条件聚合数据库查询及其性能含义

Question

I think this question is best asked with an example: if you want two counts from a table - say one with all the rows with a bit flag set to false and another with all of the ones set to true - is there a best practice for this kind of query and what are the performance implications of any approaches that could be taken?

To expand a little, and basing it off of the article below, how would separate queries compare to the version with the CASE evaluation in the SELECT list from a performance point of view? Are there other methods?

http://www.codeproject.com/Articles/310674/Conditional-Sums-in-SQL-Aggregate-Methods

Answer 1

SELECT [bitCol], count(*)
  FROM [table]
 GROUP BY [bitCol]

If that column is indexed it is an index scan followed by a stream aggregate.
Doubt you can do better than that

Answer 2

Other than Blam's way, I think there are three basic ways to get the desired result. I tested the three options below as well as Blam's on my system. The results I found were as follows. Also, a side note, we didn't have any bit data in our system so I counted an indexed column with two values ("H" or "R").

Using Conditional Aggregates method resulted in the fastest performance. Using Blam's Grouping with an Aggregate method resulted in the second fastest way, consistently taking about 33% longer than the Conditional Aggregates. The Two Separate Select Statements method was the third fastest, consistently taking close to 50% longer than the Conditional Aggregates. Finally, the Joins method took the longest, and was close to 1000% slower than the Conditional Aggregates. The joins were expected (by me) to take the longest as you're joining to that table multiple times. The reason I included this method is because it was not discussed (possibly for obvious reasons) in the question; all performance issues aside, it is a viable if not extremely slow option. The two separate select statements also makes sense as you're running two separate aggregates, accessing that table two separate times.

I'm not sure what accounts for the differences between the conditional aggregate method and Blam's method. I've always been pleasantly surprised by the speed and performance of case statements, and today was no different.

I think the case statement method, aside from the performance considerations, is possibly the most versatile method. It allows you to work with just about any type of field and facilitates the selection of a subset of values, whereas Blam's Grouping with an Aggregate method would show all possible column values unless a Where clause were included.

Conditional Aggregates

Select SUM(Case When bitcol = 1 Then 1 Else 0 End) as True_Count
    , SUM(Case When bitcol = 0 Then 1 Else 0 End) as False_Count

From Table;

Two separate select statements

Select Count(1) as True_Count

From Table

Where bitcol = 1;

Select Count(1) as False_Count

From Table

Where bitcol = 0;

Using Joins

Select Count(T2.bitcol) as True_Count
    , Count(T3.bitcol) as False_Count

From Table T1
Left Outer Join Table T2
    on T1.ID = T2.ID
Left Outer Join Table T3
    on T1.ID = T3.ID;