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Database Oracle 10 g, many previously difficult response time indicators can be obtained immediately.

Historically, Oracle dba and performance analysts have fought an uphill battle for reliable response time metrics and user session activity in order to achieve maximum database performance. The problems that dba has always faced are twofold: first, to determine exactly where a database or user session spends their time; and second, to determine an objective and natural user experience.

These tasks are unusual considering all possible activities and interactions in the database. The Oracle wait interface shows that many versions have previously been a great startup for administrators instructing how to use it, even though it lacks the ideal ability to tell DBA systems or user sessions how to handle transactions or queries effectively. Enabling and studying trace files can get this level of detail, but this exercise is a luxury for most tiring dba to manage large database clusters.

Fortunately, those DBA who have upgraded to Oracle dba 10g will find that major response time system improvements provide a better picture display system and session-level response time indicator system. Most importantly, the Oracle Database automatic Diagnostic Monitoring system (ADDM) provides insight into response time and more information by automatically collecting statistical analysis, identifying problem domains, and even providing advice through Oracle Enterprise Manager Grid Control GUI.

In addition, what is most worth discussing here is the historical mechanism of Oracle Database 10g, which allows dba to review previous results to achieve their own response time trend analysis, which helps them determine peak and off-peak transaction / system times and locate rogue programs and SQL by extending batch cycles or ETL jobs.

In this article, I will explore some of these historical mechanisms at the system, conference, and SQL levels. For more information about ADDM, see the Oracle documentation and the "ADDM and SQL tuning Advisor" section in "Arup Nanda's" Oracle Database 10g: Top 20 Features for DBAs.

System-level response time analysis

At the global or system level, dba usually wants answers to these questions:

Overall, how is my database running? What defines efficiency?

What is the average response time of my user experience?

Which activities affect the overall response time most?

Before the Oracle 10g database, the answers to these questions were already quite elusive for DBA, but now such indicators can be easier to capture if you happen to use the latest and greatest Oracle databases.

First of all, part of the answer is: in general, the running database can be obtained in database Oracle 10g by sending the query:

Select METRIC_NAME, VALUEfrom SYS.V_$SYSMETRICwhere METRIC_NAME IN ('Database CPU Time Ratio',' Database Wait Time Ratio') AND INTSIZE_CSEC = (select max (INTSIZE_CSEC) from SYS.V_$SYSMETRIC) METRIC_NAME VALUE---Database Wait Time Ratio 6Database CPU Time Ratio 94

The Oracle Database 10g V$SYSMETRIC view contains several excellent response-time metrics, two of which are the Database Wait Time Ratio and Database CPU Time Ratio. The query above shows the latest snapshot of these two statistics, which help you determine if your database is currently experiencing a high percentage of waits/bottlenecks vs. Smoothly running operations. The Database CPU Time Ratio is calculated by dividing the amount of CPU expended in the database by the amount of "database time," which is defined as the time spent by the database on user-level calls (with instance background process activity being excluded). High values (90-95 + percent) are good and indicate few wait/bottleneck actions, but take this threshold only as a general rule of thumb because every system is different.

You can also take a quick look over the last hour to see if the database has experienced any dips in overall performance by using this query:

Select end_time, valuefrom sys.v_$sysmetric_historywhere metric_name = 'Database CPU Time Ratio'order by 1 END_TIME VALUE--22-NOV-2004 10:00:38 9822-NOV-2004 10:01:39 9622-NOV-2004 10:02:37 9922-NOV-2004 10:03:38 10022-NOV-2004 10:04:37 9922-NOV-2004 10:05 : 38 7722-NOV-2004 10:06:36 10022-NOV-2004 10:07:37 9622-NOV-2004 10:08:39 100..

And, you can get a good idea of the minimum, maximum, and average values of overall database efficiency by querying the V$SYSMETRIC_SUMMARY view with a query such as this:

Select CASE METRIC_NAME WHEN 'SQL Service Response Time' then' SQL Service Response Time (secs) 'WHEN' Response Time Per Txn' then 'Response Time Per Txn (secs)' ELSE METRIC_NAME END METRIC_NAME, CASE METRIC_NAME WHEN 'SQL Service Response Time' then ROUND ((MINVAL / 100), 2) WHEN' Response Time Per Txn' then ROUND ((MINVAL / 100) 2) ELSE MINVAL END MININUM, CASE METRIC_NAME WHEN 'SQL Service Response Time' then ROUND ((MAXVAL / 100,2) WHEN' Response Time Per Txn' then ROUND ((MAXVAL / 100,2) ELSE MAXVAL END MAXIMUM, CASE METRIC_NAME WHEN 'SQL Service Response Time' then ROUND ((AVERAGE / 100)) 2) WHEN 'Response Time Per Txn' then ROUND ((AVERAGE / 100,2) ELSE AVERAGE END AVERAGEfrom SYS.V_$SYSMETRIC_SUMMARY where METRIC_NAME in (' CPU Usage Per Sec', 'CPU Usage Per Txn',' Database CPU Time Ratio', 'Database Wait Time Ratio') 'Executions Per Sec', 'Executions Per Txn',' Response Time Per Txn', 'SQL Service Response Time' 'User Transaction Per Sec') ORDER BY 1METRIC_NAME MINIMUM MAXIMUM AVERAGE---CPU Usage Per Sec 0 7 1CPU Usage Per Txn 1 29 8Database CPU Time Ratio 61 100 94Database Wait Time Ratio 0 39 5Executions Per Sec 2 60 8Executions Per Txn 16 164 41Response Time Per Txn (secs) 0.28 .08 SQL Service Response Time (sec 0 0 0User Transaction Per Sec 0 10)

The query above contains more response-time metrics than simply the Database CPU and Wait Time Ratios (we'll cover those later), but you can see the benefit in being able to acquire this information. For this particular instance, the average Database CPU Time Ratio is 94, which is well within our acceptable limits.

The next question DBAs pose at the system level involves the average level of response time that their user community is experiencing. Prior to Oracle Database 10g this type of data was difficult to capture, but not anymore. The query shown above that interrogates the V$SYSMETRIC_SUMMARY view tells us what we need to know. If complaints of unacceptable response times are mounting from users, the DBA can check the Response Time Per Txn and SQL Service Response Time metrics to see if a database issue exists. For example, the statistics shown above report that the maximum response time per user transaction has been only. 28 second, with the average response time being a blazing. 08 second. Oracle certainly wouldn't be to blame in this case.

If, however, response times are longer than desired, the DBA will then want to know what types of user activities are responsible for making the database work so hard. Again, before Oracle Database 10g, this information was more difficult to acquire, but now the answer is only a query away:

Select case db_stat_name when 'parse time elapsed' then' soft parse time' else db_stat_name end db_stat_name Case db_stat_name when 'sql execute elapsed time' then time_secs-plsql_time when' parse time elapsed' then time_secs-hard_parse_time else time_secs end time_secs Case db_stat_name when 'sql execute elapsed time' then round (100 * (time_secs-plsql_time) / db_time,2) when' parse time elapsed' then round (100 * (time_secs-hard_parse_time) / db_time,2) else round (100 * time_secs / db_time 2) end pct_timefrom (select stat_name db_stat_name, round ((value / 1000000), 3) time_secs from sys.v_$sys_time_model where stat_name not in ('DB time','background elapsed time','background cpu time','DB CPU')), (select round ((value / 1000000)) 3) db_time from sys.v_$sys_time_model where stat_name ='DB time'), (select round ((value / 1000000), 3) plsql_time from sys.v_$sys_time_model where stat_name = 'PL/SQL execution elapsed time'), (select round ((value / 1000000), 3) hard_parse_time from sys.v_$sys_time_model where stat_name =' hard parse elapsed time') order by 2 desc DB_STAT TIME_SECS PCT_TIME---sql execute elapsed time 13263.707 45.84 PL/SQL execution elapsed time 13234.738 45.74 hard parse elapsed time 1943.687 6.72 soft parse time 520.584 1.8..

The example output above shows a database that has spent the vast majority of its time handling SQL and PL/SQL requests. Complete descriptions of all the statistics supported by the V$SYS_TIME_MODEL view can be found here.

In addition to active time, a DBA will want to know the global wait times as well. Prior to Oracle Database 10g, a DBA had to view individual wait events to understand waits and bottlenecks, but now Oracle provides a summary/rollup mechanism for waits via wait classes:

Select WAIT_CLASS, TOTAL_WAITS, round (100 * (TOTAL_WAITS / SUM_WAITS), 2) PCT_WAITS, ROUND ((TIME_WAITED / 100), 2) TIME_WAITED_SECS, round (100 * (TIME_WAITED / SUM_TIME), 2) PCT_TIMEfrom (select WAIT_CLASS, TOTAL_WAITS, TIME_WAITEDfrom V$SYSTEM_WAIT_CLASSwhere WAIT_CLASS! = 'Idle') (select sum (TOTAL_WAITS) SUM_WAITS, sum (TIME_WAITED) SUM_TIMEfrom V$SYSTEM_WAIT_CLASSwhere WAIT_CLASS! = 'Idle') order by 5 desc WAIT_CLASS TOTAL_WAITS PCT_WAITS TIME_WAITED_SECS PCT_TIME--User I WAIT_CLASS TOTAL_WAITS PCT_WAITS TIME_WAITED_SECS PCT_TIME- O 2245204 7.48 4839.43 54.39System I Universe O 2438387 8.12 2486.21 27.94Application 920385 3.07 513.56 5.77Other 39962. 13 422.36 4.75Commit 200872. 67 284.76 3.2Network 24133213 80.38 162. 26 1.82Concurrency 6867. 02 102.63 1.15Configuration 39377. 13 86.21. 97

It's much easier to tell now that the bulk of overall wait time is due, for example, to user I/O waits than to try to tally individual wait events to get a global picture. As with response-time metrics, you can also look back in time over the last hour with a query like this one:

Select to_char, b.wait_class, round ((a.time_waited / 100,2) time_waited from sys.v_$waitclassmetric_history a, sys.v_$system_wait_class bwhere a.wait_class# = b.wait_class# and b.wait_class! = 'Idle'order by 1, HH:MI:SS' 2) END_TIME WAIT_CLASS TIME_WAITED- 22-NOV-2004 11:28:37 Application 022-NOV-2004 11:28:37 Commit .0222-NOV-2004 11:28:37 Concurrency 022-NOV-2004 11:28:37 Configuration 022-NOV-2004 11:28:37 Network .0122-NOV-2004 11:28:37 Other 022-NOV-2004 11:28:37 System Other 022-NOV-2004 0.0522-NOV-2004 11:28:37 User I Charpy O.O.

You can, of course, just focus on a single SID with the V$SESS_TIME_MODEL view and obtain data for all statistical areas of a session. You can also view current session wait activity using the new wait classes using the following query:

Select a.sid, b.username, a.wait_class, a.total_waits, round ((a.time_waited / 100,2) time_waited_secsfrom sys.v_$session_wait_class a, sys.v_$session bwhere b.sid = a.sid and b.username is not null and a.wait_class! = 'Idle'order by 5 desc SID USERNAME WAIT_CLASS TOTAL_WAITS TIME_WAITED_SECS----257 SYSMAN Application 356104 75.22255 SYSMAN Commit 14508 25.76257 SYSMAN Commit 25026 22.02257 SYSMAN User I/O 11924 19.98...

After this stage, you can check the standard individual wait events as you've been able to do in earlier versions of Oracle with V$SESSION_WAIT and V$SESSION_EVENT. You'll also find the new wait classes in these two modified views with Oracle Database 10g.

If you need to look back in time to discover what sessions were logged on and consuming the most resources, you can use the following query. In the example below, we're looking at activity from midnight to 5 a.m. On November 21, 2004, that involved user I/O waits:

Select sess_id, username, program, wait_event, sess_time, round (100 * (sess_time / total_time), 2) pct_time_waitedfrom (select a.session_id sess_id, decode (session_type,'background',session_type,c.username) username, a.program program, b.name wait_event Sum (a.time_waited) sess_timefrom sys.v_$active_session_history a, sys.v_$event_name b, sys.dba_users cwhere a.event# = b.event# and a.user_id = c.user_id and sample_time > '21-NOV-04 12:00:00 AM' and sample_time

< '21-NOV-04 05:00:00 AM' and b.wait_class = 'User I/O'group by a.session_id, decode(session_type,'background',session_type,c.username), a.program, b.name),(select sum(a.time_waited) total_timefrom sys.v_$active_session_history a, sys.v_$event_name bwhere a.event# = b.event# and sample_time >

'21-NOV-04 12:00:00 AM' and sample_time <' 21-NOV-04 05:00:00 AM' and b.wait_class = 'User I amp O') order by 6 desc SESS_ID USERNAME PROGRAM WAIT_EVENT SESS_TIME PCT_TIME_WAITED--242 SYS exp@RHAT9K db file scattered read 3502978 33.49 242 SYS oracle@RHA db file sequential read 2368153 22.64 242 SYS oracle@RHA db file scattered read 1113896 10.65 243 SYS oracle@RHA db file sequential read 992168 9.49

The Oracle Database 10g V$ACTIVE_SESSION_HISTORY view comes into play here to provide an insightful look back in time at session experiences for a given time period. This view gives you a lot of excellent information without the need for laborious tracing functions. We'll see more use of it in the next section, which deals with analyzing the response times of SQL statements.

SQL Response-Time Analysis

Examining the response time of SQL statements became easier in Oracle9i, and with Oracle Database 10g, DBAs have many tools at their disposal to help them track inefficient database code.

Historically the applicable V $view here has been V$SQLAREA. Starting with Oracle9i, Oracle added the ELAPSED_TIME and CPU_TIME columns, which have been a huge help in determining the actual end user experience of a SQL statement execution (at least, when dividing them by the EXECUTIONS column, which produces the average amount of time per execution).

In Oracle Database 10g, six new wait-related and timing columns have been added to V$SQLAREA:

APPLICATION_WAIT_TIME

CONCURRENCY_WAIT_TIME

CLUSTER_WAIT_TIME

USER_IO_WAIT_TIME

PLSQL_EXEC_TIME

JAVA_EXEC_TIME

The new columns are helpful in determining, for example, the amount of time that a procedure spends in PL/SQL code vs. Standard SQL execution, and if a SQL statement has experienced any particular user I/O waits. For example, a query you could use to find the top five SQL statements with the highest user I/O waits would be:

Select * from (select sql_text, sql_id, elapsed_time, cpu_time, user_io_wait_timefrom sys.v_$sqlareaorder by 5 desc) where rownum < 6 SQL_TEXT SQL_ID ELAPSED_TIME CPU_TIME USER_IO_WAIT_TIME--select / * + rule * / bucket db78fxqxwxt7 47815369 19000939 3423SELECT: "SYS_B_0" FROM SY agdpzr94rf6v 36182205 10170226 2649select obj# Type#,ctime,m 04xtrk7uyhkn 28815527 16768040 1345select grantee#,privilege 2q93zsrvbdw4 28565755 19619114 803select / * + rule * / bucket 96g93hntrzjt 9411028 3754542 606

Of course, getting the SQL statements with the highest elapsed time or wait time is good, but you need more detail to get to the heart of the matterwhich is where the V$ACTIVE_SESSION_HISTORY view again comes into play. With this view, you can find out what actual wait events delayed the SQL statement along with the actual files, objects, and object blocks that caused the waits (where applicable).

For example, let's say you've found a particular SQL statement that appears to be extremely deficient in terms of user I/O wait time. You can issue the following query to get the individual wait events associated with the query along with the corresponding wait times, files, and objects that were the source of those waits:

Select event, time_waited, owner, object_name, current_file#, current_block# from sys.v_$active_session_history a, sys.dba_objects b where sql_id = '6gvch2xu9ca3g' and a.current_obj# = b.object_id and time_waited 0 EVENT TIME_WAITED OWNER OBJECT_NAME file block--db file sequential read 27665 SYSMAN MGMT_METRICS_1HOUR_PK 3 29438db file sequential read 3985 SYSMAN SEVERITY_PRIMARY_KEY 3 52877

Of course, you can use V$ACTIVE_SESSION_HISTORY in a historical fashion to narrow down unoptimized SQL statements for a particular time period. The point is that Oracle Database 10g makes it a lot easier to conduct response-time analysis on SQL statements with simplified data dictionary views, as opposed to the time-consuming trace-and-digest method.

Conclusion

DBAs and performance analysts who manage the performance of Oracle Database 10g will find many of the response-time metrics they've yearned for over the years now at their fingertips in the latest release of Oracle's flagship database. Such statistics will help accelerate the process of finding the proverbial needle in the haystack of large and complex database performance situations.

Oracle performance tuning: limited and infinite time

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