DB2 UDB for z/OS Version 8 Performance Topics - IBM Redbooks

3.14.1 Performance
In V8 you can code SQL statements easily in one query when multiple distinct operations
need to be done for multiple columns before any column functions, such as AVG, COUNT, or
SUM are applied. This multiple distinct enhancement in V8 benefits usability of SQL by
reducing the amount of SQL statements or simplifying some queries. And it supports DB2
family compatibility by making it easier to move your programs to another platform.
Performance improvements are experienced when the multiple SQL statements are merged
into one.
The purpose of these measurements is to evaluate the improvement you can get by using a
single query statement specifying multiple DISTINCT keywords for multiple columns
compared to the case of using several query statements, each with one DISTINCT keyword.
In these tests we SELECT columns of all DECIMAL data and GROUP BY an indexed column.
First we measure the following sequence of four SELECT statements performing only one
SELECT COUNT(DISTINCT) for each one of the four columns (no buffer pool flush in
between):
1. SELECT COUNT(DISTINCT C1), C5 FROM T1 GROUP BY C5;
2. SELECT COUNT(DISTINCT C2), C5 FROM T1 GROUP BY C5;
3. SELECT COUNT(DISTINCT C3), C5 FROM T1 GROUP BY C5;
4. SELECT COUNT(DISTINCT C4), C5 FROM T1 GROUP BY C5;
Then we measure the performance of multiple distinct statements specifying more than one
DISTINCT keyword. These are the alternatives in DB2 V8 to the above SELECT statements.
We have three cases of using multiple COUNT(DISTINCT) on two, three, and four columns:
5. SELECT COUNT(DISTINCT C1), COUNT(DISTINCT C2), C5 FROM T1 GROUP BY C5;
6. SELECT COUNT(DISTINCT C1), COUNT(DISTINCT C2), COUNT(DISTINCT C3), C5
FROM T1 GROUP BY C5;
7. SELECT COUNT(DISTINCT C1), COUNT(DISTINCT C2), COUNT(DISTINCT C3),
COUNT(DISTINCT C4), C5 FROM T1 GROUP BY C5;
Figure 3-46 shows the percentage of improvement with the multiple distinct statements
compared to the total time of the single distinct statements. We are comparing the total time
of test cases 1 and 2 with test case 5, the sum of 1, 2, and 3, to test case 6, and the sum of 1,
2, 3, and 4, to test case 7.
The results show the percentage of the reduction of class 2 elapsed time and CPU time by
using multiple distincts. When we merge two SELECT single distinct statements into one
multiple distinct statement, there is a 40% elapsed time reduction. When we merge four
SELECT single distinct statements into one multiple distinct statement, we observe more than
55% elapsed time reduction.
Chapter 3. SQL performance 109