Checking performance on XE, what is the best tools.

Question

Hi, all
I'm trying to see how better to use tuning tools and I'm on XE now. What is the simplest way to start with?
I do autotarace for now, which also give me Plan, is it good enough? or Does Expaln Plan shows something else?
I also tried to play with v$ but coulnd find them on XE, is it correct?
set autotrace on/off Apprecite your information, actually it's hard to find good explanation of going thru Plan.
Best
T

Answer 1

Tx, SB
I meant that I have hard time finding info how to anylyze Plan, how to find which action could be replaced, like let say i this sample from your link, looking at what numbers/steps you can tell where you can tune this sql?
EXPLAIN PLAN FOR
SELECT e.employee_id, j.job_title, e.salary, d.department_name
    FROM employees e, jobs j, departments d
    WHERE  e.employee_id < 103
       AND e.job_id = j.job_id
       AND e.department_id = d.department_id;
The resulting output table in Example 11-14 shows the execution plan chosen by the optimizer to execute the SQL statement in the example:
Example 11-14 EXPLAIN PLAN Output
| Id  | Operation                     |  Name        | Rows  | Bytes | Cost (%CPU)|
|   0 | SELECT STATEMENT              |              |     3 |   189 |    10  (10)|
|   1 |  NESTED LOOPS                 |              |     3 |   189 |    10  (10)|
|   2 |   NESTED LOOPS                |              |     3 |   141 |     7  (15)|
|*  3 |    TABLE ACCESS FULL          | EMPLOYEES    |     3 |    60 |     4  (25)|
|   4 |    TABLE ACCESS BY INDEX ROWID| JOBS         |    19 |   513 |     2  (50)|
|*  5 |     INDEX UNIQUE SCAN         | JOB_ID_PK    |     1 |       |            |
|   6 |   TABLE ACCESS BY INDEX ROWID | DEPARTMENTS  |    27 |   432 |     2  (50)|
|*  7 |    INDEX UNIQUE SCAN          | DEPT_ID_PK   |     1 |       |            |
Predicate Information (identified by operation id):
   3 - filter("E"."EMPLOYEE_ID"<103)
   5 - access("E"."JOB_ID"="J"."JOB_ID")
   7 - access("E"."DEPARTMENT_ID"="D"."DEPARTMENT_ID"
| Id  | Operation                       | Name          | Rows  | Bytes | Cost (%CPU)| Time     |
|   0 | SELECT STATEMENT                |               |     3 |   189 |     8  (13)| 00:00:01 |
|   1 |  NESTED LOOPS                   |               |       |       |            |          |
|   2 |   NESTED LOOPS                  |               |     3 |   189 |     8  (13)| 00:00:01 |
|   3 |    MERGE JOIN                   |               |     3 |   141 |     5  (20)| 00:00:01 |
|   4 |     TABLE ACCESS BY INDEX ROWID | JOBS          |    19 |   513 |     2   (0)| 00:00:01 |
|   5 |      INDEX FULL SCAN            | JOB_ID_PK     |    19 |       |     1   (0)| 00:00:01 |
|*  6 |     SORT JOIN                   |               |     3 |    60 |     3  (34)| 00:00:01 |
|   7 |      TABLE ACCESS BY INDEX ROWID| EMPLOYEES     |     3 |    60 |     2   (0)| 00:00:01 |
|*  8 |       INDEX RANGE SCAN          | EMP_EMP_ID_PK |     3 |       |     1   (0)| 00:00:01 |
|*  9 |    INDEX UNIQUE SCAN            | DEPT_ID_PK    |     1 |       |     0   (0)| 00:00:01 |
|  10 |   TABLE ACCESS BY INDEX ROWID   | DEPARTMENTS   |     1 |    16 |     1   (0)| 00:00:01 |
Predicate Information (identified by operation id):
   6 - access("E"."JOB_ID"="J"."JOB_ID")
       filter("E"."JOB_ID"="J"."JOB_ID")
   8 - access("E"."EMPLOYEE_ID"<103)
   9 - access("E"."DEPARTMENT_ID"="D"."DEPARTMENT_ID")