog posts that I could find […]

Read More

Categories

August 2017
MTWTFSS
« Jul Sep »
 123456
78910111213
14151617181920
21222324252627
28293031