engel - resource consumption of oracle data guard
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Data Guard Performance Issues
(Cover your Assets with Data Guard)
Carel-Jan Engel
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Carel-Jan Engel
Company: DBA!ert
In IT since 1982
Using Oracle since May, 1985
Member of the Oaktable Network
email: cjpengel.dbalert@xs4all.nl
Introduction – who am I ?
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Agenda
Data Guard architectureHA AlternativesData Guard performance Test environmentResultsQ & A
Testhardware: courtesy of
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Data Guard Architecture
Redundant Hardware
Redo
Archiving
Recovery
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Data Guard Architecture
StandbyPrimary
redo
LGWR
standby redo
Oracle NetRFS
ARCH
MRP
archivesarchives
ARCH
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Data Guard Architecture
Oracle NetStandbyPrimary
redo
LGWR
standby redo
RFS
ARCH
MRP
archivesarchives
ARCH
FAL Oracle Net
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Data Guard Architecture
StandbyPrimary
redo
LGWR
standby redo
RFS
ARCH
MRP
archivesarchives
ARCH
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Data Guard benefits
Disaster Recovery
Natural or humanoid
High Availability
Switchover allows HW maintenance
Guaranteed data protection
Synchronous transfer, shutdown if no standby available
Ease of administration
GUI, CLI
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Data Guard benefits
Data Protection Flexibility
3 protection modes to tailor to your needs
Light footprint
Not too heavy transaction penalty
Extra functionality
Read-only standby for reporting
Resource Maximization
Move backup, reporting to standby
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Data Guard Requirements
Enterprise Edition license
On both ends
Any Oracle supported platform
But: same OS/OS level, same Oracle version
Archive Log Mode
Identical directory structure recommended
FORCE_LOGGING recommended
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Data Guard / HA alternatives
RAC
Redundant instances
Single database - SPOF
Complementary
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Data Guard / HA alternatives
Mirroring (storage)
Mostly asynchronous
Far from fine granularity
block/track level mirroring
much superfluous changes transferred
redo (2x), arch (2x), control (3x), database
Large bandwidth required
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Data Guard / HA alternatives
Quest’s Shareplex
3rd party
supports cross-platform, cross version
expensive
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Data Guard Performance
Performance affected by
redo log volume
log transport
network latency
network throughput
LOG_ARCHIVE_DEST_n settings
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LGWR SYNC PARALLEL
StandbyPrimary
redo
LGWR
standby redo
Oracle NetRFS
ARCH
MRP
archivesarchives
ARCH
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LGWR ASYNC
StandbyPrimary
redo
LGWR
standby redo
RFS
ARCH
MRP
archivesarchives
ARCH
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LGWR SYNC PARALLEL AFFIRM
StandbyPrimary
redo
LGWR
standby redo
Oracle NetRFS
ARCH
MRP
archivesarchives
ARCH
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LOG_ARCHIVE_DEST_n settings
ARCH LGWRLOCATION / SERVICE X XMANDATORY / OPTIONAL X XSYNC / ASYNC X(NO)AFFIRM X(NO)PARALLEL SYNCNET_TIMEOUT ASYNC > 0
SYNC=PARALLEL
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Test harness
reproducible testruns
statistics gathering
logfile gathering
long running jobs
parameterized scenarios
unattended
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Test harness
rc.d concept
execute init, run and exit jobs ordered by name
extended with default settings
init
cleanup, create schema, tablespaces, set parameters, start
databases in correct mode
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Test harness
runkick off the load generation jobs
exit
export perfstat data, schema data
backup alert and trace files
backup load-logging
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Test harness
load-generation with dbaman - James Morle
whitepaper: ‘brewing benchmarks’ - www.oaktable.org
tcl-based extended shell
oci-calls available
controlcenter randomizing ‘think time’ for parallel sessions
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Performance testing
OLTP
order-entry:
5 processes
order creation
order extension
order delivery
invoicing
payment
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Performance testing
order creation
create an order
create 1-10 order lines
64 processes
order extension
extend 25% of the orders
extend to 18 order lines
10 processes
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Performance testing
order delivery
update delivery date
16 processes
invoicing
invoice delivered orders
6 processes
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Performance testing
payment
create payments
amount 25 - 75 % (random), until full payment
4 processes
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Performance testing
OLTP
many small, scattered transactions
100 processes
delays to ‘age-out’ buffers from cache
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Performance testing
OLTP
0.5 hour runs
42824 orders (23 / second) (correct paper, p7!)
258335 orderlines (143 / second)
4329 invoices
1301 payments
25 MB redo / min ==> 1.5 GB/hr:
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Performance testing
No performance degradation measurable.
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Performance testing
OLTP - No performance degradation
System:
1 x Pentium 3.0 GHz/HT
2 disks: 1x 10,000 RP/M, 1x 15,000 RPM
100 Mb Network can keep up easily with the disks
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Performance testing
Batchruns4 parallel sessions:
create table t as select * from all_objects;delete from t;rollback;delete from t;drop table t;
run 100 timesmeasure time
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Scenarios
Per run
70 logswitches (+/- 1)
1762 MB redolog
detailed statistics
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Scenarios
Per run
12 scenarios
One single-server, base-line
10 LGWR, various options
1 ARCH
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Ramdisk redo
Avoiding disk-contention
For re-runnable batches only
Can speed things up quite well,
especially in NOARCHIVELOG mode
Take care, data lost after crash
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Results
Per run
redo size 1762 MB
(7 GB / hour)
70 - 71 logswitches
running appr. 15 minutes
~ 1.9 MB redo / second
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Run1, Redo on Ramdisk, 100Mb0 NONE 1
1 PERF LGWR SYNC NOAFFIRM NOPARALLEL 1.23
2 AVAIL LGWR SYNC AFFIRM NOPARALLEL 1.17
3 PROT LGWR SYNC AFFIRM NOPARALLEL 1.22
4 PERF LGWR SYNC NOAFFIRM PARALLEL 1.21
5 AVAIL LGWR SYNC AFFIRM PARALLEL 1.21
6 PROT LGWR SYNC AFFIRM PARALLEL 1.23
7 PERF LGWR ASYNC 50 1.06
8 PERF LGWR ASYNC 100 1.21
9 PERF LGWR ASYNC 200 1.03
10 PERF LGWR ASYNC 400 1.04
11 PERF ARCH 1.05
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Run2, Redo on Harddisk, 100Mb0 NONE 1
1 PERF LGWR SYNC NOAFFIRM NOPARALLEL 0.98
2 AVAIL LGWR SYNC AFFIRM NOPARALLEL 1.27
3 PROT LGWR SYNC AFFIRM NOPARALLEL 1.23
4 PERF LGWR SYNC NOAFFIRM PARALLEL 1.21
5 AVAIL LGWR SYNC AFFIRM PARALLEL 1.19
6 PROT LGWR SYNC AFFIRM PARALLEL 1.22
7 PERF LGWR ASYNC 50 1.21
8 PERF LGWR ASYNC 100 1.07
9 PERF LGWR ASYNC 200 1.12
10 PERF LGWR ASYNC 400 1.09
11 PERF ARCH 1.18
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Run3, Redo on Harddisk, 1Gb0 NONE 1
1 PERF LGWR SYNC NOAFFIRM NOPARALLEL 1.10
2 AVAIL LGWR SYNC AFFIRM NOPARALLEL 1.10
3 PROT LGWR SYNC AFFIRM NOPARALLEL 1.11
4 PERF LGWR SYNC NOAFFIRM PARALLEL 1.07
5 AVAIL LGWR SYNC AFFIRM PARALLEL 1.05
6 PROT LGWR SYNC AFFIRM PARALLEL 1.00
7 PERF LGWR ASYNC 50 0.98
8 PERF LGWR ASYNC 100 1.01
9 PERF LGWR ASYNC 200 1.03
10 PERF LGWR ASYNC 400 1.04
11 PERF ARCH 1.07
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Conclusions
Data Guard slows down a system saturated with batchload
Maximum performance loss in heavy batchload: ~ 27 %
(Relatively) small system with OLTP
No effect from Data Guard measurable:
Speeds vary, 2% slower - 2% faster, results unreliable
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Conclusions
Experience in day-to-day implementations
No significant performance problems during normal work
Large data loads: trade off between either slow run or
detached standby run followed by Instantiation.
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