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RT 1 - Whe
I’m certain th
108 AWR rep
the bottleneck
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and Util
metrics
In this p
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re it all sta
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s will lead to
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Hence, capacity p
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ork you'll end up
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alize data and us
ta samples is we
ization in terms
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arrays are getting
planning plays a
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is justifying the
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oved significantl
when going thro
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se statistical met
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nning.
arn how to make
easurement on
nce Firefighting.
on’t have eno
about 108 AW
neck? Well be
nd repetitive e
hen you start r
to correlate it
ysis periods h
to optimize m
ubleshooting
Capacity
al World
Karl Arao
E, OCP-DBA
ao@gmail.co
g faster, but the
very important
nexpected worklo
expense of add
st expensive har
rowth, you'll be
particular grow
IT shop.
d in 10gR1 and
y in 11gR2, en
ugh all the AW
s that will let us
thods for analys
fine the databas
emory, and netw
e use of the AWR
resources to aid
ough time to s
WR reports in
efore it will ta
execution of a
reading each
t to the proble
hence longer
my troublesho
but what if
y Plann
d Stuff
A, RHCE
om
se resources are
role to ensure pr
oads. Another cri
ding resources on
rdware. With pro
able to get just
wth period. This
is very much lik
nabling you to
R snapshots. Fr
notice trends an
is. Even more su
se server's Capac
work, which are v
R, specifically the
d in Capacity P
spare to read
n 5 minutes ju
ake so much
awrrpt.sql. Y
of them and
em at hand.
r time for a p
ooting time. Y
you are only
ing, Vis
e finite and come
roper resources a
itical matter for t
n the system. W
oper measureme
the right hardwa
will result in hu
ke a "Statspack
have a far bet
rom the AWR d
d makes it possi
urprising about t
city, Requiremen
very important k
e DBA_HIST view
Planning, Predict
d 108 AWR re
ust to answer
of my time ju
You will be ov
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problem to be
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y left with ju
ualizatio
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are
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verwhelmed b
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ust a comma
on, and
ay, even mor
what period i
te these AWR
by the manua
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as a databas
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and line or an
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performance d
visualize the d
RT 2 - How
AWR is much
sources of the
Oracle version
The AWR rep
an AWR repo
performance p
339) within th
the workload
For the query
data blocks re
since instance
delta and tran
To transform
formula. See t
IO MB/s = ( (d
                = ((5
                = 73
To validate th
339. The imag
Also a run of
the throughpu
triggered me
data in more
data, or even p
w to mine th
h like “Statspa
e AWR repor
n 11.2.
port provides
ort for SNAP
problems we
he specified in
change that’s
y output we a
ead from disk
e start. We ar
nsforming it to
the delta to
the example f
delta * <block_size
5663126 * 8192) /
3.37 MB/s 
he accuracy o
ge below show
Automatic D
ut of 74 MB/s
e to mine on t
meaningful m
possible to do
he AWR
ack on steroid
rt are the DB
a single summ
P_ID 335 to
are more inte
nterval. In th
s happening.
are investigati
k. It is also im
re particularly
o a more mea
a more mean
for SNAP_ID
e>) /1024/1024 ) /
1024/1024) / 603 
f the derived
ws the delta w
Database Diag
that is really
the source tab
manner that w
o some statist
ds” it is a won
BA_HIST view
mary report b
339 that is a
erested to see
at way we ha
ing for the S
mportant to no
y interested o
aningful and r
ningful outpu
D 338 below:
/ <snap_duration_
value we nee
we used to der
gnostic Monit
close to our d
bles of the AW
will be easier
tics out of it.
nderful data c
ws which hav
based upon an
an interval tim
what occurre
ave a granular
YSSTAT sta
ote this is a cu
on the delta o
eadable outpu
ut that we cou
_in_seconds> 
ed to compar
rive the MB/s
tor (ADDM)
derived value
WR report to
for me to no
collector for O
ave grown fro
n interval of t
me from 6:20
ed during eac
r view of wha
atistic “physic
umulative phy
of each SNAP
ut.
uld easily un
re it with the
s is correct.
on SNAP_ID
e
cut out the u
otice trends an
Oracle and OS
om 67 in Ora
time. On the i
0 – 7:01AM.
ch of the samp
at’s going on
cal reads” wh
ysical reads b
P_ID that is
nderstand we
actual AWR
D 338 – 339 s
unnecessary an
nd even poss
S statistics. T
acle version 1
image below
However wh
ple (335,336,
n and have a b
hich is the to
by all the data
end_value –
would apply
report on SN
shows that we
nd present th
ible for me to
The underlying
10.1 to 108 in
we can creat
hen analyzing
, 337, 338 and
better view on
tal number o
abase session
start_value =
y the IO MB/
NAP_ID 338 –
e are reaching
e
o
g
n
e
g
d
n
of
s
= 
s
–
g
A
T
 
And checking
The data show
SELECT * FRO
( SELECT s0.sn
  TO_CHAR(s0
  s10t0.stat_n
  s10t0.value 
  s10t1.value 
  (s10t1.value
  round(((((s1
                        
                        
                        
    ),2) as phyr
FROM dba_h
           dba_hi
           dba_hi
           dba_hi
WHERE s0.db
AND s1.dbid  
AND s10t0.db
AND s10t1.db
AND s0.instan
AND s1.instan
AND s10t0.in
AND s10t1.in
AND s1.snap_
AND s10t0.sn
AND s10t1.sn
AND s10t0.st
AND s10t1.st
) 
WHERE snap_
ORDER BY sn
g it with the E
wn above com
OM 
nap_id snap_id, 
0.END_INTERVAL_
name, 
start_value,  
end_value, 
e ‐ s10t0.value) de
0t1.value ‐ s10t0.v
          + EXTRACT(H
          + EXTRACT(M
          + EXTRACT(S
reads_mbps 
ist_snapshot s0, 
st_snapshot s1, 
st_sysstat s10t0,   
st_sysstat s10t1 
bid              = 26079
              = s0.dbid 
bid             = s0.dbi
bid             = s0.dbi
nce_number     = 1
nce_number     = s
stance_number  =
stance_number  =
_id             = s0.sna
nap_id          = s0.sn
nap_id          = s0.sn
at_name        = 'ph
at_name        = s10
_id in (335,336,33
ap_id ASC; 
Enterprise Man
mes from quer
_TIME,'YY/MM/DD
lta, 
value)* 8192)/102
HOUR FROM s1.EN
MINUTE FROM s1
SECOND FROM s1
              ‐‐ physica
950532    ‐‐ DBID 
d 
d 
1               ‐‐ INSTAN
s0.instance_numb
= s0.instance_num
= s0.instance_num
ap_id + 1 
nap_id 
nap_id + 1 
hysical reads' 
0t0.stat_name 
7,338,339) 
nager Perform
ry below:
D HH24:MI') TIME,
24/1024)  / ((round
ND_INTERVAL_TIM
.END_INTERVAL_T
.END_INTERVAL_T
l reads, diffed 
NCE_NUMBER 
er 
mber 
mber 
mance page sh
d(EXTRACT(DAY FR
ME ‐ s0.END_INTER
TIME ‐ s0.END_INT
TIME ‐ s0.END_INT
hows that the
ROM s1.END_INTE
RVAL_TIME) * 60 
TERVAL_TIME)  
TERVAL_TIME) / 6
e Disk IO is ar
ERVAL_TIME ‐ s0.E
60, 2))*60) 
round our der
END_INTERVAL_TI
rived value
IME) * 1440  
You may have noticed that I used the SQL trick below that has similar effect to the LAG function. This enables the
query to get the start_value and end_value on a single row making it possible to get the delta value and apply the
performance formula. The view DBA_HIST_SNAPSHOT also acts as an ultimate reference of snap information that
allows joining to the other DBA_HIST views to provide meaningful data on other subsystems or workload
performance data.
AND s10t0.snap_id          = s0.snap_id 
AND s10t1.snap_id          = s0.snap_id + 1 
The query I’ve shown you is just one part of the story, that’s only giving the “IO Read MB/s” - an IO subsystem
statistic. Ideally we must have a correlation on the following subsystems of the database server to fully characterize
the overall workload and performance:
1) Oracle
 Oracle instance and database configuration
2) Operating System
 CPU, memory, IO, and network
3) Application
 SQLs and anything specific to the application
For the correlation we would be using the “3-circle analysis” technique [1] where each subsystem represents a circle
and is diagnosed separately and then in combination. If the problem resides with the database server, the overlap of
the 3 circles is the current performance problem. By doing this we will have a clear correlation of the workload and
performance across subsystems and will have targeted efforts to improve the overall response time.
In mining the AWR having a query in a time series layout and only the relevant statistics shown side by side can be
very useful in various ways and even if it can’t be shown side by side each bottleneck period relates to a particular
SNAP_ID so the correlation across various performance data is extremely possible!
Having this we would have the following advantages
 Quickly notice trends for performance diagnosis
 We have the beautiful set of workload and performance data now in our control
 We have lots of data points for statistical and predictive analysis
 Faster analysis ever!
A
a
T
T
c
Script Na
awr_genw
awr_topev
awr_servic
As I go along
applied succes
The chart belo
The table bel
created:
ame DB
wl DB
DB
DB
DB
vents DB
DB
DB
ces DB
DB
g with my re
ssfully on rea
ow shows the
low shows th
IM
BA_HIST vie
BA_HIST_SNAPS
BA_HIST_OSSTA
BA_HIST_SYS_T
BA_HIST_SYSST
BA_HIST_SNAPS
BA_HIST_SYSTE
BA_HIST_SYS_T
BA_HIST_SNAPS
BA_HIST_SERVI
esearch of mi
al world perfo
categorical r
he important
MPORTANT NO
ews
SHOT
AT
TIME_MODEL
TAT
SHOT
EM_EVENT
TIME_MODEL
SHOT
ICE_STAT
ining the AW
ormance scena
relationship o
details of th
TE: Diagnostic
Data pres
AAS
CPU capac
CPU requir
Memory re
IO require
Logged on
CPU Utiliza
Event
Event Ran
Waits
Time
Avgwt (ms
DB Time %
AAS
Wait Class
Service Na
DB Time
DB CPU
Physical Re
Logical Rea
AAS
WR I have cr
arios.
f the scripts:
he scripts and
c Pack License
sented
city
rements
equirements
ments
users
ation
k
s)
%
ame
eads
ads
reated and co
d some reaso
e is needed for
Descriptio
This is the
overview of
the relations
Utilization =
The AAS co
periods whe
just idle
This is a ve
with AAS m
Coming from
must be aw
drilling dow
of data over
Graphing th
that outputs
different wa
you could g
Service ena
or allowing
This data is
us a classif
database.
Showing thi
column will
most the wo
ollected some
on behind ho
r the scripts
on
starting point.
f the load of th
ship of the form
= Requirements
olumn serves a
ere the databa
rsion of "Top 5
etric.
m the awr_genw
ware about the c
n on the time c
r a period of tim
his data will be m
s a nice graph a
ait classes giving
o back and drill
ables the groupi
the distribution
s commonly see
fication of the
is data in a tim
give us an idea
orkload of the d
e useful scrip
ow they are f
You first run
he database se
mula
/ Capacity
as a (golden) m
ase could be h
Timed Events"
wl, for the AAS
components of A
components) an
me (across SNAP
much like the E
and slicing the A
g you a broad “
l down on the p
ng of common
of connections
en on the Enter
application/mo
me series manne
a if particular ap
database.
pts that I hav
formatted and
this SQL to ha
rver. It clearly
metric on findi
having a bottlen
but across SNA
to be more use
AAS (much like
d have this kind
P_IDs).
nterprise Manag
AAS component
“historical” view
past load activity
database conne
s (e.g. RAC).
prise Manager t
odule activity o
er and adding a
pplications are
e
d
ave an
shows
ng the
neck or
AP_IDs
ful we
d
ger
ts to
which
y.
ections
to give
on the
an AAS
driving
awr_sysstat DBA_HIST_SNAPSHOT
DBA_HIST_OSSTAT
DBA_HIST_SYS_TIME_MODEL
DBA_HIST_SYSSTAT
AAS
LIO/s
DB Block Changes/s
User Calls/s
Parses/s
Hard Parses/s
Sorts/s
Logon/s
SQL*NET to client MB
SQL*NET to dblink MB
This is a version of "Load Profile" but across SNAP_IDs with
AAS metric.
Useful to quickly notice the Oracle workload change. You may
put additional SYSSTAT statistic you want to monitor here.
awr_topsqlx DBA_HIST_SNAPSHOT
DBA_HIST_SQLSTAT
DBA_HIST_SQLTEXT
SQL_ID
Plan Hash Value
Module
Elapsed Time (s)
Elapsed Time / exec (s)
CPU Time (s)
IO Time (s)
App Time (s)
Concurrency Time (s)
Cluster Wait (s)
LIO
PIO
Direct Writes
Rows
Exec
Parse Count
PX Exec
Time Rank
AAS
SQL_TEXT
The “SQL section” of the AWR report is usually segregated into
sections ordered by the following:
 Elapsed Time
 CPU Time
 Gets
 Reads
 Executions
 Parse Calls
Having separate data for a particular problematic SQL_ID
spread over 1000+ lines of report makes it hard to find every
detail about its performance.
I feel there’s a better way to present the data. And here are
the info/sections you'll get from the script and some short
description:
1) snap_id, time, instance, snap duration
The time period and snap_id could be used to show the SQLs
for a given
workload period..let's say you usual work hours is 9-6pm, you
could just
show the particular SQLs on that period.. there's a data range
section on
the bottom of the script you could make use of it if you want to
filter.
2) sql_id, plan_hash_value, module
You could make use of this info if you want to know where the
SQL was
executed (SQL*Plus, OWB, Toad, etc.).. plus you could
compare the
plan_hash_value but I suggest you make use of Kerry
Osborne's
awr_unstable_plans.sql script if you'd like to search for
unstable plans.
3) total elapsed time, elapsed time per exec
- cpu time
- io time
- app wait time
- concurrency wait time
- cluster wait time
These are the time info.. at least without tracing the SQL you'd
know what
time component is consuming the elapsed time of that
particular SQL.. so
let's say your total elapsed time is 1000sec, and cpu time of
30sec, and io
time of 300sec... you would know that it is consuming
significant IO but you
have to look for the other 670sec which could be attributed by
"other" wait
events (like PX Deq Credit: send blkd,etc,etc)
4) - LIOs
- PIOs
- direct writes
- rows
- executions
- parse count
- PX
Some other statistics about the SQL.. if your incurring a lot of
PIOs, how
many times this SQL was executed on that period, the # of PX
spawed.. just
be careful about these numbers if you have "executions" of
let's say 8.. you
have to divide these values to 8 as well as on the time
section..
only the "elapsed time per exec" is the per execution value..
this is for formatting reasons because I can't fit them all on my
screen..
5) - AAS (Average Active Sessions)
- Time Rank
- SQL type, SQL text
This is one of my favorites... this will measure how's the SQL is
performing against the database server.. I'm using the AAS &
CPU count as my
yardstick for a possible performance problem (I suggest
reading Kyle's stuff
about this):
if AAS < 1
-- Database is not blocked
AAS ~= 0
-- Database basically idle
-- Problems are in the APP not DB
AAS < # of CPUs
-- CPU available
-- Database is probably not blocked
-- Are any single sessions 100% active?
AAS > # of CPUs
-- Could have performance problems
AAS >> # of CPUS
-- There is a bottleneck
so having the AAS as another metric on the TOP SQL is good
stuff.. I've also
added the "time rank" column to know what is the SQLs
ranking on the top
SQL.. normally the default settings of the script will show time
rank 1 to 5.. this could be useful also if you are finding a
particular SQL that is on
rank #15 and you are seeing that there's an adhoc query that
is time rank #1
and #2 affecting the database performance..
And.... this script could also show SQLs that span across
SNAP_IDs... I
would order the output by SNAP_ID and filter on that particular
SQL then you
would see that if the SQL is still running and span across let's
say 2
SNAP_IDs then the exec count would be 0 (zero) and elapsed
time per exec is
0 (zero).. only the time when the query is finished you'll see
these values
populated.. I've noticed this behavior and it's the same thing
that is shown
on the AWR reports.. you could go here for that scenario
http://karlarao.tiddlyspot.com/#%5B%5BTopSQL%20on%20A
WR%5D%5D
awr_topsql DBA_HIST_SNAPSHOT
DBA_HIST_SQLSTAT
DBA_HIST_SQLTEXT
SQL_ID
Plan Hash Value
Module
Elapsed Time (s)
Elapsed Time / exec (s)
CPU Time (s)
Cluster Wait (s)
LIO
PIO
Rows
Exec
Parse Count
PX Exec
Time Rank
AAS
Similar columns from awr_topsqlx but this time just showing
the top 20 SQLs across SNAP_IDs.
awr_unstable_plans
(by Kerry Osborne)
DBA_HIST_SNAPSHOT
DBA_HIST_SQLSTAT
SQL_ID
Executions
Min,Max,Avg Etime
Avg LIO
STD_DEV
This script finds SQL statements with plan instability. I like the
clever use of standard deviation to show SQLs with variable
elapsed time.
awr_parm_mods
(by Kerry Osborne)
DBA_HIST_SNAPSHOT
DBA_HIST_PARAMETER
V$INSTANCE
Parameter Name
Old Value
New Value
This script shows all parameters (including hidden) that have
been modified.
awr_netwl DBA_HIST_SYSMETRIC_SUMMARY Network Minvalue (MB)/s
Network Maxvalue (MB)/s
Network Avgvalue (MB)/s
Network STD_DEV (MB)/s
The data comes from the metric family of tables that shows
“Network Traffic Volume Per Sec”
Keep in mind that metrics are different from sysstat values. On
sysstat you just get the delta and the rate, in metric the
sampling is different let's say the snap duration is 10mins what
metric does is it samples on per 60sec interval (num_interval)
and get the max, min, avg, std_dev of those samples.
awr_est_gc_traffic
(by
John Kanagaraj)
DBA_HIST_SNAPSHOT
DBA_HIST_SYSSTAT
DBA_HIST_DLM_MISC
V$DATABASE
V$PARAMETER
Estimated Interconnect
Traffic (KB)
This script is ideal for RAC environment and shows the
interconnect throughput of an instance. Very useful if you want
to check if the interconnect is being saturated.
awr_iowl DBA_HIST_SNAPSHOT
DBA_HIST_OSSTAT
DBA_HIST_SYS_TIME_MODEL
DBA_HIST_SYSSTAT
AAS
CPU IO WAIT Utilization
OS Load
Single Block R/W IOPS
Multi Block R/W IOPS
R/W MB/s
Total R/W IOPS
R/W Ratio
HW Disk IOPS
HW # of Disks
This script is ideal for monitoring the Oracle IO activity. Very
useful for sizing and consolidating storage for Oracle
databases. This can be used together with a storage
monitoring tool to have a complete picture of IO performance.
The last two columns have the corresponding formula that is
used by storage engineers to determine the number of disk
needed by the database.
HW Disk IOPS = (IOPS * Read Ratio) + (IOPS * Write Ratio *
RAID penalty)
HW # of Disks = Total disk IOPS / IOPS per disk
Of course the “HW # of Disks” is not the final number. There
are other factors (bandwidth, throughput, service time, etc.)
that need to be considered to determine the right storage for a
particular IO workload but this can be your starting point. Also
benchmarking will help a lot on the storage decisions.
awr_io_ts DBA_HIST_SNAPSHOT
DBA_HIST_FILESTATXS
DBA_HIST_TEMPSTATXS
Tablespace R/W IOPS
Tablespace R/W latency
This script shows the IO performance of the tablespaces. This
is the same as what you see in AWR but across SNAP_IDs.
The latency formula is as follows
latency (ms) = (readtim / phy reads) * 10
Keep in mind that on this script the IOPS and latency values
are aggregated from all the datafiles of the tablespace. So
diagnosing latency issues using this script may not represent
the actual numbers but may warn you from the textual trends
of high latency (ms) numbers that way you’ll be interested on
particular workload periods to probe it with small duration
samples.
awr_io_file DBA_HIST_SNAPSHOT
DBA_HIST_FILESTATXS
DBA_HIST_TEMPSTATXS
Datafile R/W IOPS
Datafile R/W latency
This script shows the IO performance of the datafiles. This is
the same as what you see in AWR but across SNAP_IDs.
Keep in mind that the IOPS and latency values may be
normalized if the snap interval is too long (60mins above)
compared to per 5seconds or 10 minute snap interval. (see
Appendix)
r2toolkit [2] DBA_HIST_SNAPSHOT
DBA_HIST_DATABASE_INSTANCE
DBA_HIST_SYSSTAT
DBA_HIST_SYSTEM_EVENT
DBA_HIST_SYS_TIME_MODEL
DBA_HIST_OSSTAT
DBA_HIST_WR_CONTROL
Y and X values that can
be plotted for Linear
Regression
This is a performance toolkit that uses AWR data and Linear
Regression to identify what metric/statistic is driving the
database server’s workload. The data points can be very useful
for capacity planning giving you informed decisions and
completely avoiding guesswork!
You can also do the same kind of mining with Statspack. Each DBA_HIST view has a counterpart Statspack view and
you can achieve similar results
DBA_HIST_SNAPSHOT = STATS$SNAPSHOT
DBA_HIST_OSSTAT = STATS$OSSTAT
DBA_HIST_SYS_TIME_MODEL = STATS$SYS_TIME_MODEL
DBA_HIST_SYSSTAT = STATS$SYSSTAT
The scripts mentioned are freely downloadable and more details on the math and performance formulas (rates, time,
IOPS, CPU, latency, utilization, AAS) will be discovered when you look into the SQL code. I would also suggest that
if you are serious on mining the AWR you must take time to play further with the DBA_HIST tables and the
underlying data and you’ll appreciate that you have a better understanding on how the data are derived on the plain
AWR report.
PART 3 - Visualization
Average Active Sessions (AAS) has become my default (golden) metric on finding the periods where the database
could be having a bottleneck or just idle. Essentially AAS is the database load; this value should not go above the
CPU count (NUM_CPUS in DBA_HIST_OSSTAT) and if it does then that means the database is working very hard
or waiting a lot for something.
Together, the AAS & CPU count is used as a yardstick for a possible performance problem [3]
    If AAS < 1  
      ‐‐ Database is not blocked 
 
    AAS ~= 0  
      ‐‐ Database basically idle 
      ‐‐ Problems are in the APP not DB 
 
    AAS < # of CPUs 
      ‐‐ CPU available 
      ‐‐ Database is probably not blocked 
      ‐‐ Are any single sessions 100% active? 
 
    AAS > # of CPUs 
      ‐‐ Could have performance problems 
 
    AAS >> # of CPUS 
      ‐‐ There is a bottleneck 
Just like a doctor, AAS could be your “stethoscope” when investigating performance problems but it doesn’t stop
there. For it to be more useful you must be aware about the components of AAS much like drilling down on the
time components and have this kind of data over a period of time (across SNAP_IDs). Well Enterprise Manager
does this nice graphs on the “Performance and Top Activity page” and slicing the AAS components into different
“Wait Classes” and it’s got a “Historical” view which you could go back and drill down on the past load activity.
But what could be the problem?
S
I know so
long AWR
because th
some othe
So what could
1) U
SN
2) O
To be co
SNAP_ID
The imag
there’s a
componen
ome of you h
R retention p
here was an i
er issue where
d be the alter
Use the Top T
NAP_IDs
Or use the scri
onsistent with
D 335-339. No
ge below is a
big spike on
nts.
have encounte
period (365 da
instance shutd
e Enterprise M
rnative?
imed Events
pt together w
h the initial e
ote that the A
stacked area
n the database
ered this Ent
ays to exagge
down betwee
Manager reall
SQL (awr_to
with Perfsheet
example we
AAS during th
awr_
chart of the
e load… but
erprise Mana
erate it) but E
n the date yo
ly can’t just g
opevents.sql)
! … a great to
will focus on
his period had
_genwl.sql ou
awr_topevent
we want to
ager error at
Enterprise Ma
ou want to go
give you the v
and focus on
ool for ad-hoc
n the same i
d a sudden spi
utput
nts.sql using P
know more
some point. Y
anager won’t
o and the date
visualization y
the AAS and
c performance
interval time
ike that is on t
Perfsheet. It’s
about it by d
You are conf
let you go ba
e you are now
you need.
d wait class co
e visualizatio
6:20 to 7:0
the range of 2
s clear from t
drilling down
figured with
ack farther al
w. Or could b
olumns acros
on [4]
1 AM that i
2.2 to 3.5
the image tha
n on the AAS
a
ll
e
s
s
at
S
S
Looking a
know wh
activity, it
Some more ba
On the E
into differ
From the
ways to d
1) T
2) S
AAS on t
model. T
DBA_HIS
at the “textua
hich AAS com
t’s evident tha
ackground
nterprise Ma
rent wait clas
2nd slide of K
erive the valu
Time Statistics
ampling
the Performa
This is also
ST_SYSTEM
al trends” of a
mponent is d
at there’s a hi
anager “Perfor
ses. But, did y
Kyle Hailey’s
ue:
s
ance Page use
what the sc
M_EVENT a
Stacke
awr_topevent
driving the w
igh User IO a
awr_to
rmance” and
you know tha
s presentation
es “Time Sta
cript awr_top
and the “CPU
ed area chart o
ts.sql output j
workload of th
activity.
opevents.sql o
“Top Activit
at their data so
n [3] on AAS
atistics” and i
pevents.sql is
U” from tim
of AAS
just by lookin
he database.
output
ty” Page you
ources are dif
(Average Ac
is actually fr
s doing… it
me model vie
ng at the AA
For the part
’ll see the AA
fferent?
ctive Sessions
rom v$system
t unions the
ew DBA_HIS
S column we
ticular SNAP
AS compone
s) it says that
m_event + CP
e output of
ST_SYS_TIM
e would easily
P_IDs of high
ents are sliced
there are two
PU from tim
“events” on
ME_MODEL
y
h
d
e
n
L
S
N
and then f
it look sim
AAS valu
“CPU use
AAS on th
on a 15
refresh to
CPU from
So what’s the
On a high
to Perform
session (th
think) tha
Time Stat
If you wa
History of
Now time for
Finding th
we can cr
filter only the
milar to the E
ues will be cou
ed by this sess
he Top Activ
5sec refresh
o Historical t
m time model)
e effect?
h CPU activity
mance Page
he only way t
an v$sysstat “
tistics (one of
ant more info
f Session Loa
Perfsheet a l
he AAS comp
eate the same
e top 5 and do
Enterprise Ma
unted. By the
sion”.
vity Page uses
rate… but
then it also st
).
y period you
. Simply bec
to see CPU u
“CPU used by
f two ways to
o about the d
ad [5] and AA
la Enterprise
ponent that’s
e visualization
Stacke
o this across th
anager Perfor
e way, on 10g
s “Sampling”
as I have
tarts to behav
’ll notice that
cause ASH s
usage real tim
y this session
calculate AA
etails around
AS investigati
Manager!
driving the w
n like the Ent
ed area chart
he SNAP_ID
rmance Page
g below the lo
and by defau
observed wh
ve like the Pe
t there will be
samples every
e) while the t
n” there could
AS) which cou
d the Perform
on [14]
workload is a
erprise Mana
t AAS compo
Ds but for grap
I have to inc
oad chart is co
ult is taking a
hen you sw
erformance P
e a higher AA
y second and
time model C
d still be som
uld be affecte
mance and To
a lot easier in
ager broken do
onents – wai
phing purpose
clude all of t
oming from v
advantage of A
witch from
age (pulls da
AS on the To
d it does tha
CPU although
me lag time an
ed by average
p Activity pa
n graphics. Th
own into “Wa
it class
es on the Perf
the “events”
v$system_eve
ASH (sample
the Real T
ata from v$sy
p Activity Pa
at quickly on
h it updates qu
nd it will stil
s.
age this is wo
he image belo
ait Class”.
fsheet to mak
so that all th
ent + v$syssta
es) and does i
Time 15 se
ystem_event +
age compared
n every activ
uicker (5secs
ll be based on
orth reading
ow shows tha
e
e
at
it
c
+
d
e
I
n
-
at
Even mor
graphs. B
is mostly
Ooops, do
uses could
view and
compare
chart view
Compare
it’s on the
Then com
happening
1.6 on SN
re, we have t
elow is broke
consuming th
on’t get too ex
d hide import
see the data
the above an
w could tell a
the wait clas
e range of 0.1
mpare the wai
g.. but on 3D
NAP_ID 335 a
the data now
en down into
he AAS.
Stack
xcited.. impor
tant informati
a clearly sepa
nd below ch
a more meanin
ss chart… ab
1 (hidden bet
it event char
you can see
and 336. Yes,
in our contro
“Wait Events
ked area chart
rtant reminde
ion and somet
arated into th
harts, you’ll k
ngful story.
bove notice th
tween CPU an
rt… notice th
that only the
, you will also
ol. So we cou
s”, aside from
t AAS compon
er… the 2-dim
times could b
heir respective
know what I
he blue (Othe
nd System IO
he big differen
db file sequ
o not be foole
uld play arou
m being more
ents – wait ev
mensional Sta
be misleading
e component
I mean.. Wa
er wait class)
O)… that’s a b
nce on the ch
ential read a
ed when you
und with the
colorful it let
vents
acked area cha
g [13] and it r
ts, rather than
ait Class and
on the range
big difference
hart? above y
and direct pa
look at the ra
data and crea
t’s you see wh
art that Enterp
really helps to
n being stack
d Wait Event
e of AAS of 1
e!
you can’t real
ath read are o
aw data… but
ate interesting
hat wait even
prise Manage
o have anothe
ked… As you
ts in 3D area
1 while below
lly tell what’
on the AAS o
t visualization
g
nt
er
er
u
a
w
s
of
n
A
is much e
AAS through
On my te
data. You
SNAP_ID
database.
beyond m
there you
asier and the
out the AWR
st machine I
u can see from
D 335-339) ha
You could a
my maximum
could use AS
way to go bu
3
3D
R retention pe
have 365 day
m the chart b
appens to be
also see the p
CPU which
SH, run the A
ut you must be
D area chart A
D area chart AA
eriod!
ys retention p
below (stacke
the highest l
period of shut
could justify
AWR report, ru
e able to sens
AAS componen
AS component
period. This e
ed area chart
oad period f
tdowns (nega
the drill dow
un ADDM, o
e and validate
nts – wait clas
ts – wait even
enables me to
t), that what
from all the A
ative value) a
wn on the spe
or make use o
e if it’s drivin
ss
nts
o have a data
we are focus
AAS samples
and other tim
ecific SNAP_
f your high ca
ng you to bad
warehouse of
sing on (6:20
for the lifetim
me period whe
_IDs or time
aliber scripts!
d conclusions.
f performanc
0 to 7:01 AM
me of my tes
ere AAS wen
frame… from
!
e
M
st
nt
m
PAR
U
The good
RT 4 - Capa
Utilization is
Capacity
expected
will fit in
measurem
and presen
Measuring
 H
 E
 E
On the In
explained
Requirem
Essentiall
formula
Utilization = 
As shown
water” an
decision t
into the s
server cap
much or i
thing here is
acity Plann
the ultimate m
planning pla
and unexpec
nto the availab
ment [7]. Goo
nt the in a mo
g the workloa
Have enough c
Enable us to qu
Enable us to qu
ntroduction to
d in detail wha
ments, and U
ly what we ca
Requirements / C
n on the imag
nd “another p
to purchase th
erver. And o
pacity. And w
t could be the
, you are not
ning
metric!
ays a very im
ted workload
ble capacity o
d thing the d
ore meaningfu
ad will give u
capacity and n
uantify the re
uantify the be
o Oracle Serv
at information
Utilization
are most in C
Capacity 
ge below the
pitcher with b
he database s
f course, the
when this does
e other way ar
guessing!
mportant role
ds. The prima
of the databa
ata collection
ul and useful
us the followin
not over buy
esults of respo
enefit of work
er Consolidat
n you need to
Capacity Plann
“empty pitch
beer” are the
erver that is t
application r
sn’t occur nic
round where t
to ensure pr
ary principle
se server. An
n process is a
manner.
ng advantages
onse time opti
kload reductio
tion paper [6
o get for you
ning is the da
her” represent
Oracle work
they define th
requirement m
cely, there can
the capacity i
roper resourc
is to ensure
nd with this w
already being
s and benefits
imizations in
on
] and Chapte
to be able to
atabase server
ts the databas
kload require
he capacity. T
may or may
n be an exces
is not enough
es are availa
the applicati
we need to ha
done by AW
s [7]:
the savings o
er 9 of Craig
define the Da
r utilization a
se server capa
ements. Typic
Then they sta
not fit nicely
s of capacity,
h for the requi
able and be a
ion workload
ave a facility
WR. We just n
of system reso
Shallahamer’
atabase Serve
and it is repre
acity while th
cally the IT s
art pouring th
y on the avail
, which mean
irements at ha
able to handl
d requirement
y for workload
need to extrac
ources
’s book [8] h
er’s Capacity
esented by thi
he “glass with
shop makes
he application
lable databas
ns IT spent too
and.
e
s
d
ct
e
y,
s
h
a
s
e
o
This simp
presented
Having th
periods w
ple and very u
in a manner
he data presen
with high work
useful concep
that we can e
nted this way
kload requirem
pt can be app
asily abstract
y, we can easi
ments.
plied as well i
t the performa
ily apply filte
in AWR. Usi
ance statistics
er to the data
ing the awr_g
s to the Utiliz
set and imm
genwl.sql scr
zation formula
mediately find
ript the data i
a.
d the workload
s
d
C
And we c
AAS range 
   
 
Per SNAP_ID 
   
   
 
Oracle CPU U
   
 
OS CPU Utiliz
   
 
Particular Wo
 
 AND TO_CHA
 AND TO_CHA
 AND TO_CHA
 AND TO_CHA
 AND s0.END_
 AND s0.END_
CPU sizing re
Having th
The data
server is a
occurred.
needed to
The formu
core need = #
The data
collocated
can virtua
ould do other
aas > 1 
or range of SNAP
id in (336) 
where id >= 3
Utilization 
oracpupct > 5
zation 
oscpupct > 50
orkload periods 
AR(s0.END_INTERV
AR(s0.END_INTERV
AR(s0.END_INTERV
AR(s0.END_INTERV
_INTERVAL_TIME 
_INTERVAL_TIME 
ecommendati
his data outpu
points below
a dual core m
The manage
handle the w
ula used to de
# of cores * utilizat
points were
d to a data cen
alize it to a ne
r filtering as w
P_IDs 
36 and  id <= 340 
0 
0 
VAL_TIME,'D') >= 
VAL_TIME,'D') <= 7
VAL_TIME,'HH24M
VAL_TIME,'HH24M
>= TO_DATE('2010
<= TO_DATE('2010
ions
ut can be easil
w came from a
machine and b
ement would
workload of th
erive the “CPU
tion * 1.25 
very useful
nter, we could
ewer hardware
well…
1     ‐‐ Day of week
7 
MI') >= 0900     ‐‐ H
MI') <= 1800 
0‐jan‐17 00:00:00
0‐aug‐22 23:59:59
y used as inp
an actual pro
been used for
like to know
he database.
U core need”
to character
d opt to just u
e.
k: 1=Sunday 7=Sat
Hour 
','yyyy‐mon‐dd hh
9','yyyy‐mon‐dd hh
uts to CPU si
oduction serve
r almost 8 yea
w what would
[9] is as follo
ize the curre
upgrade to a n
turday 
h24:mi:ss')    ‐‐ Dat
h24:mi:ss‘) 
izing of a data
er that needs
ars and there
d be the ideal
ows:
ent utilization
newer model
ta range 
abase server.
to be migrat
e have been a
l machine and
n of the data
but not the la
ted to a new
couple of ha
d how many
abase server.
atest and the g
machine. Th
ardware error
cores will b
Since it wa
greatest or w
e
s
e
s
e
S
But notice
summariz
ignore the
Validating
a year. H
process w
affect the
Storage sizing
Having th
e the outlier (
zing the data
e outlier just l
g with the app
Having this in
will run again
overall conne
g recommend
his data outpu
(shown in red
will tell me t
like that becau
plication own
nformation, w
on the new se
ected users.
dations
ut can be easil
d above) repre
that I’m most
use there mig
ner, she confi
we can safely
erver we just
y used as inp
esenting a SN
t of the time
ght be a critica
irmed that it w
remove the
have to make
uts to storage
NAP period ha
on the 10 %<
al application
was indeed an
outlier from
e sure that it’
e sizing of a d
aving high CP
< CPU utiliza
n process on th
n adhoc proce
the data poi
s being run o
database serve
PU utilization
ation but we
hat workload
ess that is bei
ints and even
on an off-peak
er.
n. Statistically
don’t want to
d period.
ing done onc
n if the adho
k period to no
y
o
e
c
ot
The data
mentioned
can be us
measured
Also take
determine
will help a
For storag
points below
d above. This
sed together w
data easily tr
note that the
e the right sto
a lot on the st
ge sizing purp
w came from
s shows the I
with a storag
ransforms req
re are other f
orage for a pa
torage decisio
poses, I strong
m awr_genw
IOPS requirem
e monitoring
quirements to
factors (bandw
articular IO w
ons.
gly recommen
wl.sql as wel
ments needed
tool to have
capacity.
width, through
workload but
nd using the a
l, sizing sto
d to run the d
e a complete
hput, service
this can be y
awr_iowl.sql
rage for the
database on t
picture of IO
time, etc.) th
your starting
same produ
the new envir
O performanc
hat need to be
point. Also b
uction system
ronment. Thi
ce. Having th
considered to
benchmarking
m
s
e
o
g
Rea
D
al World Ex
Diagnosing a
The graph
processing
done any
performan
So it’s a
plotted in
was able
visualizat
On this im
peaks are
suspect or
particular
and OS s
problem.
If it weren
This is the
xample
and Resolving
h shown was
g so it’s the m
changes on t
nce problem s
sudden slow
one graph…
to apply the
ion and I was
mage above y
e the particula
r possible cul
database ses
statistics (CPU
n’t for this vis
e image after
g GC Block L
a sudden slo
most critical w
the database e
so the tasks o
down, and I
that would a
e things that
s able to achie
you can see t
ar periods w
lprit for the p
ssions running
U, memory,
sualization th
replacing the
Lost
ow down on a
week of the m
environment…
f finding whe
I was thinkin
answer a lot o
t I have lear
eve what I hav
the where, wh
e are interest
performance p
g critical mod
network) we
he troubleshoo
e network inte
a client runni
month. Interv
… well that w
ere/when/why
ng… if I can
of questions.
ned. So I m
ve envisioned
hen, and why
ted in. And w
problem. Dril
dules that are
e were able c
oting would h
erconnect swi
ing 2 nodes o
viewing the D
would be the
y it went wron
have time se
Coming from
made use of P
d.
y. Most of th
what wait ev
lling down fu
e slow plus c
conclude that
have taken lon
itch… this sh
of RAC and
DBA, he wou
majority of th
ng is all left to
eries perform
m Tanel Pode
Perfsheet and
he load is on
vents are con
urther on thos
correlating it
t it was a ne
nger.
ows their nor
it’s a period
ld insist that
he customers
o us.
mance of both
r’s seminar in
d played aro
the first node
ntributing on
se peak perio
with the data
etwork interco
rmal workload
of month end
they have no
s will say on
h of the node
n Singapore,
ound with th
e. And on th
the peak is
ods and on th
abase advisor
onnect switch
d.
d
ot
a
s
I
e
e
a
e
s
h
LLinear Regres
Mining th
targeted re
The graph
8core HS2
respective
at >80% t
On the dri
high load
componen
when look
reduction,
If the serv
seems to b
ssion of AAS
he AWR back
esponse time
h shown below
21 Bladeserve
ely which sho
the AAS also
ill down show
SQL greatly
nt being utiliz
king at the SQ
, response tim
ver’s workloa
be low. Also
Nod
S and CPU on
ked by solid s
optimization
w is a scatter
er on a DS48
ows a strong c
shoots up!
wn below on t
affecting the
zed is on “CPU
QL details on
me optimizatio
ad is on the
you will notic
de 1
n 2 node RAC
statistical ana
ns and worklo
plot of a prod
00 SAN. Not
correlation be
the peak perio
overall perfo
U” hence you
awr_topsqlx.
on, and huge
AAS value o
ce the top SQ
C
alysis [10] [1
ad reduction.
duction enviro
tice the strong
tween AAS v
od with AAS
ormance of th
u will see larg
. Tuning the h
savings on sy
of 2.2, the CP
QL from AAS
1] [12] lets y
onment with
g correlation c
vs. CPU utiliz
value of 10 i
e database. A
ge LIOs and m
high load SQL
ystem resourc
PU utilization
of 10 is not t
you do foreca
2 nodes of 11
coefficient (R
zation. Also w
it shows that t
Also note that
most of the el
L will result t
ces.
n, latency, A
there anymore
Nod
ast that can gu
1gR1 RAC ru
R2) of .97 and
when CPU sta
the workload
the large chu
lapsed time sp
to great work
AAS compone
e.
de 2
uide you with
unning on
d .89
arts to queue
is driven by
unk of AAS
pent on CPU
kload
ent on “CPU
h
”
Drill
The perfo
database s
informed
The toolk
- CREAT
- DROP
- CREAT
- POPUL
- ANAL
- POPUL
- R2 REP
ing down o
1) General W
2) Tablespa
3) Top Ti
ormance toolk
server’s work
decisions and
kit contains 7
TE USER - c
TABLES - d
TE THE r2 T
LATE y data
YZE r2 VAL
LATE x and r
PORT - gene
on the peak
Workload repor
ace IO report
med Events
kit uses AWR
kload based on
d completely
sections, see b
reates the r2to
drop the tables
TABLES - cre
- y data is the
LUES - get the
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Whitepaper: Mining the AWR repository for Capacity Planning and Visualization

  • 1. M PAR I 1 t r A o D c a S ining th RT 1 - Whe I’m certain th 108 AWR rep the bottleneck reports by han AWR reports of the 1000+ l Definitely thi consultant I m already availa SQL*Plus ses e AWR New CPU a cost. H available DBAs an guesswo proper p for your savings AWR is steroids workloa samples to visua AWR da and Util metrics In this p to have Analysis re it all sta hat DBAs or d ports in just an k? And what nd, and it is a generation, e lines of perfo s will lead to must also be aw able to help ssion? Reposit o Us and storage a Hence, capacity p e and to handle nd IT managers ork you'll end up planning, and ma r workload with for the company a built-in data s ". It has impro d information w s, we could build alize data and us ta samples is we ization in terms for Capacity Plan paper you will lea e a clear-cut me s, and Performan arted developers do n hour. How a is the bottlen a daunting an especially wh rmance data t o longer analy ware on how with the trou tory for C other Re K Oracle ACE karlara arrays are getting planning plays a expected and un is justifying the p getting the mo anagement of gr allowance for a y and a happier I store that starte oved significantl when going thro amazing reports se statistical met e are able to def of CPU, IO, me nning. arn how to make easurement on nce Firefighting. on’t have eno about 108 AW neck? Well be nd repetitive e hen you start r to correlate it ysis periods h to optimize m ubleshooting Capacity al World Karl Arao E, OCP-DBA ao@gmail.co g faster, but the very important nexpected worklo expense of add st expensive har rowth, you'll be particular grow IT shop. d in 10gR1 and y in 11gR2, en ugh all the AW s that will let us thods for analys fine the databas emory, and netw e use of the AWR resources to aid ough time to s WR reports in efore it will ta execution of a reading each t to the proble hence longer my troublesho but what if y Plann d Stuff A, RHCE om se resources are role to ensure pr oads. Another cri ding resources on rdware. With pro able to get just wth period. This is very much lik nabling you to R snapshots. Fr notice trends an is. Even more su se server's Capac work, which are v R, specifically the d in Capacity P spare to read n 5 minutes ju ake so much awrrpt.sql. Y of them and em at hand. r time for a p ooting time. Y you are only ing, Vis e finite and come roper resources a itical matter for t n the system. W oper measureme the right hardwa will result in hu ke a "Statspack have a far bet rom the AWR d d makes it possi urprising about t city, Requiremen very important k e DBA_HIST view Planning, Predict d 108 AWR re ust to answer of my time ju You will be ov you only nee problem to be You can argu y left with ju ualizatio e at are the With ent, are uge on tter ata ble the nts, key ws, tive eports in a da the question w ust to generat verwhelmed b ed to see parti e solved and ue that there ar ust a comma on, and ay, even mor what period i te these AWR by the manua icular section as a databas re visual tool and line or an e s R al s e s n
  • 2. T p v PAR A s O T a p 3 t F d s d T f T 3 A t This scenario performance d visualize the d RT 2 - How AWR is much sources of the Oracle version The AWR rep an AWR repo performance p 339) within th the workload For the query data blocks re since instance delta and tran To transform formula. See t IO MB/s = ( (d                 = ((5                 = 73 To validate th 339. The imag Also a run of the throughpu triggered me data in more data, or even p w to mine th h like “Statspa e AWR repor n 11.2. port provides ort for SNAP problems we he specified in change that’s y output we a ead from disk e start. We ar nsforming it to the delta to the example f delta * <block_size 5663126 * 8192) / 3.37 MB/s  he accuracy o ge below show Automatic D ut of 74 MB/s e to mine on t meaningful m possible to do he AWR ack on steroid rt are the DB a single summ P_ID 335 to are more inte nterval. In th s happening. are investigati k. It is also im re particularly o a more mea a more mean for SNAP_ID e>) /1024/1024 ) / 1024/1024) / 603  f the derived ws the delta w Database Diag that is really the source tab manner that w o some statist ds” it is a won BA_HIST view mary report b 339 that is a erested to see at way we ha ing for the S mportant to no y interested o aningful and r ningful outpu D 338 below: / <snap_duration_ value we nee we used to der gnostic Monit close to our d bles of the AW will be easier tics out of it. nderful data c ws which hav based upon an an interval tim what occurre ave a granular YSSTAT sta ote this is a cu on the delta o eadable outpu ut that we cou _in_seconds>  ed to compar rive the MB/s tor (ADDM) derived value WR report to for me to no collector for O ave grown fro n interval of t me from 6:20 ed during eac r view of wha atistic “physic umulative phy of each SNAP ut. uld easily un re it with the s is correct. on SNAP_ID e cut out the u otice trends an Oracle and OS om 67 in Ora time. On the i 0 – 7:01AM. ch of the samp at’s going on cal reads” wh ysical reads b P_ID that is nderstand we actual AWR D 338 – 339 s unnecessary an nd even poss S statistics. T acle version 1 image below However wh ple (335,336, n and have a b hich is the to by all the data end_value – would apply report on SN shows that we nd present th ible for me to The underlying 10.1 to 108 in we can creat hen analyzing , 337, 338 and better view on tal number o abase session start_value = y the IO MB/ NAP_ID 338 – e are reaching e o g n e g d n of s =  s – g
  • 3. A T   And checking The data show SELECT * FRO ( SELECT s0.sn   TO_CHAR(s0   s10t0.stat_n   s10t0.value    s10t1.value    (s10t1.value   round(((((s1                                                                                ),2) as phyr FROM dba_h            dba_hi            dba_hi            dba_hi WHERE s0.db AND s1.dbid   AND s10t0.db AND s10t1.db AND s0.instan AND s1.instan AND s10t0.in AND s10t1.in AND s1.snap_ AND s10t0.sn AND s10t1.sn AND s10t0.st AND s10t1.st )  WHERE snap_ ORDER BY sn g it with the E wn above com OM  nap_id snap_id,  0.END_INTERVAL_ name,  start_value,   end_value,  e ‐ s10t0.value) de 0t1.value ‐ s10t0.v           + EXTRACT(H           + EXTRACT(M           + EXTRACT(S reads_mbps  ist_snapshot s0,  st_snapshot s1,  st_sysstat s10t0,    st_sysstat s10t1  bid              = 26079               = s0.dbid  bid             = s0.dbi bid             = s0.dbi nce_number     = 1 nce_number     = s stance_number  = stance_number  = _id             = s0.sna nap_id          = s0.sn nap_id          = s0.sn at_name        = 'ph at_name        = s10 _id in (335,336,33 ap_id ASC;  Enterprise Man mes from quer _TIME,'YY/MM/DD lta,  value)* 8192)/102 HOUR FROM s1.EN MINUTE FROM s1 SECOND FROM s1               ‐‐ physica 950532    ‐‐ DBID  d  d  1               ‐‐ INSTAN s0.instance_numb = s0.instance_num = s0.instance_num ap_id + 1  nap_id  nap_id + 1  hysical reads'  0t0.stat_name  7,338,339)  nager Perform ry below: D HH24:MI') TIME, 24/1024)  / ((round ND_INTERVAL_TIM .END_INTERVAL_T .END_INTERVAL_T l reads, diffed  NCE_NUMBER  er  mber  mber  mance page sh d(EXTRACT(DAY FR ME ‐ s0.END_INTER TIME ‐ s0.END_INT TIME ‐ s0.END_INT hows that the ROM s1.END_INTE RVAL_TIME) * 60  TERVAL_TIME)   TERVAL_TIME) / 6 e Disk IO is ar ERVAL_TIME ‐ s0.E 60, 2))*60)  round our der END_INTERVAL_TI rived value IME) * 1440  
  • 4. You may have noticed that I used the SQL trick below that has similar effect to the LAG function. This enables the query to get the start_value and end_value on a single row making it possible to get the delta value and apply the performance formula. The view DBA_HIST_SNAPSHOT also acts as an ultimate reference of snap information that allows joining to the other DBA_HIST views to provide meaningful data on other subsystems or workload performance data. AND s10t0.snap_id          = s0.snap_id  AND s10t1.snap_id          = s0.snap_id + 1  The query I’ve shown you is just one part of the story, that’s only giving the “IO Read MB/s” - an IO subsystem statistic. Ideally we must have a correlation on the following subsystems of the database server to fully characterize the overall workload and performance: 1) Oracle  Oracle instance and database configuration 2) Operating System  CPU, memory, IO, and network 3) Application  SQLs and anything specific to the application For the correlation we would be using the “3-circle analysis” technique [1] where each subsystem represents a circle and is diagnosed separately and then in combination. If the problem resides with the database server, the overlap of the 3 circles is the current performance problem. By doing this we will have a clear correlation of the workload and performance across subsystems and will have targeted efforts to improve the overall response time. In mining the AWR having a query in a time series layout and only the relevant statistics shown side by side can be very useful in various ways and even if it can’t be shown side by side each bottleneck period relates to a particular SNAP_ID so the correlation across various performance data is extremely possible! Having this we would have the following advantages  Quickly notice trends for performance diagnosis  We have the beautiful set of workload and performance data now in our control  We have lots of data points for statistical and predictive analysis  Faster analysis ever!
  • 5. A a T T c Script Na awr_genw awr_topev awr_servic As I go along applied succes The chart belo The table bel created: ame DB wl DB DB DB DB vents DB DB DB ces DB DB g with my re ssfully on rea ow shows the low shows th IM BA_HIST vie BA_HIST_SNAPS BA_HIST_OSSTA BA_HIST_SYS_T BA_HIST_SYSST BA_HIST_SNAPS BA_HIST_SYSTE BA_HIST_SYS_T BA_HIST_SNAPS BA_HIST_SERVI esearch of mi al world perfo categorical r he important MPORTANT NO ews SHOT AT TIME_MODEL TAT SHOT EM_EVENT TIME_MODEL SHOT ICE_STAT ining the AW ormance scena relationship o details of th TE: Diagnostic Data pres AAS CPU capac CPU requir Memory re IO require Logged on CPU Utiliza Event Event Ran Waits Time Avgwt (ms DB Time % AAS Wait Class Service Na DB Time DB CPU Physical Re Logical Rea AAS WR I have cr arios. f the scripts: he scripts and c Pack License sented city rements equirements ments users ation k s) % ame eads ads reated and co d some reaso e is needed for Descriptio This is the overview of the relations Utilization = The AAS co periods whe just idle This is a ve with AAS m Coming from must be aw drilling dow of data over Graphing th that outputs different wa you could g Service ena or allowing This data is us a classif database. Showing thi column will most the wo ollected some on behind ho r the scripts on starting point. f the load of th ship of the form = Requirements olumn serves a ere the databa rsion of "Top 5 etric. m the awr_genw ware about the c n on the time c r a period of tim his data will be m s a nice graph a ait classes giving o back and drill ables the groupi the distribution s commonly see fication of the is data in a tim give us an idea orkload of the d e useful scrip ow they are f You first run he database se mula / Capacity as a (golden) m ase could be h Timed Events" wl, for the AAS components of A components) an me (across SNAP much like the E and slicing the A g you a broad “ l down on the p ng of common of connections en on the Enter application/mo me series manne a if particular ap database. pts that I hav formatted and this SQL to ha rver. It clearly metric on findi having a bottlen but across SNA to be more use AAS (much like d have this kind P_IDs). nterprise Manag AAS component “historical” view past load activity database conne s (e.g. RAC). prise Manager t odule activity o er and adding a pplications are e d ave an shows ng the neck or AP_IDs ful we d ger ts to which y. ections to give on the an AAS driving
  • 6. awr_sysstat DBA_HIST_SNAPSHOT DBA_HIST_OSSTAT DBA_HIST_SYS_TIME_MODEL DBA_HIST_SYSSTAT AAS LIO/s DB Block Changes/s User Calls/s Parses/s Hard Parses/s Sorts/s Logon/s SQL*NET to client MB SQL*NET to dblink MB This is a version of "Load Profile" but across SNAP_IDs with AAS metric. Useful to quickly notice the Oracle workload change. You may put additional SYSSTAT statistic you want to monitor here. awr_topsqlx DBA_HIST_SNAPSHOT DBA_HIST_SQLSTAT DBA_HIST_SQLTEXT SQL_ID Plan Hash Value Module Elapsed Time (s) Elapsed Time / exec (s) CPU Time (s) IO Time (s) App Time (s) Concurrency Time (s) Cluster Wait (s) LIO PIO Direct Writes Rows Exec Parse Count PX Exec Time Rank AAS SQL_TEXT The “SQL section” of the AWR report is usually segregated into sections ordered by the following:  Elapsed Time  CPU Time  Gets  Reads  Executions  Parse Calls Having separate data for a particular problematic SQL_ID spread over 1000+ lines of report makes it hard to find every detail about its performance. I feel there’s a better way to present the data. And here are the info/sections you'll get from the script and some short description: 1) snap_id, time, instance, snap duration The time period and snap_id could be used to show the SQLs for a given workload period..let's say you usual work hours is 9-6pm, you could just show the particular SQLs on that period.. there's a data range section on the bottom of the script you could make use of it if you want to filter. 2) sql_id, plan_hash_value, module You could make use of this info if you want to know where the SQL was executed (SQL*Plus, OWB, Toad, etc.).. plus you could compare the plan_hash_value but I suggest you make use of Kerry Osborne's awr_unstable_plans.sql script if you'd like to search for unstable plans. 3) total elapsed time, elapsed time per exec - cpu time - io time - app wait time - concurrency wait time - cluster wait time These are the time info.. at least without tracing the SQL you'd know what time component is consuming the elapsed time of that particular SQL.. so let's say your total elapsed time is 1000sec, and cpu time of 30sec, and io time of 300sec... you would know that it is consuming significant IO but you have to look for the other 670sec which could be attributed by "other" wait events (like PX Deq Credit: send blkd,etc,etc) 4) - LIOs - PIOs - direct writes - rows - executions - parse count - PX Some other statistics about the SQL.. if your incurring a lot of PIOs, how many times this SQL was executed on that period, the # of PX spawed.. just be careful about these numbers if you have "executions" of
  • 7. let's say 8.. you have to divide these values to 8 as well as on the time section.. only the "elapsed time per exec" is the per execution value.. this is for formatting reasons because I can't fit them all on my screen.. 5) - AAS (Average Active Sessions) - Time Rank - SQL type, SQL text This is one of my favorites... this will measure how's the SQL is performing against the database server.. I'm using the AAS & CPU count as my yardstick for a possible performance problem (I suggest reading Kyle's stuff about this): if AAS < 1 -- Database is not blocked AAS ~= 0 -- Database basically idle -- Problems are in the APP not DB AAS < # of CPUs -- CPU available -- Database is probably not blocked -- Are any single sessions 100% active? AAS > # of CPUs -- Could have performance problems AAS >> # of CPUS -- There is a bottleneck so having the AAS as another metric on the TOP SQL is good stuff.. I've also added the "time rank" column to know what is the SQLs ranking on the top SQL.. normally the default settings of the script will show time rank 1 to 5.. this could be useful also if you are finding a particular SQL that is on rank #15 and you are seeing that there's an adhoc query that is time rank #1 and #2 affecting the database performance.. And.... this script could also show SQLs that span across SNAP_IDs... I would order the output by SNAP_ID and filter on that particular SQL then you would see that if the SQL is still running and span across let's say 2 SNAP_IDs then the exec count would be 0 (zero) and elapsed time per exec is 0 (zero).. only the time when the query is finished you'll see these values populated.. I've noticed this behavior and it's the same thing that is shown on the AWR reports.. you could go here for that scenario http://karlarao.tiddlyspot.com/#%5B%5BTopSQL%20on%20A WR%5D%5D awr_topsql DBA_HIST_SNAPSHOT DBA_HIST_SQLSTAT DBA_HIST_SQLTEXT SQL_ID Plan Hash Value Module Elapsed Time (s) Elapsed Time / exec (s) CPU Time (s) Cluster Wait (s) LIO PIO Rows Exec Parse Count PX Exec Time Rank AAS Similar columns from awr_topsqlx but this time just showing the top 20 SQLs across SNAP_IDs. awr_unstable_plans (by Kerry Osborne) DBA_HIST_SNAPSHOT DBA_HIST_SQLSTAT SQL_ID Executions Min,Max,Avg Etime Avg LIO STD_DEV This script finds SQL statements with plan instability. I like the clever use of standard deviation to show SQLs with variable elapsed time.
  • 8. awr_parm_mods (by Kerry Osborne) DBA_HIST_SNAPSHOT DBA_HIST_PARAMETER V$INSTANCE Parameter Name Old Value New Value This script shows all parameters (including hidden) that have been modified. awr_netwl DBA_HIST_SYSMETRIC_SUMMARY Network Minvalue (MB)/s Network Maxvalue (MB)/s Network Avgvalue (MB)/s Network STD_DEV (MB)/s The data comes from the metric family of tables that shows “Network Traffic Volume Per Sec” Keep in mind that metrics are different from sysstat values. On sysstat you just get the delta and the rate, in metric the sampling is different let's say the snap duration is 10mins what metric does is it samples on per 60sec interval (num_interval) and get the max, min, avg, std_dev of those samples. awr_est_gc_traffic (by John Kanagaraj) DBA_HIST_SNAPSHOT DBA_HIST_SYSSTAT DBA_HIST_DLM_MISC V$DATABASE V$PARAMETER Estimated Interconnect Traffic (KB) This script is ideal for RAC environment and shows the interconnect throughput of an instance. Very useful if you want to check if the interconnect is being saturated. awr_iowl DBA_HIST_SNAPSHOT DBA_HIST_OSSTAT DBA_HIST_SYS_TIME_MODEL DBA_HIST_SYSSTAT AAS CPU IO WAIT Utilization OS Load Single Block R/W IOPS Multi Block R/W IOPS R/W MB/s Total R/W IOPS R/W Ratio HW Disk IOPS HW # of Disks This script is ideal for monitoring the Oracle IO activity. Very useful for sizing and consolidating storage for Oracle databases. This can be used together with a storage monitoring tool to have a complete picture of IO performance. The last two columns have the corresponding formula that is used by storage engineers to determine the number of disk needed by the database. HW Disk IOPS = (IOPS * Read Ratio) + (IOPS * Write Ratio * RAID penalty) HW # of Disks = Total disk IOPS / IOPS per disk Of course the “HW # of Disks” is not the final number. There are other factors (bandwidth, throughput, service time, etc.) that need to be considered to determine the right storage for a particular IO workload but this can be your starting point. Also benchmarking will help a lot on the storage decisions. awr_io_ts DBA_HIST_SNAPSHOT DBA_HIST_FILESTATXS DBA_HIST_TEMPSTATXS Tablespace R/W IOPS Tablespace R/W latency This script shows the IO performance of the tablespaces. This is the same as what you see in AWR but across SNAP_IDs. The latency formula is as follows latency (ms) = (readtim / phy reads) * 10 Keep in mind that on this script the IOPS and latency values are aggregated from all the datafiles of the tablespace. So diagnosing latency issues using this script may not represent the actual numbers but may warn you from the textual trends of high latency (ms) numbers that way you’ll be interested on particular workload periods to probe it with small duration samples. awr_io_file DBA_HIST_SNAPSHOT DBA_HIST_FILESTATXS DBA_HIST_TEMPSTATXS Datafile R/W IOPS Datafile R/W latency This script shows the IO performance of the datafiles. This is the same as what you see in AWR but across SNAP_IDs. Keep in mind that the IOPS and latency values may be normalized if the snap interval is too long (60mins above) compared to per 5seconds or 10 minute snap interval. (see Appendix) r2toolkit [2] DBA_HIST_SNAPSHOT DBA_HIST_DATABASE_INSTANCE DBA_HIST_SYSSTAT DBA_HIST_SYSTEM_EVENT DBA_HIST_SYS_TIME_MODEL DBA_HIST_OSSTAT DBA_HIST_WR_CONTROL Y and X values that can be plotted for Linear Regression This is a performance toolkit that uses AWR data and Linear Regression to identify what metric/statistic is driving the database server’s workload. The data points can be very useful for capacity planning giving you informed decisions and completely avoiding guesswork! You can also do the same kind of mining with Statspack. Each DBA_HIST view has a counterpart Statspack view and you can achieve similar results DBA_HIST_SNAPSHOT = STATS$SNAPSHOT DBA_HIST_OSSTAT = STATS$OSSTAT
  • 9. DBA_HIST_SYS_TIME_MODEL = STATS$SYS_TIME_MODEL DBA_HIST_SYSSTAT = STATS$SYSSTAT The scripts mentioned are freely downloadable and more details on the math and performance formulas (rates, time, IOPS, CPU, latency, utilization, AAS) will be discovered when you look into the SQL code. I would also suggest that if you are serious on mining the AWR you must take time to play further with the DBA_HIST tables and the underlying data and you’ll appreciate that you have a better understanding on how the data are derived on the plain AWR report. PART 3 - Visualization Average Active Sessions (AAS) has become my default (golden) metric on finding the periods where the database could be having a bottleneck or just idle. Essentially AAS is the database load; this value should not go above the CPU count (NUM_CPUS in DBA_HIST_OSSTAT) and if it does then that means the database is working very hard or waiting a lot for something. Together, the AAS & CPU count is used as a yardstick for a possible performance problem [3]     If AAS < 1         ‐‐ Database is not blocked        AAS ~= 0         ‐‐ Database basically idle        ‐‐ Problems are in the APP not DB        AAS < # of CPUs        ‐‐ CPU available        ‐‐ Database is probably not blocked        ‐‐ Are any single sessions 100% active?        AAS > # of CPUs        ‐‐ Could have performance problems        AAS >> # of CPUS        ‐‐ There is a bottleneck  Just like a doctor, AAS could be your “stethoscope” when investigating performance problems but it doesn’t stop there. For it to be more useful you must be aware about the components of AAS much like drilling down on the time components and have this kind of data over a period of time (across SNAP_IDs). Well Enterprise Manager does this nice graphs on the “Performance and Top Activity page” and slicing the AAS components into different “Wait Classes” and it’s got a “Historical” view which you could go back and drill down on the past load activity. But what could be the problem?
  • 10. S I know so long AWR because th some othe So what could 1) U SN 2) O To be co SNAP_ID The imag there’s a componen ome of you h R retention p here was an i er issue where d be the alter Use the Top T NAP_IDs Or use the scri onsistent with D 335-339. No ge below is a big spike on nts. have encounte period (365 da instance shutd e Enterprise M rnative? imed Events pt together w h the initial e ote that the A stacked area n the database ered this Ent ays to exagge down betwee Manager reall SQL (awr_to with Perfsheet example we AAS during th awr_ chart of the e load… but erprise Mana erate it) but E n the date yo ly can’t just g opevents.sql) ! … a great to will focus on his period had _genwl.sql ou awr_topevent we want to ager error at Enterprise Ma ou want to go give you the v and focus on ool for ad-hoc n the same i d a sudden spi utput nts.sql using P know more some point. Y anager won’t o and the date visualization y the AAS and c performance interval time ike that is on t Perfsheet. It’s about it by d You are conf let you go ba e you are now you need. d wait class co e visualizatio 6:20 to 7:0 the range of 2 s clear from t drilling down figured with ack farther al w. Or could b olumns acros on [4] 1 AM that i 2.2 to 3.5 the image tha n on the AAS a ll e s s at S
  • 11. S Looking a know wh activity, it Some more ba On the E into differ From the ways to d 1) T 2) S AAS on t model. T DBA_HIS at the “textua hich AAS com t’s evident tha ackground nterprise Ma rent wait clas 2nd slide of K erive the valu Time Statistics ampling the Performa This is also ST_SYSTEM al trends” of a mponent is d at there’s a hi anager “Perfor ses. But, did y Kyle Hailey’s ue: s ance Page use what the sc M_EVENT a Stacke awr_topevent driving the w igh User IO a awr_to rmance” and you know tha s presentation es “Time Sta cript awr_top and the “CPU ed area chart o ts.sql output j workload of th activity. opevents.sql o “Top Activit at their data so n [3] on AAS atistics” and i pevents.sql is U” from tim of AAS just by lookin he database. output ty” Page you ources are dif (Average Ac is actually fr s doing… it me model vie ng at the AA For the part ’ll see the AA fferent? ctive Sessions rom v$system t unions the ew DBA_HIS S column we ticular SNAP AS compone s) it says that m_event + CP e output of ST_SYS_TIM e would easily P_IDs of high ents are sliced there are two PU from tim “events” on ME_MODEL y h d e n L
  • 12. S N and then f it look sim AAS valu “CPU use AAS on th on a 15 refresh to CPU from So what’s the On a high to Perform session (th think) tha Time Stat If you wa History of Now time for Finding th we can cr filter only the milar to the E ues will be cou ed by this sess he Top Activ 5sec refresh o Historical t m time model) e effect? h CPU activity mance Page he only way t an v$sysstat “ tistics (one of ant more info f Session Loa Perfsheet a l he AAS comp eate the same e top 5 and do Enterprise Ma unted. By the sion”. vity Page uses rate… but then it also st ). y period you . Simply bec to see CPU u “CPU used by f two ways to o about the d ad [5] and AA la Enterprise ponent that’s e visualization Stacke o this across th anager Perfor e way, on 10g s “Sampling” as I have tarts to behav ’ll notice that cause ASH s usage real tim y this session calculate AA etails around AS investigati Manager! driving the w n like the Ent ed area chart he SNAP_ID rmance Page g below the lo and by defau observed wh ve like the Pe t there will be samples every e) while the t n” there could AS) which cou d the Perform on [14] workload is a erprise Mana t AAS compo Ds but for grap I have to inc oad chart is co ult is taking a hen you sw erformance P e a higher AA y second and time model C d still be som uld be affecte mance and To a lot easier in ager broken do onents – wai phing purpose clude all of t oming from v advantage of A witch from age (pulls da AS on the To d it does tha CPU although me lag time an ed by average p Activity pa n graphics. Th own into “Wa it class es on the Perf the “events” v$system_eve ASH (sample the Real T ata from v$sy p Activity Pa at quickly on h it updates qu nd it will stil s. age this is wo he image belo ait Class”. fsheet to mak so that all th ent + v$syssta es) and does i Time 15 se ystem_event + age compared n every activ uicker (5secs ll be based on orth reading ow shows tha e e at it c + d e I n - at
  • 13. Even mor graphs. B is mostly Ooops, do uses could view and compare chart view Compare it’s on the Then com happening 1.6 on SN re, we have t elow is broke consuming th on’t get too ex d hide import see the data the above an w could tell a the wait clas e range of 0.1 mpare the wai g.. but on 3D NAP_ID 335 a the data now en down into he AAS. Stack xcited.. impor tant informati a clearly sepa nd below ch a more meanin ss chart… ab 1 (hidden bet it event char you can see and 336. Yes, in our contro “Wait Events ked area chart rtant reminde ion and somet arated into th harts, you’ll k ngful story. bove notice th tween CPU an rt… notice th that only the , you will also ol. So we cou s”, aside from t AAS compon er… the 2-dim times could b heir respective know what I he blue (Othe nd System IO he big differen db file sequ o not be foole uld play arou m being more ents – wait ev mensional Sta be misleading e component I mean.. Wa er wait class) O)… that’s a b nce on the ch ential read a ed when you und with the colorful it let vents acked area cha g [13] and it r ts, rather than ait Class and on the range big difference hart? above y and direct pa look at the ra data and crea t’s you see wh art that Enterp really helps to n being stack d Wait Event e of AAS of 1 e! you can’t real ath read are o aw data… but ate interesting hat wait even prise Manage o have anothe ked… As you ts in 3D area 1 while below lly tell what’ on the AAS o t visualization g nt er er u a w s of n
  • 14. A is much e AAS through On my te data. You SNAP_ID database. beyond m there you asier and the out the AWR st machine I u can see from D 335-339) ha You could a my maximum could use AS way to go bu 3 3D R retention pe have 365 day m the chart b appens to be also see the p CPU which SH, run the A ut you must be D area chart A D area chart AA eriod! ys retention p below (stacke the highest l period of shut could justify AWR report, ru e able to sens AAS componen AS component period. This e ed area chart oad period f tdowns (nega the drill dow un ADDM, o e and validate nts – wait clas ts – wait even enables me to t), that what from all the A ative value) a wn on the spe or make use o e if it’s drivin ss nts o have a data we are focus AAS samples and other tim ecific SNAP_ f your high ca ng you to bad warehouse of sing on (6:20 for the lifetim me period whe _IDs or time aliber scripts! d conclusions. f performanc 0 to 7:01 AM me of my tes ere AAS wen frame… from ! e M st nt m
  • 15. PAR U The good RT 4 - Capa Utilization is Capacity expected will fit in measurem and presen Measuring  H  E  E On the In explained Requirem Essentiall formula Utilization =  As shown water” an decision t into the s server cap much or i thing here is acity Plann the ultimate m planning pla and unexpec nto the availab ment [7]. Goo nt the in a mo g the workloa Have enough c Enable us to qu Enable us to qu ntroduction to d in detail wha ments, and U ly what we ca Requirements / C n on the imag nd “another p to purchase th erver. And o pacity. And w t could be the , you are not ning metric! ays a very im ted workload ble capacity o d thing the d ore meaningfu ad will give u capacity and n uantify the re uantify the be o Oracle Serv at information Utilization are most in C Capacity  ge below the pitcher with b he database s f course, the when this does e other way ar guessing! mportant role ds. The prima of the databa ata collection ul and useful us the followin not over buy esults of respo enefit of work er Consolidat n you need to Capacity Plann “empty pitch beer” are the erver that is t application r sn’t occur nic round where t to ensure pr ary principle se server. An n process is a manner. ng advantages onse time opti kload reductio tion paper [6 o get for you ning is the da her” represent Oracle work they define th requirement m cely, there can the capacity i roper resourc is to ensure nd with this w already being s and benefits imizations in on ] and Chapte to be able to atabase server ts the databas kload require he capacity. T may or may n be an exces is not enough es are availa the applicati we need to ha done by AW s [7]: the savings o er 9 of Craig define the Da r utilization a se server capa ements. Typic Then they sta not fit nicely s of capacity, h for the requi able and be a ion workload ave a facility WR. We just n of system reso Shallahamer’ atabase Serve and it is repre acity while th cally the IT s art pouring th y on the avail , which mean irements at ha able to handl d requirement y for workload need to extrac ources ’s book [8] h er’s Capacity esented by thi he “glass with shop makes he application lable databas ns IT spent too and. e s d ct e y, s h a s e o
  • 16. This simp presented Having th periods w ple and very u in a manner he data presen with high work useful concep that we can e nted this way kload requirem pt can be app asily abstract y, we can easi ments. plied as well i t the performa ily apply filte in AWR. Usi ance statistics er to the data ing the awr_g s to the Utiliz set and imm genwl.sql scr zation formula mediately find ript the data i a. d the workload s d
  • 17. C And we c AAS range        Per SNAP_ID            Oracle CPU U       OS CPU Utiliz       Particular Wo    AND TO_CHA  AND TO_CHA  AND TO_CHA  AND TO_CHA  AND s0.END_  AND s0.END_ CPU sizing re Having th The data server is a occurred. needed to The formu core need = # The data collocated can virtua ould do other aas > 1  or range of SNAP id in (336)  where id >= 3 Utilization  oracpupct > 5 zation  oscpupct > 50 orkload periods  AR(s0.END_INTERV AR(s0.END_INTERV AR(s0.END_INTERV AR(s0.END_INTERV _INTERVAL_TIME  _INTERVAL_TIME  ecommendati his data outpu points below a dual core m The manage handle the w ula used to de # of cores * utilizat points were d to a data cen alize it to a ne r filtering as w P_IDs  36 and  id <= 340  0  0  VAL_TIME,'D') >=  VAL_TIME,'D') <= 7 VAL_TIME,'HH24M VAL_TIME,'HH24M >= TO_DATE('2010 <= TO_DATE('2010 ions ut can be easil w came from a machine and b ement would workload of th erive the “CPU tion * 1.25  very useful nter, we could ewer hardware well… 1     ‐‐ Day of week 7  MI') >= 0900     ‐‐ H MI') <= 1800  0‐jan‐17 00:00:00 0‐aug‐22 23:59:59 y used as inp an actual pro been used for like to know he database. U core need” to character d opt to just u e. k: 1=Sunday 7=Sat Hour  ','yyyy‐mon‐dd hh 9','yyyy‐mon‐dd hh uts to CPU si oduction serve r almost 8 yea w what would [9] is as follo ize the curre upgrade to a n turday  h24:mi:ss')    ‐‐ Dat h24:mi:ss‘)  izing of a data er that needs ars and there d be the ideal ows: ent utilization newer model ta range  abase server. to be migrat e have been a l machine and n of the data but not the la ted to a new couple of ha d how many abase server. atest and the g machine. Th ardware error cores will b Since it wa greatest or w e s e s e
  • 18. S But notice summariz ignore the Validating a year. H process w affect the Storage sizing Having th e the outlier ( zing the data e outlier just l g with the app Having this in will run again overall conne g recommend his data outpu (shown in red will tell me t like that becau plication own nformation, w on the new se ected users. dations ut can be easil d above) repre that I’m most use there mig ner, she confi we can safely erver we just y used as inp esenting a SN t of the time ght be a critica irmed that it w remove the have to make uts to storage NAP period ha on the 10 %< al application was indeed an outlier from e sure that it’ e sizing of a d aving high CP < CPU utiliza n process on th n adhoc proce the data poi s being run o database serve PU utilization ation but we hat workload ess that is bei ints and even on an off-peak er. n. Statistically don’t want to d period. ing done onc n if the adho k period to no y o e c ot
  • 19. The data mentioned can be us measured Also take determine will help a For storag points below d above. This sed together w data easily tr note that the e the right sto a lot on the st ge sizing purp w came from s shows the I with a storag ransforms req re are other f orage for a pa torage decisio poses, I strong m awr_genw IOPS requirem e monitoring quirements to factors (bandw articular IO w ons. gly recommen wl.sql as wel ments needed tool to have capacity. width, through workload but nd using the a l, sizing sto d to run the d e a complete hput, service this can be y awr_iowl.sql rage for the database on t picture of IO time, etc.) th your starting same produ the new envir O performanc hat need to be point. Also b uction system ronment. Thi ce. Having th considered to benchmarking m s e o g
  • 20. Rea D al World Ex Diagnosing a The graph processing done any performan So it’s a plotted in was able visualizat On this im peaks are suspect or particular and OS s problem. If it weren This is the xample and Resolving h shown was g so it’s the m changes on t nce problem s sudden slow one graph… to apply the ion and I was mage above y e the particula r possible cul database ses statistics (CPU n’t for this vis e image after g GC Block L a sudden slo most critical w the database e so the tasks o down, and I that would a e things that s able to achie you can see t ar periods w lprit for the p ssions running U, memory, sualization th replacing the Lost ow down on a week of the m environment… f finding whe I was thinkin answer a lot o t I have lear eve what I hav the where, wh e are interest performance p g critical mod network) we he troubleshoo e network inte a client runni month. Interv … well that w ere/when/why ng… if I can of questions. ned. So I m ve envisioned hen, and why ted in. And w problem. Dril dules that are e were able c oting would h erconnect swi ing 2 nodes o viewing the D would be the y it went wron have time se Coming from made use of P d. y. Most of th what wait ev lling down fu e slow plus c conclude that have taken lon itch… this sh of RAC and DBA, he wou majority of th ng is all left to eries perform m Tanel Pode Perfsheet and he load is on vents are con urther on thos correlating it t it was a ne nger. ows their nor it’s a period ld insist that he customers o us. mance of both r’s seminar in d played aro the first node ntributing on se peak perio with the data etwork interco rmal workload of month end they have no s will say on h of the node n Singapore, ound with th e. And on th the peak is ods and on th abase advisor onnect switch d. d ot a s I e e a e s h
  • 21. LLinear Regres Mining th targeted re The graph 8core HS2 respective at >80% t On the dri high load componen when look reduction, If the serv seems to b ssion of AAS he AWR back esponse time h shown below 21 Bladeserve ely which sho the AAS also ill down show SQL greatly nt being utiliz king at the SQ , response tim ver’s workloa be low. Also Nod S and CPU on ked by solid s optimization w is a scatter er on a DS48 ows a strong c shoots up! wn below on t affecting the zed is on “CPU QL details on me optimizatio ad is on the you will notic de 1 n 2 node RAC statistical ana ns and worklo plot of a prod 00 SAN. Not correlation be the peak perio overall perfo U” hence you awr_topsqlx. on, and huge AAS value o ce the top SQ C alysis [10] [1 ad reduction. duction enviro tice the strong tween AAS v od with AAS ormance of th u will see larg . Tuning the h savings on sy of 2.2, the CP QL from AAS 1] [12] lets y onment with g correlation c vs. CPU utiliz value of 10 i e database. A ge LIOs and m high load SQL ystem resourc PU utilization of 10 is not t you do foreca 2 nodes of 11 coefficient (R zation. Also w it shows that t Also note that most of the el L will result t ces. n, latency, A there anymore Nod ast that can gu 1gR1 RAC ru R2) of .97 and when CPU sta the workload the large chu lapsed time sp to great work AAS compone e. de 2 uide you with unning on d .89 arts to queue is driven by unk of AAS pent on CPU kload ent on “CPU h ”
  • 22. Drill The perfo database s informed The toolk - CREAT - DROP - CREAT - POPUL - ANAL - POPUL - R2 REP ing down o 1) General W 2) Tablespa 3) Top Ti ormance toolk server’s work decisions and kit contains 7 TE USER - c TABLES - d TE THE r2 T LATE y data YZE r2 VAL LATE x and r PORT - gene on the peak Workload repor ace IO report med Events kit uses AWR kload based on d completely sections, see b reates the r2to drop the tables TABLES - cre - y data is the LUES - get the residual data rate the textu workload... rt R data and Lin n AAS. The d avoiding gue brief descript oolkit user s for a fresh s eate the main e "dependent e stat names w - x data is the ual report and . with AAS o near Regressio data points ca sswork! tion below: tart tables value", variab with high r2 v e "independen r2 values wit of 10 on to identify an be very use ble whose va values, to hav nt value", use th or w/o outl y what metric/ eful for capac lue is to be pr ve a more accu d to predict th liers /statistic is dri city planning g redicted urate analysis he value of y iving the giving you s
  • 23. Now 4) Top 20 6) Top 5 SQ w on the low 0 SQLs QLs of SNAP_ID w workload D 8631.. which b period… wi y the way got a ith AAS of 2 n AAS of 10 2.2
  • 24. Refe            1) Genera 2) Tables 3) Top Ti 4) Top 20 No entry – t 6) Top 5 SQ erences  [1] Craig  [2] r2proj  [3] Kyle H  [4] Tanel  [5] Histor  [6] Craig  [7] Andy  [8] Craig  [9] Husnu http://husn  [10] Forec  [11] Statis al Workload rep space IO report med Events 0 SQLs the top SQL fro QLs on SNAP_ID Shallahamer ect - http://ka Hailey Semin Poder – Perfs ry of session l Shallahamer Rivenes – Or Shallahamer u Sensoy - Da nusensoy.file casting Oracl stics Without port m AAS of 10 is D 8582 - Oracle Perf arlarao.tiddlys nar – AAS pre sheet http://w load - http://si - Introduction racle Workloa - Oracle Perf atabase Conso s.wordpress.c e Performanc t Tears not here anymo formance Fire spot.com/#r2p esentation www.tanelpod ites.google.co n To Oracle S ad Measurem formance Fire olidation Best com/2010/05/ ce ore efighting - Ch project der.com/files/P om/site/youvi Server Consol ment efighting - Ch t Practices /database-con hapter 1 PerfSheet.zip isualize/active lidation hapter 9 nsolidation-be p e-session-hist est-practices.p tory pdf
  • 25.     Ape  [12] Neer  [13] Neil http://arxi  [14] AAS  Other refe o ht o St o ht o ht endix - Ave The IO lat latency (ms) = The imag shorter s http://ww raj Bahatia – L l Gunther & iv.org/pdf/080 S investigation erences: ttp://karlarao. torage IOPS, ttp://karlarao. ttp://karlarao. erage Laten tency formula = (readtim / phy re ges below sho nap interval w.freelists.or Linear Regres Tanel Poder 09.2532 n http://goo.gl .wordpress.co capacity, per .tiddlyspot.co .tiddlyspot.co ncy Issue a used in AW eads) * 10  ow that latenc ls. Also rea g/post/oracle- ssion Paper r - Multidim l/5WaAg om rformance, co om/#Statistics om/#OraclePe WR is as follow cy values ma ad on this l -l/Disk-Devic mensional Vis ost - http://goo s erformance ws: ay be normali link for the ce-Busy-Wha sualization of o.gl/FCN0w ized if the sn e effects of at-exactly-is-t f Oracle Per nap interval i CPU sched this,7 rformance us is too long as duling issues sing Barry007 s compared to s on latency 7 o y