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--- 50 row(s) selected.
•
Return the SALARY of 50 sales people. In this case, the table is clustered on EMPID. If the
optimizer chooses a plan to access rows using the primary access path, the result consists
of salaries of the 50 sales people with the smallest employee identifiers.
SELECT salary
FROM salesperson
SAMPLE FIRST 50 ROWS;
SALARY
-----------
175500.00
137000.10
136000.00
138000.40
75000.00
90000.00
...
--- 50 row(s) selected.
•
Return the SALARY of the youngest five sales people, skip the next 15 rows, and repeat this
process until there are no more rows in the intermediate result table. Note that you cannot
specify periodic sampling with the sample size larger than the period.
SELECT salary
FROM salesperson
SAMPLE PERIODIC 5 ROWS EVERY 20 ROWS SORT BY age;
SALARY
-----------
90000.00
90000.00
28000.00
27000.12
136000.00
36000.00
...
--- 17 row(s) selected.
In this example, there are 62 rows in the SALESPERSON table. For each set of 20 rows, the
first five rows are selected. The last set consists of two rows, both of which are selected.
•
Compute the average salary of a random 10 percent of the sales people. You will get a
different result each time you run this query because it is based on a random sample.
SELECT AVG(salary)
FROM salesperson
SAMPLE RANDOM 10 PERCENT;
(EXPR)
--------------------
61928.57
--- 1 row(s) selected.
•
Compute the average salary of a random 10 percent of the sales people using cluster sampling
where each cluster is 4 blocks. You will get a different result each time you run this query
because it is based on a random sample.
SAMPLE Clause
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