Олег Коротков [email protected] awr, ash - use cases and 11.2 enhancements

Олег Коротков[email protected]

AWR, ASH - use cases and 11.2 enhancements


Agenda

- Automatic Workload Repository (AWR) - Basic ideas - dba_hist% views - 11.2 enhancements - AWR use cases & limitations

- Active Session History (ASH) - Basic ideas - 11.2 enhancements - Typical use cases


Automatic Workload Repository

Oracle Database performance diagnostics tools evolution:- UTLBSTAT/UTLESTAT - STATSPACK (starting from Oracle 8i)- AWR (starting from Oracle 10g)

But the idea is the same…



Oracle has a lot of operational statistics/metrics gathered since the instance startup.


Automatic Workload RepositorySQL> select inst_id, name, value from gv$sysstatwhere name in ('physical reads','session logical reads','user commits','user rollbacks')order by name, inst_id;

INST_ID NAME VALUE---------- ---------------------- ---------- 1 physical reads 219525005 2 physical reads 905189162 1 session logical reads 5925054313 2 session logical reads 1.7457E+10 1 user commits 5294595 2 user commits 28113236 1 user rollbacks 8455066 2 user rollbacks 150792358

-- All stattistics:select * from v$statname;10.2.0.4 = 387; 10.2.0.5 = 39511.2.0.2 = 628


Automatic Workload ReportsSQL> select inst_id, event, total_waits, time_waited, average_wait, sum(time_waited_micro) over (partition by event) twm_totalfrom gv$system_eventwhere wait_class='User I/O'order by twm_total desc, event, inst_id;

INST_ID EVENT TOTAL_WAITS TIME_WAITED AVERAGE_WAIT TWM_TOTAL---------- ------------------------- ----------- ----------- ------------ ---------- 1 db file sequential read 27577537 40274551 1.46 3.8091E+12 2 db file sequential read 159856155 340633564 2.13 3.8091E+12 1 direct path read temp 44837941 8919281 .2 2.9431E+11 2 direct path read temp 122808964 20511343 .17 2.9431E+11 1 direct path read 1435296 1511142 1.05 9.9823E+10 2 direct path read 12075539 8471152 .7 9.9823E+10

-- All events:select count(*) from v$event_name;10.2.0.4 = 889; 10.2.0.5 = 91611.2.0.2 = 1142


Automatic Workload RepositorySQL> select sql_id, execs, rw, LIOs, PhIOs from ( 2 select sql_id, /*sql_text,*/ sum(executions) execs, 3 sum(rows_processed) rw, sum(buffer_gets) LIOs, sum(disk_reads) PhIOs 4 from gv$sql 5 where module='SQL Developer' and rownum>=1 6 group by sql_id/*, sql_text*/ 7 order by PhIOs desc) 8 where rownum<=5;

SQL_ID EXECS RW LIOS PHIOS------------- ---------- ---------- ---------- ----------3w1fk8r93360m 1 1 8156 348davt444np8yr7 6 6 3583 2897b775q3tc69a9 22 22 2899 21358kz178ugwm87 29 29 2982 96ayaq4d3bbt7k8 1 3 106 88



AWR just makes a copy of system views with scheduled time interval…

… and gives a possibility to make a report (diff) based on two snapshots.

gv$sysstat

gv$system_event

…

gv$sql

Snap at 8 A

M;

done by MM

ON

gv$sysstat

gv$system_event

…

gv$sql

Snap at 9 A

MDB activity

[8AM, 9AM]



AWR configuration.

- Oracle Diagnostic Pack is required (Oracle EE additional option).

- STATISTICS_LEVEL = TYPICAL or ALL

- (11g) CONTROL_MANAGEMENT_PACK_ACCESS = DIAGNOSTIC or DIAGNOSTIC+TUNING



AWR configuration.

SQL> select * from dba_hist_wr_control;

DBID SNAP_INTERVAL RETENTION TOPNSQL---------- ------------------ ------------------ ----------1486911308 +00000 01:00:00.0 +00007 00:00:00.0 DEFAULT

To change:dbms_workload_repository.modify_snapshot_settings( retention=>129600, -- New retention time (in minutes). 60*24*90=129600 interval=>30, -- New interval setting between each snapshot, in units of minutes topnsql=>50 – Number 30..50000; 'DEFAULT', 'MAXIMUM')



Create (additional) snapshot:dbms_workload_repository.create_snapshot('ALL') -- flush_level = 'TYPICAL' or 'ALL‘

SQL> select dbms_workload_repository.create_snapshot from dual;CREATE_SNAPSHOT--------------- 7762

SQL> select dbms_workload_repository.create_snapshot('ALL') from dual;DBMS_WORKLOAD_REPOSITORY.CREATE_SNAPSHOT('ALL')----------------------------------------------- 7763

SQL> select snap_id, count(*) from dba_hist_sqlstat where snap_id in (7762,7763) group by snap_id; SNAP_ID COUNT(*)---------- ---------- 7763 103 7762 59



Generate report across two snapshots:select * from table( dbms_workload_repository.awr_report_text( 2334238573, -- DBID 1, -- instance number 38392, -- ‘Begin Snapshot’ ID 38393, -- ‘End Snapshot’ ID 0) -- flag = 0 or 8 (display ADDM specific parts) );

-- ADDM sections: Buffer Cache Advisory (for ADDM); SGA Target Advisory (for ADDM); Shared Pool Advisory (for ADDM); Streams Pool Advisory (for ADDM); PGA Target Advisory (for ADDM)

There is a similar awr_report_html() function.



AWR report (fragments) 1/8:WORKLOAD REPOSITORY report for

DB Name DB Id Instance Inst Num Startup Time Release RAC------------ ----------- ------------ -------- --------------- ----------- ---XXXXX 207063651 ###### 1 09-Oct-11 20:43 11.2.0.2.0 YES

Host Name Platform CPUs Cores Sockets Memory(GB)---------------- -------------------------------- ---- ----- ------- ----------###### Linux x86 64-bit 8 8 4 31.38

Snap Id Snap Time Sessions Curs/Sess --------- ------------------- -------- ---------Begin Snap: 46095 03-Feb-12 08:00:02 248 5.0 End Snap: 46096 03-Feb-12 09:00:12 249 5.0 Elapsed: 60.17 (mins) DB Time: 183.68 (mins)

11.2 new data/format


Automatic Workload ReportsAWR reports 2/8:Load Profile Per Second Per Transaction Per Exec Per Call~~~~~~~~~~~~ --------------- --------------- ---------- ---------- DB Time(s): 3.1 0.4 0.05 0.02 DB CPU(s): 1.1 0.1 0.02 0.01 Redo size: 167,379.4 20,585.9 Logical reads: 70,689.2 8,694.0 Block changes: 769.8 94.7 Physical reads: 3,480.6 428.1 Physical writes: 126.5 15.6 User calls: 138.9 17.1 Parses: 46.4 5.7 Hard parses: 0.1 0.0W/A MB processed: 4.9 0.6 Logons: 0.1 0.0 Executes: 63.2 7.8 Rollbacks: 0.3 0.0 Transactions: 8.1


Automatic Workload RepositoryAWR report 3/8:Top 5 Timed Foreground Events~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Avg wait % DB Event Waits Time(s) (ms) time Wait Class------------------------------ ------------ ----------- ------ ------ ----------db file sequential read 618,214 4,667 8 42.3 User I/O DB CPU 4,085 37.1 direct path read temp 810,891 1,726 2 15.7 User I/O enq: TX - row lock contention 693 208 300 1.9 Applicatiolog file sync 29,137 104 4 .9 Commit Host CPU (CPUs: 8 Cores: 8 Sockets: 4)~~~~~~~~ Load Average Begin End %User %System %WIO %Idle --------- --------- --------- --------- --------- --------- 4.45 4.17 27.9 1.1 14.1 70.7Instance CPU~~~~~~~~~~~~ % of total CPU for Instance: 15.0 % of busy CPU for Instance: 51.3


Automatic Workload ReportsAWR reports 4/8:Wait Event Histogram DB/Inst: ######/###### Snaps: 46095-46096<…> % of Waits ----------------------------------------------- Total Event Waits <1ms <2ms <4ms <8ms <16ms <32ms <=1s >1s-------------------------- ----- ----- ----- ----- ----- ----- ----- ----- -----db file sequential read 619.1 22.0 1.8 9.4 37.0 25.0 3.5 1.5 .0<…> Waits 64ms Event to 2s <32ms <64ms <1/8s <1/4s <1/2s <1s <2s >=2s-------------------------- ----- ----- ----- ----- ----- ----- ----- ----- -----db file sequential read 9020 98.5 1.0 .3 .1 .1 .0 .0 .0<…> Waits 4s Event to 2m <2s <4s <8s <16s <32s < 1m < 2m >=2m-------------------------- ----- ----- ----- ----- ----- ----- ----- ----- -----db file sequential read 1 100.0 .0


Automatic Workload RepositoryAWR report 5/8:SQL ordered by Elapsed Time DB/Inst: ######/##### Snaps: 46095-46096<…> Elapsed Elapsed Time Time (s) Executions per Exec (s) %Total %CPU %IO SQL Id ---------------- -------------- ------------- ------ ------ ------ ------------- 3,610.8 4 902.69 32.8 3.8 96.6 3c8sz91kt214tModule: JDBC Thin ClientMERGE INTO …

3,609.9 0 N/A 32.8 52.0 47.8 0q694rv7gzkzsModule: SQL*PlusSELECT count(*) FROM …


Automatic Workload RepositoryAWR report 6/8:SQL ordered by Elapsed Time

SQL ordered by CPU Time

SQL ordered by User I/O Wait Time

SQL ordered by Gets

SQL ordered by Reads

SQL ordered by Physical Reads (UnOptimized)-> UnOptimized Read Reqs = Physical Read Reqts - Optimized Read Reqs

SQL ordered by Executions

SQL ordered by Parse Calls

SQL ordered by Sharable Memory

SQL ordered by Version Count

SQL ordered by Cluster Wait Time


Automatic Workload RepositoryAWR report 7/8:IOStat by Function summary DB/Inst: #####/##### Snaps: 46095-46096 Reads: Reqs Data Writes: Reqs Data Waits: Avg Function Name Data per sec per sec Data per sec per sec Count Tm(ms)--------------- ------- ------- ------- ------- ------- ------- ------- -------Direct Reads 45.5G 228.3 12.9145 0M 0.0 0M 0 N/ABuffer Cache Re 2.4G 171.7 .681144 0M 0.0 0M 619.1K 7.1DBWR 0M 0.0 0M 1.7G 71.4 .493891 0 N/A<…>TOTAL: 48.9G 409.7 13.8572 2.8G 89.3 .800808 716.7K 6.3

IOStat by Filetype summary DB/Inst: #####/##### Snaps: 46095-46096 Reads: Reqs Data Writes: Reqs Data Small LargeFiletype Name Data per sec per sec Data per sec per sec Read Read--------------- ------- ------- ------- ------- ------- ------- ------- -------Temp File 39.6G 224.9 11.2232 0M 0.0 0M 1.6 N/AData File 8.4G 175.2 2.37223 1.7G 71.4 .493060 7.1 29.1<…>TOTAL: 48.9G 409.7 13.8569 2.8G 89.3 .799977 3.9 31.7

IOStat by Function/Filetype summary


Automatic Workload RepositoryAWR report 8/8:Segments by Physical Reads

Segments by Physical Read Requests

Segments by UnOptimized Reads

Segments by Optimized Reads

Segments by Direct Physical Reads

Segments by Physical Writes

Segments by Physical Write Requests

Segments by Direct Physical Writes

Segments by Table Scans

Segments by DB Blocks Changes

+ enhanced RAC (interconnect, DRM) statistics


Automatic Workload RepositoryOther AWR reports/procedures:

Dbms_workload_repository package:ASH_report_text (ASH_report_html)ASH_global_report_textAWR_diff_report_textAWR_global_diff_report_textAWR_global_report_textAWR_SQL_report_text

Dbms_xplan.display_awr


Automatic Workload RepositoryAWR baselines.

Baseline is a pair of snapshots…

Oracle10g: fixed baselines only:DBMS_WORKLOAD_REPOSITORY.CREATE_BASELINE( start_snap_id, end_snap_id, baseline_name...);

Oracle 11g: baseline templates for fixed date or for repeated timeframe.


Automatic Workload RepositoryAWR tables and views.

AWR data is stored in SYS schema in SYSAUX tablespace.

Looks like there are WRH$% and WRM$% tables.

DBA_HIST% views are created above the tables.10.2.0.4 – 78 views; 11.2.0.2 – 111 views



select <...> from dba_hist_snapshot, dba_hist_sys_time_model <...>

Date min_snap_id max_id DB time DB CPU31.01.2012 121851 121955 3582,46 1899,3130.01.2012 121747 121850 3942,73 1787,5829.01.2012 121643 121746 3225,62 1587,8328.01.2012 121538 121642 2626,14 1410,2227.01.2012 121435 121537 -705799,94 -284112,9226.01.2012 121329 121434 3524,76 1934,4425.01.2012 121226 121328 3935,66 2004,01



select <...> from dba_hist_snapshot, dba_hist_system_event <...>

Event_name waits_1 duration_1 waits_2 duration_2gc buffer busy 1378135 1,9 16189 0,4gc cr grant 2-way 5830652 0,2 97805 0,2gc current block 2-way 2783997 0,3 365330 0,3gc cr multi block request 1339350 0,2 1850738 0,2gc cr block 2-way 39967 0,3 948740 0,3gc current grant busy 298901 0,7 20273 0,3gc current grant 2-way 1027710 0,2 1164 0,3


Automatic Workload RepositoryExample 1. Average and Skew.

So four executions took 278 seconds (69,5*4). How long did each take?69,5 in average.



select <...> from dba_hist_snapshot, dba_hist_sqlstat <...>

SNAP_ID EXECS ELA GETS READS IOWAIT PLAN_HASH_VALUE---------- ---------- ---------- ---------- ---------- ---------- --------------- 4918 1 178966 45213 0 0 4196013364 4876 1 1145258 151525 34 599518 4196013364 4854 1 1775405 114964 127 1277256 4196013364 4770 1 274975901 3775568 21750 260995652 4196013364

69,5 in average.But no any execution even close to this time.


Automatic Workload RepositoryExample 2. TOPNSQL.A query is the same (9g7dr4k9qj1r1). Usage pattern is the same.“Heavy” executions:DD EXECS ELA_PER_EXEC GETS_PER_EXEC-------------------- ---------- ------------ -------------28.12.2011 14 1053 379809 2116128.12.2011 13 12336 9043237 2114828.12.2011 12 942 379609 2129628.12.2011 11 1097 378855 2106028.12.2011 10 1505 382856 2116828.12.2011 09 6102 7229608 21604

“Light” executions:-------------------- ---------- ------------ -------------29.12.2011 14 5860 2003 8929.12.2011 13 6723 2016 9129.12.2011 10 6435 2008 86

There were no executions in some snaps.

ADD_COLORED_SQL/REMOVE_COLORED_SQL to mark sql_id.



A kind of conclusion about AWR.

- It’s very useful tool for analyzing performance in past periods.- Oracle11g AWR is better (more comprehensive and more convenient) than 10g.- Selecting from AWR views gives even more powerful and flexible reports.

But…AWR requires addition licensing.It gives you only aggregated information.Some data can be ‘omitted’.


Agenda

- Automatic Workload Repository (AWR) - Basic ideas - dba_hist% views - 11.2 enhancements - AWR use cases & limitations

- Active Session History (ASH) - Basic ideas - 11.2 enhancements - Typical use cases


Active Session History

Active Session History (ASH) is a new tool introduced in Oracle10g.

Once a second it makes snapshot of active sessions (on CPU or in non-Idle events).Something close to…select ... from gv$sessionwhere wait_class<>'Idle';

ASH data is not complete but.. It is not aggregated (like other AWR data).



dba_hist_active_sess_history10.2.0.5 – 52 columns; 11.2.0.2 – 97 columns.

Some of the columns:SNAP_ID, DBID, INSTANCE_NUMBER, SAMPLE_ID, SAMPLE_TIME – sample identification;

SESSION_ID, SESSION_SERIAL#, USER_ID, PROGRAM, MODULE, MACHINE, PORT – session identification;

SQL_ID, SQL_PLAN_HASH_VALUE, SQL_PLAN_LINE_ID, SQL_EXEC_ID – SQL information;

EVENT, P1, P2, P3, TIME_WAITED – wait event information;

BLOCKING_SESSION, BLOCKING_SESSION_SERIAL#, BLOCKING_INST_ID – locking information;

TM_DELTA_CPU_TIME, TM_DELTA_DB_TIME, DELTA_READ_IO_REQUESTS. DELTA_WRITE_IO_REQUESTS, DELTA_READ_IO_BYTES, DELTA_WRITE_IO_BYTES,

DELTA_INTERCONNECT_IO_BYTES – session activity info.


Agenda

ASH architecture (John Beresniewicz. Practical Active Session History)

Circular bufferin SGA

(2MB per CPU)

Session state

objects

V$SESSIONV$SESSION_WAI

T

MMON Lite(MMNL)

V$ACTIVE_SESSION_HISTORY

DBA_HIST_ACTIVE_SESS_HISTORY

AWR

Direct-path

INSERTS

Every hour

Write 1 out of 10

samples

Every second

(or flush)

Indexed

on time

Readers go

unlatched

Writer goesone

direction

Readers go the

opposite way



ASH in memory – fixed memory consumption, variable time range. SQL> select inst_id, bytes/(1024*1024) MB from gv$sgastat where name='ASH buffers'; INST_ID MB---------- ---------- 1 16 3 16 2 16

SQL> select inst_id, (max(sample_time)-min(sample_time)) ASH_windowfrom gv$active_session_history group by inst_id;INST_ID ASH_WINDOW---------- ------------------------------- 1 +000000000 07:18:12.038 2 +000000000 07:01:26.268 3 +000000000 10:15:25.558

Samples for every second.



ASH on disk – fixed time range controlled by AWR retention. SQL> select instance_number, (max(sample_time)-min(sample_time)) ASH_windowfrom dba_hist_active_sess_history group by instance_number;INSTANCE_NUMBER ASH_WINDOW--------------- ---------------------------------- 1 +000000032 04:59:50.479 2 +000000032 04:59:45.743 3 +000000032 04:59:40.818

SQL> select 'ASH in memory' what, count(distinct sample_id) samples_per_hour 2 from v$active_session_history 3 where sample_time>=trunc(sysdate) and sample_time<trunc(sysdate)+1/24 4 union all 5 select 'ASH on disk', count(distinct sample_id) sample_id 6 from dba_hist_active_sess_history 7 where instance_number=1 and sample_time>=trunc(sysdate) and sample_time<trunc(sysdate)+1/24;WHAT SAMPLES_PER_HOUR------------- ----------------ASH in memory 3592ASH on disk 359

1/10 of samples from ‘ASH in memory’.



Each sample in ASH data represents a second of database activity.

Theoretically:- Count of rows for one sample is DB Time.- Count of rows with session_state=‘ON CPU’ is DB CPU.

In my experience the accuracy of the calculation hardly ever better than 15-20% on production systems with significant load.



Example 1. AWR report: Snap Id Snap Time Sessions Curs/Sess --------- ------------------- -------- ---------Begin Snap: 118264 27-Dec-11 13:30:23 1,410 49.8 Elapsed: 15.06 (mins) DB Time: 2,438.18 (mins)<…>Event Waits Time (s) (ms) Time Wait Class------------------------------ ------------ ----------- ------ ------ ----------latch: cache buffers chains 409,488 51,930 127 35.5 ConcurrencCPU time 6,341 4.3 db file sequential read 164,900 1,113 7 0.8 User I/O<…> Elapsed CPU Elap per % Total Time (s) Time (s) Executions Exec (s) DB Time SQL Id ---------- ---------- ------------ ---------- ------- ------------- 139,282 4,307 11,574 12.0 95.2 9g7dr4k9qj1r1

140 000 (ela for the query) / 900 (15 minutes) == 155 concurrently executed queries.



Example 1. ASH content (1/3):SQL> select to_char(trunc(sample_time,'mi'),'hh24:mi') dd, count(*) c, 2 count(distinct h.session_id||':'||h.session_serial#) s 3 from dba_hist_active_sess_history h 4 where h.instance_number=1 and h.snap_id between 118265 and 118265 5 and h.sample_time>=to_date('27.12.2011 13:30','dd.mm.yyyy hh24:mi') 6 and h.sample_time <to_date('27.12.2011 13:45','dd.mm.yyyy hh24:mi') 7 group by trunc(sample_time,'mi') order by trunc(sample_time,'mi');DD C S--------------- ---------- ----------13:30 33 2413:31 3134 104413:32 4846 91413:33 55 4813:34 37 2413:35 28 1713:36 25 1713:37 239 23013:38 5242 101613:39 1188 87313:40 28 2613:41 19 19<…>



Example 1. ASH content (2/3):SQL> select sample_time, count(*) c, 2 sum(case when sql_id='9g7dr4k9qj1r1' then 1 else 0 end) s 3 from dba_hist_active_sess_history h 4 where h.instance_number=1 and h.snap_id between 118265 and 118265 5 and h.sample_time>=to_date('27.12.2011 13:30','dd.mm.yyyy hh24:mi') 6 and h.sample_time <to_date('27.12.2011 13:45','dd.mm.yyyy hh24:mi') 7 group by sample_time order by sample_time;

…



Example 1. ASH content (3/3):SAMPLE_TIME C S------------------------------ ---------- ----------27-DEC-11 01.30.05.551 PM 6 027-DEC-11 01.30.15.591 PM 5 0<…>27-DEC-11 01.31.15.850 PM 4 027-DEC-11 01.31.25.959 PM 410 39527-DEC-11 01.31.36.069 PM 980 96327-DEC-11 01.31.46.652 PM 887 85727-DEC-11 01.31.56.951 PM 848 82227-DEC-11 01.32.06.994 PM 862 84427-DEC-11 01.32.17.056 PM 852 83127-DEC-11 01.32.27.118 PM 869 84227-DEC-11 01.32.37.165 PM 855 84027-DEC-11 01.32.47.225 PM 800 77627-DEC-11 01.32.57.516 PM 608 57027-DEC-11 01.33.07.566 PM 25 1027-DEC-11 01.33.17.613 PM 8 127-DEC-11 01.33.27.658 PM 5 127-DEC-11 01.33.37.690 PM 4 0<…>



Example 2. sql_exec_id (Oracle 11g) (1/2).SQL_EXEC_ID is counter of SQL executions on a given instance.(See Tanel Poder blog entry.)

SQL> declare j number;begin dbms_job.submit(job=>j, what=>'declare p number; begin for i in 1..3 loop select count(*) into p from positions e_test where mrp=1; end loop; end;', instance=>1);end;/PL/SQL procedure successfully completed.

SQL> declare j number;begin dbms_job.submit(job=>j, what=>'declare p number; begin for i in 1..2 loop select count(*) into p from positions e_test where mrp=1; end loop; end;', instance=>2);end;/



Example 2. sql_exec_id (Oracle 11g) (2/2).

SQL> select sql_id, sql_text from v$sql where sql_id='2dxypmkd8p3qk';-------------2dxypmkd8p3qkSELECT COUNT(*) FROM POSITIONS E_TEST WHERE MRP=1

SQL> select inst_id, sql_exec_id, to_char(sql_exec_id,'XXXXXXXX') sql_exec_id_h, count(*) sfrom gv$active_session_historywhere sql_id='2dxypmkd8p3qk'group by inst_id, sql_exec_idorder by 1,2;

INST_ID SQL_EXEC_ID SQL_EXEC_ S---------- ----------- --------- ---------- 1 16777216 1000000 4 1 16777217 1000001 4 1 16777218 1000002 5 2 33554432 2000000 5 2 33554433 2000001 4



ASH is great tool for:- Investigate load spikes within an AWR snapshot.- Analyze ‘long’ queries executions (especially in 11g).- Investigate locking/blocking issues (if locking time not too short).

Limitations:- The information is not complete. ASH on disk is more incomplete. - DB activity spikes makes ‘retention window’ of ASH in memory shorter (sometimes dramatically).- Tends to sample ‘long’ events. - Licensing as part of AWR.


ReferencesOracle® Database Documentation, 11g Release 2 (11.2)Oracle® Database Performance Tuning Guide5 Automatic Performance Statisticshttp://docs.oracle.com/cd/E11882_01/server.112/e16638/autostat.htm

Oracle® Database PL/SQL Packages and Types Reference161 DBMS_WORKLOAD_REPOSITORYhttp://docs.oracle.com/cd/E11882_01/appdev.112/e25788/d_workload_repos.htm

Mike Ault. AWR Report Detailed Analysis.http://www.nyoug.org/Presentations/2008/Sep/Ault_AWR.pdf

John Beresniewicz. Practical Active Session History

Tanel Poder. What the heck is the SQL Execution ID – SQL_EXEC_ID?http://blog.tanelpoder.com/2011/10/24/what-the-heck-is-the-sql-execution-id-sql_exec_id/

http://docs.oracle.com/cd/E11882_01/server.112/e16638/autostat.htm

http://docs.oracle.com/cd/E11882_01/appdev.112/e25788/d_workload_repos.htm

http://www.nyoug.org/Presentations/2008/Sep/Ault_AWR.pdf

http://blog.tanelpoder.com/2011/10/24/what-the-heck-is-the-sql-execution-id-sql_exec_id/


Thank you for coming!

Questions?

Олег Коротков [email protected] awr, ash - use cases and 11.2 enhancements

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