IOUG Collaborate 2014 ASH/AWR Deep Dive

Deep Dive to ASH and AWR
with EM12c
Kellyn Pot‟Vin
Consulting Member of Technical Team
Strategic Customer Program

The following is intended to outline our general product
direction. It is intended for information purposes only, and
may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality,
and should not be relied upon in making purchasing
decisions. The development, release, and timing of any
features or functionality described for Oracle‟s products
remains at the sole discretion of Oracle.

Program Agenda
 What am I asked about?
 Easiest Way to Get the Job Done
– ASH/AWR Reports in EM12c
– Compare ADDM
– Search SQL, (Least known and very valuable tool)
– Top Tricks in EM12c with ASH and AWR

Brief History
 ASH= Active Session History
 AWR= Automatic Workload Repository
 Introduced in Oracle 10g
 Evolution to statspack, requests for performance reporting
improvements.
 “Always on” approach to performance metrics with requirement of non-
locking collection process.
 Requires Management Tuning Pack License from Oracle.

 Read vs. Write
 MMON, MMNL
 In Memory vs. written to disk
ASH Architecture
Build and Buffer

 Read vs. Write
 MMON, MMNL
ASH Architecture
Build and Buffer

The Location in EM12c For Some of Today’s
Presentation…

Running ASH Report from EM
• ASH is by time, not snapshot.
• Set start date and time.
• End date and time
• Generate report

 Beginning and End Time of
Report
 How Many Samples
 Average # of Sessions
 Target information in Report
HTML Format ASH
Report Details

Top 5 Events
12

SQL Top Events
13

Top Row Source
14

Top PL/SQL Procedures
15

Top Sessions
16

Blocking Sessions
17

Parallel Processes
18

Activity Over Time
19

ASH- What have we learned?
 Solid information from samples for a time period of activity
 Shouldn‟t be used for # of occurrences, as it‟s based on samples.
 Excellent reporting on
– Percentage of activity
– SQL information
– Procedural info
– Blocking Sessions
– Activity over time.
20

How Often Do We Ask, “What Changed?”
 It ran fine last week, now it isn‟t!
 ETL loads have changed, but no one has released any new code!
 The DBA says there hasn‟t been any parameter changes to this
database, but I‟m sure there have been.
 Compare ADDM Resolution

What is Compare ADDM?
 Uses Two AWR snapshots
 Creates Report that-
– Compares SQL that is common and different.
– SGA changes
– IO/CPU bound issues
– Parameter Changes

What is in an ADDM Compare?
 Report Includes Following:
– Clear Demonstration of impact of change.
– Recommendations to address issue.
– Identifies causes behind change, (with limitations.)
– Lists Regressed SQL, too!
– Tip: If Installing to database for first time, (simple installation, nothing to
concern about, just pkg to fulfill views) you must have preferred
credentials SET of install will fail!

 Choose focus period
 Choose to compare to an
Offset, Baseline or Custom
Executing a Report from EM12c
Comparison

 Familiar interface with visual wait event
comparisons.
 Average # of sessions during each period
are displayed.
Main Screen of Comparison
2-3PM, 12th Vs. 13th

Detail Report
 High level data, highlight for analysis and recommendations.

Regression SQL
 Any performance degradation is noted with the down arrow icon:

Top Segments Causing IO Waits
 High Level data
 Click on “Show Hot Object Breakdown” to see more detail.

Resource Comparisons
 Comparisons of Memory, CPU, IO and Interconnect.
 Memory Is there Virtual paging?
 Memory Base Period
 Memory Comparison Period

Dashboard Provided for CPU, Memory, IO and
Interconnect
 Is something OTHER than Oracle the cause?

IO Bound Dashboard
 Base vs. comparison period
 Temp reads/writes specified
 Single block read latency

SQL Monitor, EM12c Style
 One More way to identify performance issues.
 Monitoring view ease for those less familiar with database
performance.

SQL Monitor Dashboard
Status of Statement
Wait EventsDegree of
Parallelism
SQL_ID
SQL Text

Exadata and Offloading
 Drill down to specific statement within SQL Monitor will display offload
efficiency per statement.

Full Detail of SQL Execution

View Report

SQL Monitor Report CLI
SET LONG 1000000
SET LONGCHUNKSIZE 1000000
SET LINESIZE 1000
SET PAGESIZE 0
SET TRIM ON
SET TRIMSPOOL ON
SET ECHO OFF
SET FEEDBACK OFF
SELECT DBMS_SQLTUNE.report_sql_monitor(
sql_id => '5vh6y3b7tnv8r',
type => 'TEXT',
report_level => 'ALL') AS report
FROM dual;

Text Output of SQL Monitor

One of the Best & Least Used Features in EM
Search SQL
Problem Query

 Available since OEM 10g
 Strong, but simple feature to
assist the DBA
 4v2tsp8dz0nhn is our SQL_ID
 Go to the EM
Console, (Example is EM12c)
We Have the SQL_ID, What’s Next?
Search SQL

Search SQL Interface
 Choose AWR Snapshots, (change Time Period), AWR Baselines and
put SQL_ID

Click on Search
 SQL_ID link for SQL Details
 Split up by tabs for Cursor, AWR, Baselines and SQL Tuning Sets
 Plan Hash Value
 Elapsed Time

AWR Data

Snapshot IDs
 Click on Snapshot ID and gather valuable data on resource usage
during snapshot time or choose to view report.

AWR Report or Run ADDM Report

Running Reports, Command Line
$ORACLE_HOME/rdbms/admin/awrrpt.sql;
$ORACLE_HOME/rdbms/admin/ashrpt.sql;
$ORACLE_HOME/rdbms/admin/awrsqrpt.sql;

Running Reports, Command Line
$ORACLE_HOME/rdbms/admin/awrrpt.sql;
$ORACLE_HOME/rdbms/admin/ashrpt.sql;
$ORACLE_HOME/rdbms/admin/awrsqrpt.sql;
Less Known AWR Reports:
awrinfo.sql General AWR Info
awrddrpt.sql Comparison report between snapshots
awrblmig.sql Migrates pre-11g baseline data into 11g Baseline tables.
awrgrpt.sql RAC Aware AWR Report.

AWR Info Report
 Snapshot Interval Information
 Basic Info on Instances and Nodes
 No User or Application Schema info.
 Space Usage by SYSAUX
 WRH$ and Non- AWR Objects, ordered by size
 Snapshot info and if any errors.
 Advisor Tasks

AWR Info Report

ASH Info Report

SQL_ID Specific AWR Report

“Interesting Part”

Finale!
Select * from table(dbms_xplan.display_awr(„43mp3mjufgnkg‟));

Querying ASH Data Directly
 More defined reporting
 No need to pull full report
 Detail on waits that are of interest
 Join to non-AWR objects
 Simple queries presented…

V$ACTIVE_SESSION_HISTORY
 SAMPLE_ID- This is a unique identifier within an ASH sample.
 SAMPLE_TIME- A unit of time used by Active Session History
 USER_ID- Identifier for a user that‟s executing the session.
 SESSION_ID- Same as the SID or Session ID and can be used to join to SID in other views/tables.
 SESSION_STATE- What was the state of the session when ASH recorded the sample.
 ON CPU/WAITING- The two session states in Active Session History. ON CPU is active, vs.
Waiting, which is self-explanatory.
 EVENT- Type of event that the session is currently active or waiting on.
 TIME_WAITED- How long the session has been waiting if waiting.
 WAIT_TIME- Confusing- but this is populated by any wait time if the session is currently active for the
previous waits.
 SQL_ID- The unique identifier for the SQL statement being executed.
 SQL_CHILD_NUMBER-The cursor child number.

Session Averages
select
ROUND(RATIO_TO_REPORT(SUM(1)) OVER () * 100 ,2) PERCENTAGE,
ash.session_type SESS_TYPE,
session_state STATUS,
decode(nvl(sql_id,'-1'),'-1','nonsql','sql') SQL_TYPE,
count(distinct to_char(session_id)|| to_char(session_serial#)) SESS_CNT
from v$active_session_history ash
where
sample_time > sysdate - 30/(24*60)
and (
( ash.session_state = 'ON CPU' )
or
( ash.session_type != 'BACKGROUND' )
)
group by
ash.session_type,
ash.session_state, decode(nvl(sql_id,'-1'),'-1','nonsql','sql')
order by count(*)
/

Session Avg. Output
 Note the % of Background processes

Inspecting What
col type for a20
select * from (select
ash.SQL_ID , ash.SQL_PLAN_HASH_VALUE Plan_hash, aud.name type,
sum(decode(ash.session_state,'ON CPU',1,0)) "CPU",
sum(decode(ash.session_state,'WAITING',1,0)) "WAITING",
sum(decode(ash.session_state,'WAITING', decode(wait_class, 'User I/O',1,0),0)) "IO WAIT" ,
sum(decode(ash.session_state,'WAITING', decode(wait_class, 'User I/O',1,0),0)) "IO" ,
sum(decode(ash.session_state,'WAITING', decode(wait_class, 'Concurrency',1,0))) "CONCURRENCY" ,
sum(decode(ash.session_state,'WAITING', decode(wait_class, 'Application',1,0))) "Application" ,
sum(decode(ash.session_state,'ON CPU',1,1)) "TOTAL"
from v$active_session_history ash,
audit_actions aud
where SQL_ID is not NULL
and ash.sql_opcode=aud.action
and ash.sample_time > sysdate - &minutes /( 60*24)
group by sql_id, SQL_PLAN_HASH_VALUE , aud.name
order by sum(decode(session_state,'ON CPU',1,1)) desc
) where rownum < 5;

12 Min. View of Waits by SQL_ID
 Choose Time in Minutes To Review, (10 in our example)
 SQL_ID and Plan Hash Value Shown
 Waits for CPU, Wait, IO Wait and others.

Quantity of Events Occurred Over Small Amounts of
Time
Col event for a50
select event, count(1)
from v$active_session_history
where sample_time between
to_date('21-FEB-14 01.43.00 PM','dd-MON-yy hh:mi:ss PM')
and
to_date('21-FEB-15 01.53.00 PM','dd-MON-yy hh:mi:ss PM')
group by event
order by event;

Results, Where to Focus?

Transaction Wait Detail
select
to_char(sample_time,'HH:MI') st,
substr(event,0,20) event,
ash.session_id sid,
mod(ash.p1,16) lm,
ash.p2,
ash.p3,
nvl(o.object_name,ash.current_obj#) objn,
substr(o.object_type,0,10) otype,
CURRENT_FILE# fn,
CURRENT_BLOCK# blockn,
ash.SQL_ID,
BLOCKING_SESSION bsid
from v$active_session_history ash,
all_objects o
where event like 'enq: TX%'
and o.object_id (+)= ash.CURRENT_OBJ#
and sample_time > sysdate - 10/(60*24)
Order by sample_time

Transaction Lock Output
 What TX row locks are occurring!

Knowing What’s in the ASH Buffer
• Deters from making assumptions on what data is being
queried.
• Know your samples!

Wait Events Across Nodes

Query top 10
SQL_ID‟s in the
last 10 minutes?

SQL_ID and CPU Usage

IO Waits by Object from ASH

SQL Text with ASH
• SQL for most recent five minutes of sample data from ASH

SQL Results
• SQL_ID, SQL Text, Sample Time that Process was captured
in.

Average Activity- Graphed

select
to_char(to_date(tday||' '||tmod*&v_secs,'YYMMDD SSSSS'),'DD-MON HH24:MI:SS') tm,
samples npts,total/&samples aas,
substr(substr(substr(rpad('+',round((cpu*&v_bars)/&samples),'+') ||
rpad('-',round((waits*&v_bars)/&samples),'-') ||
rpad(' ',p.value * &v_bars,' '),0,(p.value * &v_bars)) ||
p.value || substr(rpad('+',round((cpu*&v_bars)/&samples),'+') ||
rpad('-',round((waits*&v_bars)/&samples),'-') ||
rpad(' ',p.value * &v_bars,' '),(p.value * &v_bars),10) ,0,30)
,0,&v_graph)graph,total,cpu, waits
from (
select to_char(sample_time,'YYMMDD')tday
, trunc(to_char(sample_time,'SSSSS')/&v_secs) tmod
, sum(decode(session_state,'ON CPU',1,decode(session_type,'BACKGROUND',0,1))) total
, (max(sample_id) - min(sample_id) + 1 ) samples
, sum(decode(session_state,'ON CPU' ,1,0)) cpu
, sum(decode(session_type,'BACKGROUND',0,decode(session_state,'WAITING',1,0))) waits
/* for waits I want to subtract out the BACKGROUND
but for CPU I want to count everyon */
from v$active_session_history
where sample_time > sysdate - &v_hours/24
group by trunc(to_char(sample_time,'SSSSS')/&v_secs),
to_char(sample_time,'YYMMDD')

Query Cont.
union all
select to_char(sample_time,'YYMMDD')tday
, trunc(to_char(sample_time,'SSSSS')/&v_secs) tmod
, sum(decode(session_state,'ON CPU',10,decode(session_type,'BACKGROUND',0,10))) total
, (max(sample_id) - min(sample_id) + 1 ) samples
, sum(decode(session_state,'ON CPU' ,10,0)) cpu
, sum(decode(session_type,'BACKGROUND',0,decode(session_state,'WAITING',10,0))) waits
/* for waits I want to subtract out the BACKGROUND
but for CPU I want to count everyon */
from dba_hist_active_sess_history
where sample_time > sysdate - &v_hours/24
and sample_time < (select min(sample_time) from v$active_session_history)
group by trunc(to_char(sample_time,'SSSSS')/&v_secs),
to_char(sample_time,'YYMMDD')) ash, v$parameter p
where p.name='cpu_count'
order by to_date(tday||' '||tmod*&v_secs,'YYMMDD SSSSS')
/
73

Pivot the Wait Events

Digging into History
 DBA_HIST_ACTIVE_SESS_HISTORY
– SNAP_ID
– SAMPLE_ID
– SAMPLE_TIME
– SESSION_ID
– USER_ID
– SQL_ID
– WAIT_CLASS
– SESSION_STATE
– PGA_ALLOCATED

Process Information
SELECT * FROM (
SELECT /*+ PARALLEL */
count(*) AS count,
user_id, program, module, sql_id
FROM SYS.DBA_HIST_ACTIVE_SESS_HISTORY
WHERE sample_time > TO_DATE('19-FEB-2014 03.00.00 PM','dd-MON-yy hh:mi:ss PM')
AND sample_time < TO_DATE('19-FEB-2014 08.00.00 PM','dd-MON-yy hh:mi:ss PM')
AND program LIKE 'oracle@%'
GROUP BY user_id, program, module, machine, sql_id
ORDER BY count(*) desc
)
WHERE rownum <= 20
/

Results of Process History

Tyler Muth ASH Mining Query

ASH Mining Output
Additional Options:
• Physical Read Averages
• Physical Writes, (Max/Averages)
• Redo Info
• Logon Info
• Hard Parsing, etc.

Best Practice When Querying ASH Data
 Keep it Simple and don‟t reinvent the wheel.
 Samples are an alias for time, not for counts.
 Understand what is valuable and compare to packaged reports.
 Be aware on RAC of node specific data.
 Take care when querying Obj#, File# and Block#, (still issues in
different versions…)
 Check the time that is available in buffer, don‟t assume!

AWR/ASH Links/Blogs
 Tyler Muth: http://tylermuth.wordpress.com/
 Kyle Hailey, John Beresniewicz, Graham Wood:
http://ashmasters.com/
 Mine- “For the Love of ASH and AWR”
http://dbakevlar.com/2011/02/for-the-love-of-awr-and-ash/
 Oracle- http://www.oracle.com/technetwork/oem/db-mgmt/db-mgmt-
093445.html

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IOUG Collaborate 2014 ASH/AWR Deep Dive

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