Data Guard Redo Apply and Media Recovery Best Practices 10gR2

Data Guard Redo Apply and
Media Recovery Best Practices
Oracle Database 10g Release 2
Oracle Maximum Availability Architecture White Paper
September 2007
Maximum
Availability
Architecture
Oracle Best Practices for High Availability
Maximum Availability Architecture
Data Guard Redo Apply and
Media Recovery Best Practices
Oracle Database 10g Release 2
Introduction ....................................................................................................... 2
Executive Summary .......................................................................................... 2
Data Guard Redo Apply and Media Recovery Best Practices.................... 3
Assessing Media Recovery Performance ....................................................... 4
Tuning Media Recovery ................................................................................... 6
Collect Data Necessary for Tuning............................................................ 7
Assess System Resources............................................................................. 9
Assess Database Waits ............................................................................... 10
Tuning Case Studies........................................................................................ 11
Enabling Block Checking............................................................................... 14
Conclusion........................................................................................................ 14
Data Guard Redo Apply and Media Recovery Best Practices: Oracle Database 10g Release 2
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Maximum Availability Architecture
Data Guard Redo Apply and
Media Recovery Best Practices
Oracle Database 10g Release 2
INTRODUCTION
Oracle media recovery is a fundamental element of Maximum Availability
Architecture (MAA) environments. Media recovery occurs when one or more
datafiles or the controlfiles are restored from a previous backup or when using
Data Guard Redo Apply (physical standby database). The goal of media recovery is
to recover a database to a consistent point in time or to apply all primary database
transactions to a physical standby database.
In most cases, the default Oracle settings result in satisfactory performance for
media recovery. As applications and databases increase in size and throughput,
however, media recovery operations can benefit from additional tuning to further
optimize recovery time or Redo Apply throughput on a standby database. The goal
of this paper is to provide best practices for monitoring media recovery
performance and, if necessary, for tuning media recovery for optimal performance.
EXECUTIVE SUMMARY
Based on MAA test results and customer experiences, the following list describes
the results obtained after adopting the best practices outlined in this paper:
•
The redo apply rate for the Oracle Internal Mail Database (supporting
65,000 active users) increased from 8 megabytes per second (MB/sec) to 38
MB/sec.
•
The redo apply rate on a physical standby database for a customer
workload consisting of batch processing of online transaction processing
(OLTP) transactions was observed to be over 25MB/sec.
•
The recovery performance in MAA tests for OLTP workload is affected
most by I/O bandwidth. For example, doubling the number of spindles
increased recovery rates by over 100%.
•
In contrast, media recovery performance in MAA tests using direct load
operations did not display the same benefits from increasing the I/O
bandwidth. For example, direct load operations sustained 38MB/sec
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Maximum Availability Architecture
recovery rate using 28 spindles. Reducing the spindle count by half had
little effect on the recovery rate.
•
For additional protection against data corruption at the standby database,
the impact of setting DB_BLOCK_CHECKSUM to FULL was
approximately 1% for an OLTP primary workload and approximately 3%
for a direct path primary workload.
DATA GUARD REDO APPLY AND MEDIA RECOVERY BEST
PRACTICES
The best practices outlined in this paper have been derived as a result of testing
media recovery on Oracle Database 10g Release 2 in the Oracle Maximum
Availability Architecture (MAA) lab. In addition to Oracle MAA testing, this paper
also utilizes results obtained by Oracle customers who have optimized media
recovery in their environments.
Oracle recommends the following best practices for improving the performance of
media recovery:
•
Allow media recovery to control the number of processes for parallel
media recovery. By default, media recovery uses the CPU_COUNT
initialization parameter to determine the number of processes to use for
recovery operations.
•
Configure PARALLEL_EXECUTION_MESSAGE_SIZE = 65535. The
message size parameter is used by all parallel query operations and pulls
memory from the shared pool. Therefore, when increasing
PARALLEL_EXECUTION_MESSAGE_SIZE (PEMS) consider the
amount of available shared pool memory. Note that 64k is the maximum
value for a non-Oracle RAC database. For an Oracle RAC database, you
should continue to set PEMS to 64k but be aware that the actual value
might be automatically lowered to the IPC limit for the OS.
•
The overall recovery rate can be significantly impacted by enabling
DB_BLOCK_CHECKING. Setting DB_BLOCK_CHECKING=FALSE
during media recovery can provide as much as a two fold increase in the
apply rate. The lack of block checking during recovery must be an accepted
risk. Block checking is recommended for the production database.
•
Tune the I/O subsystem. The most important factor in obtaining high
recovery rates is tuning the I/O subsystem. When tuning I/O for media
recovery:
o Ensure that Oracle can use ASYNC I/O. Note that, by default,
the Oracle database is configured for asynchronous I/O.
However, you must also properly configure the operating system,
the host bus adapter (HBA) driver, and storage array. Consult
your operating system and storage array documentation for
further information on enabling ASYNC I/O.
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o
Maximize the I/O write size through all layers of the I/O stack.
The layers will include one or more of the following: operating
system (including async write size), device drivers, storage
network transfer size, and disk array. Consult your operating
system and storage array documentation for further information
on enabling ASYNC I/O tuning I/O write sizes. Media recovery
issues 1MB read I/O to the redo log.
o
Set the initialization parameter DISK_ASYNCH_IO=TRUE
(default). If asynchronous I/O is not available, consider using the
DBWR_IO_SLAVES parameter to simulate asynchronous I/O.
o
Set the DB_WRITER_PROCESSES parameter to a value greater
than 1 when asynchronous I/O is available and free buffer waits or
checkpoint completed wait events are the top Oracle waits. Multiple
database writers are only applicable if you have sufficient CPU
and I/O bandwidth.
o
If you continue to receive high “free buffer wait” as a significant
database wait event in V$SYSTEM_EVENT after implementing
the above recommendation, then consider increasing the buffer
cache.
o
Increase the size of the primary database’s online redo log and
standby database’s standby redo logs to reduce the number of
times a full checkpoint is performed.
o
Place online redo logs and standby redo logs in ASM diskgroups
with the best performance characteristics.
•
Query the V$RECOVERY_PROGRESS view to monitor and assess
recovery performance in real time.
•
Query the V$SYSTEM_EVENT view to monitor and assess database wait
events that might lead to recovery optimizations.
ASSESSING MEDIA RECOVERY PERFORMANCE
The first step in any tuning exercise is to assess the current performance and use
that as a baseline. As changes are made, reassess and compare the performance
level to the baseline to get a level of improvement. Monitor the performance of
media recovery by querying the V$RECOVERY_PROGRESS view. This view
contains the following columns:
Average Apply Rate: Redo Applied / Elapsed Time includes time spent
actively applying redo and time spent waiting for redo to arrive.
Active Apply Rate: Redo Applied / Active Time is a moving average
over the last 3 minutes. The rate does not include time spent waiting for
redo to arrive.
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Apply Time per Log: Average time spent actively applying redo in a log
file.
Checkpoint Time per Log: Average time spent for a log boundary
checkpoint.
Last Applied Redo: SCN and Timestamp of last redo applied. This is the
time as stored in the redo stream, so it can be used to compare where the
standby database is relative to the primary.
Note that the Average Apply Rate (includes the) time waiting for redo to arrive.
This can falsely indicate an apply rate that is much lower than the actual apply rate.
To get a true assessment, you may wish to stop media recovery, allow several
archive logs to accumulate, and then start media recovery. By doing so, you
remove the idle time from the average apply rate and get a much more accurate
picture of the true apply rate
In a Data Guard physical standby environment, it is important to determine if the
standby database can recover redo as fast as, or faster than, the primary database
can generate redo. The simplest way to determine application throughput in terms
of redo volume is to collect Automatic Workload Repository (AWR) reports on the
primary database during normal and peak workload and determine the number of
bytes per second of redo data the production database is producing. You can then
compare the speed at which redo is being generated with the Average Apply Rate
or Active Apply Rate to determine if the standby database is able to maintain the
pace.
While using AWR reports is an effective method of comparing application
throughput and recovery rates over a defined period of time, it is possible to get an
instantaneous view of redo generate rate and recovery rates using V$SYSSTAT.
On the primary database take two snapshots (P1 and P2) of the “redo blocks
written” statistic from the V$SYSSTAT view separated by an interval of time (T).
The instantaneous primary redo generation rate can be derived as:
(P2 - P1)/T
On the standby database, take two snapshots (S1 and S2) of the “redo blocks read
for recovery” statistic from the V$SYSSTAT view at the same interval of time (T)
as above. The instantaneous apply rate can be derived as:
(S2 - S1)/T
To determine if media recovery tuning is required, use the redo apply rate quick
assessment chart below.
Table 1: Redo Apply Rate Quick Assessment
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Redo Generation Rate vs Redo Apply
Rate
Assessment and Recommendation
2 * Max Primary Database Redo
Generation Rate < Redo Apply Rate
Excellent – No tuning required with
plenty of room for future growth
Max Primary Database Redo Generation
Rate < Redo Apply Rate
Good – Tuning is Optional
Average Primary Redo Generation Rate
< Redo Apply Rate
OK – Could benefit from tuning in
order to accommodate peaks in
workload
Average Primary Redo Generation Rate
> Redo Apply Rate
Bad - Needs tuning. Call Oracle
Technical Support if all tuning steps
have been followed and the redo
apply rate is still too slow. Refer to
the Tuning Media Recovery section.
The recovery rate may vary depending on the primary database’s transaction
activity. Typically, recovery rate is much higher when the number of distinct blocks
being changed is small or during batch processing because both cases result in less
I/O either because of the number of changed blocks or because of coalescing
blocks in a single I/O. In most applications, a predictable pattern surfaces after
monitoring for several days.
TUNING MEDIA RECOVERY
The physical standby database or a recovery instance is unlike the primary database.
While the typical primary instance may be comprised of 95% or more query activity
with many CPU intensive operations, the media recovery instance is very write and
update intensive. The recovery instance’s goal is to apply changes to data blocks
and write them to the data files. In many cases, the media recovery instance
requires much less overall CPU resources but equal or greater I/O or memory
capacity. Instead of possibly hundreds of CPU intensive operations on the primary,
only the recovery coordinator (PID of the foreground process in V$PROCESS) or
MRP process (MRP0 PID found in V$MANAGED_STANDBY) is generally CPU
intensive. In many cases, fewer but faster CPUs will typically enhance recovery
performance. There is no simple formula to predict the standby database system
utilization. Here are some general observations found during MAA testing.
•
The higher the read ratio on the primary database, the greater the
difference in CPU utilization between the primary and standby databases.
•
Higher numbers of sorts or complex queries executed will require more
CPU utilization on the primary database. Queries and sorts do not create
additional redo and thus do not create additional work on the standby
database.
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•
If the recovery set or the number of distinct blocks that are being
modified during recovery is small, you may utilize less CPU resources and
also get higher Redo Apply rates because the blocks are usually cached and
applying redo is more optimized. For example, the SQL*Loader runs had
a relatively small recovery set compared to our OLTP runs; thereby the
redo apply rate was higher and CPU consumption was 30% less. .
Therefore, tuning media recovery focuses primarily on removing system resource
contention and database wait constraints.
Use the following methodology if your monitoring of the media recovery indicates
that tuning is required. Media recovery consists of three distinct phases. Each phase
must be assessed and tuned if the recovery rate is not sufficient.
1.
Log Read Phase involves the reading of redo from the standby redo logs
or archived redo logs by the recovery coordinator or Managed Recovery
Process (MRP).
2.
Redo Apply Phase involves the reading of data blocks into the buffer
cache and the application of redo, by parallel recovery slave processes. The
recovery coordinator (or MRP) ships redo to the recovery slaves using the
parallel query (PQ) interprocess communication framework.
3.
Checkpoint Phase involves database writer (DBWR) flushing to disk
modified (dirty) data blocks and the update of data file headers to record
checkpoint completion.
It is important to understand that in a Data Guard Redo Apply configuration with
an Oracle RAC standby database, media recovery will always execute on a single
instance in the cluster, called the apply instance. In addition, when using the Data
Guard Broker with an Oracle RAC standby database, a surviving instance
automatically assumes the role of the apply instance should the original apply
instance fail. The first step in tuning media recovery is to follow the best practices
outlined in the beginning of this paper. If after implementing best practices your
monitoring of media recovery indicates that performance still requires
improvement, conduct additional tuning using the following methodology:
o
Collect data necessary for tuning
o
Assess system resources
o
Assess database waits
Collect Data Necessary for Tuning
To perform accurate recovery tuning, set Timed_Statistics=TRUE on the primary
and standby databases and collect the following information during the recovery
session:
•
Output from the operating system (OS) sar command, which was invoked
with a 60-second interval from the primary and standby databases
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•
Output from the OS vmstat command for the recovery period for the
standby database
•
AWR reports from the primary database
•
Output from the following query from V$SYSSTAT run on a 60-second
interval on the standby database:
select name, value, to_char(sysdate, 'DD-MON-YYYY HH:MI:SS')
from v$sysstat where value > 0 order by name;
spool off
•
Output from the following query from V$SYSTEM_EVENT run on a 60second interval on the standby database:
set echo off
set feedback off
set termout off
set pagesize 100
set numwidth 10
column event format a40 truncate
column name format a35 truncate
column opname format a35 truncate
column value format 99999999999999
select event, total_waits, time_waited,
average_wait*10
from v$system_event where time_waited > 100 and
event not like 'rdbms ipc %' and event not like
'%timer%'and lower(event) not like '%idle%'
and lower(event) not like 'sql%net%'
and event not like 'ges%'
order by time_waited;
•
Output from the following query on V$RECOVERY_PROGRESS run
once at the completion of the media recovery operation on the standby:
set echo off
set feedback off
set termout off
set pagesize 100
set numwidth 15
column type format a20 truncate
column item format a25 truncate
column units format a10 truncate
column name format a30 truncate
select to_char(start_time,'dd-mon-yyyy HH:MI:SS')
start_time, type, item, units, sofar, total,
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Maximum Availability Architecture
to_char(timestamp,'dd-mon-yyyy HH:MI:SS') timestamp from
v$recovery_progress;
Assess System Resources
Use system commands such as UNIX sar and vmstat or system monitoring tools to
assess system resources.
•
If there are I/O bottlenecks or excessive wait I/Os, then stripe across
more spindles/devices or leverage more controllers. A stripe size between
256KB to 1MB is optimal to leverage your I/O subsystem. Verify that this
is not a bus or controller bottleneck or any other I/O bottleneck. The read
I/O from the standby redo log should be greater than the expected
recovery rate.
•
Assess I/O read rates from standby redo logs or archived redo logs
ALTER SYSTEM DUMP LOGFILE ‘redo log name’ VALIDATE;
A trace file is generated with the redo read rate from a recovery
perspective. The overall recovery rate will always be bounded by the rate at
which redo can be read; so ensure that the redo read rate surpasses your
required recovery rate. The following UNIX example shows how to
measure the maximum redo read rate for recovery. Oracle uses a 4 MB
read buffer for redo log reads.1
% /bin/time dd if=/redo_logs/t_log8.f of=/dev/null bs=4096k
50+1 records in
50+1 records out
real 6.4
user 0.0
sys 0.1
Estimated Read Rate (200 MB log file) = (50 * 4 MB) / 6.4s = 31.25
MB/sec
•
Check for excessive swapping or memory paging.
•
Check to ensure the recovery coordinator or MRP is not CPU bound
during recovery.
•
If excessive CPU is being used, consider removing non-database CPU
resource consuming programs off the system and setting
DB_BLOCK_CHECKING to lower values.
1 If you repeat this simple test, use a different SRL or archive log since the data may be
cached making the results artificially high and incorrect.
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Assess Database Waits
•
Database wait events from V$SYSTEM_EVENTS and V$SESSION_WAITS
Refer to the top 10 system wait events and tune the biggest waits
first. You can determine the top system and session wait events
by querying v$session_wait and v$system_event and taking
the top waits with the largest “TIME_WAITED” value
o
If recovery is applying a lot of redo efficiently, the system will be
I/O bound and the I/O wait should be reasonable for your
system. The following are the top recovery-related waits that you
may observe. Only apply the tuning tips if the recovery events are
in the top 10 waits.
Table 2: Key Wait Event Table
Wait Name
Description
Tuning Tips
Log File Sequential
Reads
Coordinator (recovery session
or MRP process) wait for log
file read I/O.
Tune Log Read I/O
PX Deq: Par Recov
Reply
Coordinator synchronous wait
for Slave (wait for checkpoints)
Increase PARALLEL
EXECUTION MESSAGE
SIZE to 65535
PX Deq Credit: send
blkd
Coordinator streaming wait for
Slave (wait for apply)
Increase PARALLEL
EXECUTION MESSAGE
SIZE to 65535
Free buffer waits
Foreground waiting available
free buffer in the buffer cache
Increase DB CACHE SIZE
and remove any KEEP or
RECYCLE POOL settings.
Direct path read
Coordinator wait for file
header read at log boundary
checkpoint
Tune File Read I/O
Direct path write
Coordinator wait for file
header write at log boundary
checkpoint
Tune File Write I/O
Checkpoint completed
Wait for checkpoint completed
Tune File Write I/O
PX Deq Credit: need
buffer
Increase number of DB
WRITER PROCESSES
db file parallel read
Wait for data block read
Tune File Read I/O
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Maximum Availability Architecture
TUNING CASE STUDIES
The following section provides examples of the potential benefits of tuning for
media recovery performance. In this example, following the tuning
recommendations in this paper produced the following performance gains:
Test
Run
Redo
Volume
Recovered
Seconds for
Media
Recovery to
complete
recovery
MB of Redo
applied/second
(Redo Apply
Rate)
Percentage
improvement
on baseline
Baseline
8723 MB
1290 sec
6.7 MB/sec
n/a - baseline
Recovery
Tuning
8723 MB
1134 sec
7.7 MB/sec
14%
Recovery
+ I/O
Tuning
8723 MB
1009 sec
8.6 MB/sec
28%
Details for this tuning example are as follows:
The hardware used in this exampled consisted of the following:
Host:
•
•
•
Sun V65x with 2 3.0Ghz CPU’s (4 hyper threaded)
6 GB of main memory
Red Hat Enterprise Linux AS release 4 (Nahant Update 3) (2.6.9-34.ELsmp)
Storage:
• EMC CX700 for Data Area (two test with 14 and 28 spindles)
• EMC CX500 for Flash Recovery Area (two test with 14 and 28 spindles)
• ASM used for both Data Area and Flash Recovery Area
Database:
• RDBMS 10.2.0.2
• 2.4 GB SGA
o 1.7 GB buffer cache
• 4 redo log groups of 1 GB each
• 2 members per group
• 2 controlfiles
• UNDO tablespace
• Flashback Database
Application used to generate redo
• 250 Warehouse Database TPCC for OLTP
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Flashback Database was enabled and a guaranteed restore point was created before
starting the test. The TPCC workload was run generating 8.7GB of OLTP data. To
test recovery performance, the database was flashed back to the restore point, and
media recovery was used to apply the archived logs generated in the original run. A
script was used that performed the following:
1.
Flashback Database to a beginning restore point
2.
Recover 8.7 GB of OLTP load (TPCC application)
3.
Gather statistics
The first recovery run was performed prior to performing any tuning. At the end
of the recovery run the apply rate was obtained using the
V$RECOVERY_PROGRESS view.
ITEM
=================
Log Files
Active Apply Rate
Average Apply Rate
Redo Applied
Active Time
Apply Time per Log
Checkpoint Time per
Elapsed Time
UNIT
=========
Files
KB/sec
KB/sec
Megabytes
Seconds
Seconds
Seconds
Seconds
TOTAL
=======
9
6038
7006
8723
946
86
18
1290
Looking at the top wait events in the V$SYSTEM_EVENT view for the initial
recovery run we see:
EVENT
===========================
db file sequential read
control file parallel write
recovery read
checkpoint completed
db file parallel write
PX Deq Credit: need buffer
PX Deq: Test for msg
PX Deq Credit: send blkd
TOTAL_WAITS
===========
17285
447
68648
125
7314
5320
90053
2496
TIME_WAIT
=========
38
171
191
392
514
766
1003
2224
From the above we see that the top wait events are centered on messaging between
the parallel query slaves and coordinator. To make the message passing more
efficient we can increase the PARALLEL_EXECUTION_MESSAGE_SIZE from
the default of 2k to 64k. After making the parameter change a flashback to the
restore point was performed and the test was re-run. The following illustrates the
new recovery rate:
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ITEM
=================
Log Files
Active Apply Rate
Average Apply Rate
Redo Applied
Active Time
Apply Time per Log
Checkpoint Time per
Elapsed Time
UNIT
=========
Files
KB/sec
KB/sec
Megabytes
Seconds
Seconds
Seconds
Seconds
TOTAL
=======
9
7690
7916
8723
823
86
18
1134
We see an increase in over 13% increase as a result of our change. Looking at the
top wait events we see the following:
EVENT
===========================
PX qref latch
PX Deq Credit: need buffer
control file parallel write
PX Deq Credit: send blkd
checkpoint completed
db file parallel write
PX Deq: Par Recov Reply
PX Deq: Test for msg
recovery read
TOTAL_WAITS
===========
145151
17285
447
68648
125
7314
5320
90053
2496
TIME_WAIT
=========
28
38
171
191
374
517
666
903
2627
The “recovery read” wait event is the amount of time needed to perform reads
from the log files in the flash recovery area. In general, when the database is tuned
optimally, the top wait events will be I/O related. From this point we can attempt
to further optimize the I/O sub system. In this environment the following changes
were made at the OS kernel level to assure that the I/O rate was optimal:
fs.aio-max-nr = 1048576
fs.aio-max-pinned = 1671168
After making the changes, the workload was run once again. The recovery rate
increased as follows:
ITEM
=================
Log Files
Active Apply Rate
Average Apply Rate
Redo Applied
Active Time
Apply Time per Log
Checkpoint Time per
Elapsed Time
UNIT
=========
Files
KB/sec
KB/sec
Megabytes
Seconds
Seconds
Seconds
Seconds
Data Guard Redo Apply and Media Recovery Best Practices: Oracle Database 10g Release 2
TOTAL
=======
9
8634
8852
8723
724
86
15
1009
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Maximum Availability Architecture
ENABLING BLOCK CHECKING
By default, the Oracle database always validates the data blocks that it reads from
disk. Enabling data and log block checksums by setting DB_BLOCK_CHECKSUM to
TYPICAL enables Oracle to detect other types of corruption caused by underlying
disks, storage systems, or I/O systems. Before a data block is written to disk, a
checksum is computed and stored in the block. When the block is subsequently
read from disk, the checksum is computed again and compared with the stored
checksum. Any difference is treated as a media error.
With DB_BLOCK_CHECKING enabled, the Oracle Database verifies that the
block is self-consistent by executing block-type specific logical checks after every
change. If the block is inconsistent, then it is marked corrupt, an ORA-1578 error
is returned, and a trace file is created containing details of the problem. Without
block checking enabled, corruption can go undetected until a subsequent change
discovers the inconsistency.
In the MAA lab, testing showed the following impact of enabling block checking:
•
The impact of setting DB_BLOCK_CHECKING to MEDIUM, or
FULL was approximately 80% for OLTP.
•
The impact of setting DB_BLOCK_CHECKING to MEDIUM, or
FULL was approximately 15% for direct path operations.
CONCLUSION
With Oracle Database 10g Release 2, you should be able to inherently achieve fast
media recovery performance. The best practices described in this white paper
provide a checklist you can use to ensure that media recovery is not being
constrained by any bottlenecks. Optimized media recovery reduces the time
required for Data Guard switchover, failovers, or database media recovery. This
equates to more uptime and higher availability in the case of an unplanned or
planned outage, which helps enterprises meet the Service Level Agreements
associated with recovery time objectives.
Data Guard Redo Apply and Media Recovery Best Practices: Oracle Database 10g Release 2
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Data Guard Redo Apply and Media Recovery Best Practices:
Oracle Database 10g Release 2
September 2007
Author: Michael Smith
Contributing Authors: Lawrence To, Joseph Meeks, Vinay Srihari
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