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http://www.orafaq.com/forum/m/120560/42800/?srch=cr_user_like#msg_120560

set pagesize 100
set heading off
set feedback off
select ‘create tablespace ‘ || df.tablespace_name || chr(10)
|| ‘ datafile ”’ || df.file_name || ”’ size ‘ || df.bytes
|| decode(autoextensible,’N',null, chr(10) || ‘ autoextend on maxsize ‘
|| maxbytes)
|| chr(10)
|| ‘default storage ( initial ‘ || initial_extent
|| decode (next_extent, null, null, ‘ next ‘ || next_extent )
|| ‘ minextents ‘ || min_extents
|| ‘ maxextents ‘ ||  decode(max_extents,’2147483645′,’unlimited’,max_extents)
|| ‘) ;’
from dba_data_files df, dba_tablespaces t
where df.tablespace_name=t.tablespace_name
/

•Before 10g you enabled DBMS_STATS to automatically gather statistics for a table by specifying the MONITORING keyword in the CREATE (or ALTER) TABLE statement. It is good to remember that starting with Oracle Database 10g, the MONITORING and NOMONITORING keywords have been deprecated and statistics are collected automatically. If you do specify these keywords, they are ignored.

•The job GATHER_STATS_JOB automatically gather optimizer statistics.

•This job gathers statistics on all objects in the database which have either

-Missing statistics or
-Stale statistics

•This job is created automatically at database creation time and is managed by the Scheduler. By default GATHER_STATS_JOB runs every night from 10 P.M. to 6 A.M. and all day on weekends if missing statistics or stale statistics found.

•In fact the Scheduler runs this job when the maintenance window is opened. By default, the maintenance window opens every night from 10 P.M. to 6 A.M. and all day on weekends.

•The stop_on_window_close attribute controls whether the GATHER_STATS_JOB continues when the maintenance window closes. The default setting for the stop_on_window_close attribute is TRUE, causing Scheduler to terminate GATHER_STATS_JOB when the maintenance window closes. The remaining objects are then processed in the next maintenance window.

•Database automatically collects statistics on database objects when the object has no previously gathered statistics or the existing statistics are stale because the underlying object has been modified significantly (more than 10% of the rows).

•If the parameter STATISTICS_LEVEL is set to TYPICAL or ALL then database automatically gather statistics for the objects which has stale statistics. If it is set to BASIC then then the automatic statistics gathering job is not able to detect stale statistics.

•To know about job GATHER_JOB_STATS issue the following query,

SQL>select JOB_TYPE,SCHEDULE_TYPE,START_DATE,REPEAT_INTERVAL,END_DATE,ENABLED,STATE,RUN_COUNT FROM DBA_SCHEDULER_JOBS WHERE JOB_NAME = ‘GATHER_STATS_JOB’;

JOB_TYPE SCHEDULE_TYP START_DATE REPEA END_DATE ENABL STATE RUN_COUNT
—————- ———— ———- —– ———- —– ——— ———-
WINDOW_GROUP TRUE SCHEDULED 31

To know the database creation date issue,

SQL> select created, sysdate from v$database;
CREATED SYSDATE
——— ———
06-MAY-08 12-JUN-08

So between May 06 and Jun 08 this job ran 31 times.

•In order to determine whether or not a given database object needs new database statistics, Oracle provides a table monitoring facility. If STATISTICS_LEVEL is set to TYPICAL or ALL then monitoring is enabled. Monitoring tracks the approximate number of INSERTs, UPDATEs, and DELETEs for that table, as well as whether the table has been truncated, since the last time statistics were gathered. The information about changes of tables can be viewed in the USER_TAB_MODIFICATIONS view.

Like you can query,

select TABLE_NAME,INSERTS,UPDATES,DELETES from USER_TAB_MODIFICATIONS;

•Following a data-modification, there may be a few minutes delay while Oracle propagates the information to this view. Use the DBMS_STATS.FLUSH_DATABASE_MONITORING_INFO procedure to immediately reflect the outstanding monitored information kept in the memory.

Example:
—————
SQL> insert into test values(‘hi’);
1 row created.

SQL> select TABLE_NAME,INSERTS,UPDATES,DELETES from USER_TAB_MODIFICATIONS where table_name=’TEST’;
no rows selected

SQL> exec DBMS_STATS.FLUSH_DATABASE_MONITORING_INFO;
PL/SQL procedure successfully completed.

SQL> select TABLE_NAME,INSERTS,UPDATES,DELETES from USER_TAB_MODIFICATIONS where table_name=’TEST’;
TABLE_NAME INSERTS UPDATES DELETES
—————————— ———- ———- ———-
TEST 1 0 0

After analyze they will disappear,
SQL> analyze table test estimate statistics;
Table analyzed.

SQL> select TABLE_NAME,INSERTS,UPDATES,DELETES from USER_TAB_MODIFICATIONS where table_name=’TEST’;
no rows selected

•If a monitored table has been modified more than 10%, then these statistics are considered stale and gathered again.

Source :  http://arjudba.blogspot.com/2008/06/automatic-statistics-gathering.html

$ORACLE_HOME/dbs — hc_<sid>.dat

HC stands for a health check monitoring. It contains information used to monitor the instance health, and to determine why it went down if the instance isn’t up. The file will be recreated at every instance startup. You don’t need to back it up.

$ORACLE_HOME/dbs — lk_<sid>

It’s a lock file which means that the Oracle shared memory segment is locked by a process or processes.if you shut down you db and this file still exists, you won’t be able to restart the db until the file is gone.And an Oracle process(s) is not releasing it’s lock on shared memory, not really normal behaviour if the file lock doesn’t clean up by itself, then you might have to run ipcs to see what s being held.

$ORACLE_HOME/dbs — snapcf_<sid>

Oracle takes snapshot and store it in snapcf_SID.f file.The faster way to restore control file is restoring from this snapshot than rman and cold backup restoration controlfile from this snap shot restore controlfile, restores the snapshot controlfile (all versions) restore controlfile from autobackup (9i and higher) takes the autobackup controlfile.

1.Install Oracle RDBMS Server Software on destination host.

2.Patch it to same release which is installed on source host.

3.Copy Datafile Backups , Archivelog Backups , Controlfile backup and spfile backup on to destination host ( test2 ) to same location as source host ( test1 )

4.Restore spfile from autobackup using following command.

$export ORACLE_SID=DEV
$export ORACLE_HOME=/apps1/oracle01/u11/app/oracle/product/10.2.0/db_1
$rman target / nocatalog
RMAN>set DBID=00000000 ( You can get DB ID for source db by querying v$database view )
RMAN>startup nomount;
RMAN>restore spfile from ‘/var/backups1/DEV/autobackup/2009_10_04/o1_mf_s_699336061_5dj3zg47_.bkp’;

Spfile will be restored in $ORACLE_HOME/dbs folder.

RMAN>shutdown immediate;
$sqlplus / as sysdba
SQL>create pfile from spfile; (pfile will be restored in $ORACLE_HOME/dbs folder.)

Open pfile ( initDEV.ora ) and modify adump,bdump,cdump,udump and db_recovery_file_dest parameter.Also modify control_files parameter according to new path.

$sqlplus / as sysdba
SQL>startup nomount pfile=’$ORACLE_HOME/dbs/initDEV.ora’
SQL>create spfile from pfile;
SQL>startup nomount force;

5.Restore controlfile from autobackup using following command.

$rman target / nocatalog
RMAN>set DBID=00000000
RMAN>restore controlfile from ‘/var/backups1/DEV/autobackup/2009_10_04/o1_mf_s_699336061_5dj3zg47_.bkp’;
RMAN>alter database mount;
6.Restore datafiles.

If the directory structure is different than you need to use “set newname” command to change file name location else its not required.

Create RMAN script for restoring DB.

RUN
{
SET NEWNAME FOR DATAFILE 1 TO ‘/apps1/DEV/system01.dbf’;
SET NEWNAME FOR DATAFILE 2 TO ‘/apps1/DEV/undotbs01.dbf’;
SET NEWNAME FOR DATAFILE 3 TO ‘/apps1/DEV/sysaux01.dbf’;
SET NEWNAME FOR DATAFILE 4 TO ‘/apps1/DEV/users01.dbf’;
SET NEWNAME FOR DATAFILE 5 TO ‘/apps1/DEV/cs_dev_owner_01.dbf’;
SET NEWNAME FOR DATAFILE 6 TO ‘/apps1/DEV/admin_01.dbf’;
SET UNTIL TIME  = “to_date(’2019-11-03:41:54:00′,’YYYY-MM-DD:HH24:MI:SS’)”;
RESTORE DATABASE;
SWITCH DATAFILE ALL;
}
EXIT

7.Recover database to point in time.

$rman target / nocatalog
RMAN>recover database until time “to_date(”2019-11-03:41:54:00”,’YYYY-MM-DD:HH24:MI:SS’)”;

8.Rename redo logfile name before opening DB with resetlogs option.

$sqlplus / as sysdba
SQL>alter database rename file ‘/apps1/u14/oradata/DEV/redo01a.log’ to ‘/apps1/DEV/redo01a.log’;

Do same for all the redo files.( run select member from v$logfile to get list of redo logs )

9.Open DB with resetlogs option.

$sqlplus / as sysdba
SQL>alter database open resetlogs;

10.Create TEMP tablespace.

$sqlplus / as sysdba
SQL>create temporary tablespace temp1 tempfile ‘/apps1/DEV/temp.dbf’ size 10M;
SQL>alter database default temporary tablespace temp1;

step 1 : Create procedure
=========================
create or replace procedure ssas_externalalertlog(in_instance in varchar2) as
path_bdump varchar2(4000);
name_alert varchar2(100) := 'alert_' || in_instance || '.log';
begin
select
value into path_bdump
from
sys.v_$parameter
where
name = 'background_dump_dest';

--select
--'alert_' || value || '.log' into name_alert
--from
--sys.v_$parameter
--where
--name = 'db_name';

execute immediate 'create or replace directory ssas_BDUMP as ''' ||
path_bdump || '''';
execute immediate
'create table ssas_ALERTLOG ' ||
' (MSG_line varchar2(4000) ) ' ||
' organization external ' ||
' (type oracle_loader ' ||
' default directory ssas_BDUMP ' ||
' access parameters ( ' ||
' records delimited by newline ' ||
' nobadfile ' ||
' nologfile ' ||
' nodiscardfile ' ||
' skip 0 ' ||
' READSIZE 1048576 ' ||
' FIELDS LDRTRIM ' ||
' REJECT ROWS WITH ALL NULL FIELDS ' ||
' (MSG_LINE (1:1000) CHAR(1000)) ' ||
' ) ' ||
' location (''' || name_alert || ''') )' ||
' reject limit unlimited ' ||
' noparallel nomonitoring ';
end;
/

step 2 : execute the procedure
==============================
execute ssas_externalalertlog('ORACLE_SID')

step 3 : issue this sql statement
=================================
col lineno noprint
col ora_error noprint
col msg_line format a132
set pages 0 lines 300 trimspool on trim on
alter session set nls_date_format='dd/mm/yyyy hh24:mi:ss';
alter session set sql_trace=false;
break on thedate
prompt
prompt ERROR IN ALERT LOG FILE - LAST 3 DAYS
prompt =====================================
select "LINENO","THEDATE","ORA_ERROR","MSG_LINE"
from (
select *
from (
select lineno,
msg_line,
thedate,
max( case when (ora_error like 'ORA-%' or ora_error like 'PLS-%')
then rtrim(substr(ora_error,1,instr(ora_error,' ')-1),':')
else null
end ) over (partition by thedate) ora_error
from (
select lineno,
msg_line,
max(thedate) over (order by lineno) thedate,
lead(msg_line) over (order by lineno) ora_error
from (
select rownum lineno,
substr( msg_line, 1, 132 ) msg_line,
case when msg_line like '___ ___ __ __:__:__ ____'
then to_date( msg_line, 'Dy Mon DD hh24:mi:ss yyyy' )
else null
end thedate
from ssas_alertlog
)
)
)
)
where ora_error is not null
and thedate >= (trunc(sysdate) - 3)
order by thedate
/

step 4 : drop the external table
================================
drop table ssas_alertlog
/

SELECT * FROM (
SELECT * FROM (
SELECT   TO_CHAR(FIRST_TIME, 'DD/MM') AS "DAY"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '00', 1, 0)), '99') "00:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '01', 1, 0)), '99') "01:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '02', 1, 0)), '99') "02:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '03', 1, 0)), '99') "03:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '04', 1, 0)), '99') "04:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '05', 1, 0)), '99') "05:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '06', 1, 0)), '99') "06:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '07', 1, 0)), '99') "07:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '08', 1, 0)), '99') "08:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '09', 1, 0)), '99') "09:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '10', 1, 0)), '99') "10:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '11', 1, 0)), '99') "11:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '12', 1, 0)), '99') "12:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '13', 1, 0)), '99') "13:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '14', 1, 0)), '99') "14:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '15', 1, 0)), '99') "15:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '16', 1, 0)), '99') "16:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '17', 1, 0)), '99') "17:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '18', 1, 0)), '99') "18:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '19', 1, 0)), '99') "19:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '20', 1, 0)), '99') "20:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '21', 1, 0)), '99') "21:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '22', 1, 0)), '99') "22:00"
       , TO_NUMBER(SUM(DECODE(TO_CHAR(FIRST_TIME, 'HH24'), '23', 1, 0)), '99') "23:00"
    FROM V$LOG_HISTORY
    WHERE extract(year FROM FIRST_TIME) = extract(year FROM sysdate)
GROUP BY TO_CHAR(FIRST_TIME, 'DD/MM')
) ORDER BY TO_DATE(extract(year FROM sysdate) || DAY, 'YYYY DD/MM') DESC
) WHERE ROWNUM < 8
/

SQL>create table dev as select rownum num from dual connect by rownum <= 1000000;
Check the size of table after its creating using following SQL.

col segment_name format a20
select segment_name
,      bytes “SIZE_BYTES”
,      ceil(bytes / 1024 / 1024) “SIZE_MB”
from   dba_segments

where  segment_name like ‘DEV’

/
SEGMENT_NAME         SIZE_BYTES    SIZE_MB
——————– ———- ———-
DEV                    12582912         12

A materialized view is a database object that contains the results of a query. They are local copies of data located remotely, or are used to create summary tables based on aggregations of a table’s data. A materialized view can query tables, views, and other materialized views. Collectively these are called master tables (a replication term) or detail tables (a data warehouse term).

For replication purposes, materialized views allow you to maintain copies of remote data on your local node. These copies are read-only. If you want to update the local copies, you have to use the Advanced Replication feature. You can select data from a materialized view as you would from a table or view.

Materialized views, which store data based on remote tables are also, know as snapshots.

Why Use Materialized Views?

You can use materialized views to achieve one or more of the following goals:

• Ease Network Loads
• Create a Mass Deployment Environment
• Enable Data Sub-setting
• Enable Disconnected Computing

Ease Network Loads If one of your goals is to reduce network loads, then you can use materialized views to distribute your corporate database to regional sites. Instead of the entire company accessing a single database server, user load is distributed across multiple database servers. Through the use of multi-tier materialized views, you can create materialized views based on other materialized views, which enables you to distribute user load to an even greater extent because clients can access materialized view sites instead of master sites. To decrease the amount of data that is replicated, a materialized view can be a subset of a master table or master materialized view.

In addition to not requiring a dedicated network connection, replicating data with materialized views increases data availability by providing local access to the target data. These benefits, combined with mass deployment and data sub-setting (both of which also reduce network loads), greatly enhance the performance and reliability of your replicated database.

Create a Mass Deployment Environment Deployment templates allow you to pre-create a materialized view environment locally. You can then use deployment templates to quickly and easily deploy materialized view environments to support sales force automation and other mass deployment environments. Parameters allow you to create custom data sets for individual users without changing the deployment template. This technology enables you to roll out a database infrastructure to hundreds or thousands of users.

Enable Data Sub-settingà Materialized views allow you to replicate data based on column- and row-level sub-setting, while multimaster replication requires replication of the entire table. Data sub-setting enables you to replicate information that pertains only to a particular site. For example, if you have a regional sales office, then you might replicate only the data that is needed in that region, thereby cutting down on unnecessary network traffic.

Enable Disconnected Computingà Materialized views do not require a dedicated network connection. Though you have the option of automating the refresh process by scheduling a job, you can manually refresh your materialized view on-demand, which is an ideal solution for sales applications running on a laptop. For example, a developer can integrate the replication management API for refresh on-demand into the sales application. When the salesperson has completed the day’s orders, the salesperson simply dials up the network and uses the integrated mechanism to refresh the database, thus transferring the orders to the main office.

Read-Only Materialized Views

You can make a materialized view read-only during creation by omitting the FOR UPDATE clause or disabling the equivalent option in the Replication Management tool. Read-only materialized views use many of the same mechanisms as updatable materialized views, except that they do not need to belong to a materialized view group. In addition, using read-only materialized views eliminates the possibility of a materialized view introducing data conflicts at the master site or master materialized view site, although this convenience means that updates cannot be made at the remote materialized view site. The following is an example of a read-only materialized view:

CREATE MATERIALIZED VIEW hr.employees
AS
SELECT * FROM hr.employees@orc1.world

Updatable Materialized Views

You can make a materialized view updatable during creation by including the FOR UPDATE clause or enabling the equivalent option in the Replication Management tool. For changes made to an updatable materialized view to be pushed back to the master during refresh, the updatable materialized view must belong to a materialized view group.Updatable materialized views enable you to decrease the load on master sites because users can make changes to the data at the materialized view site. The following is an example of an updatable materialized view:

CREATE MATERIALIZED VIEW hr.departments
FOR UPDATE AS
SELECT * FROM hr.departments@orc1.world;

Primary Key Materialized Views

The following statement creates the primary-key materialized view on the table emp located on a remote database.

CREATE MATERIALIZED VIEW mv_emp_pk
REFRESH FAST START WITH SYSDATE
NEXT SYSDATE + 1/48
WITH PRIMARY KEY
AS
SELECT * FROM emp@remote_db;

Note: When you create a materialized view using the FAST option you will need to create a view log on the master tables(s) as shown below:

CREATE MATERIALIZED VIEW LOG ON emp;

Rowid Materialized Views

The following statement creates the rowid materialized view on table emp located on a remote database:

CREATE MATERIALIZED VIEW mv_emp_rowid
REFRESH WITH ROWID
AS
SELECT * FROM emp@remote_db;

Subquery Materialized Views

The following statement creates a subquery materialized view based on the emp and dept tables located on the remote database:

CREATE MATERIALIZED VIEW mv_empdept
AS
SELECT *
FROM emp@remote_db e
WHERE EXISTS ( SELECT * FROM dept@remote_db d
WHERE e.dept_no = d.dept_no)

REFRESH CLAUSE

[refresh [fast|complete|force]
[on demand | commit]
[start with date] [next date]
[with {primary key|rowid}]]

The refresh option specifies:

• The refresh method used by Oracle to refresh data in materialized view
• Whether the view is primary key based or row-id based
• The time and interval at which the view is to be refreshed

Refresh Method - FAST Clause

The FAST refreshes use the materialized view logs (as seen above) to send the rows that have changed from master tables to the materialized view. You should create a materialized view log for the master tables if you specify the REFRESH FAST clause.

CREATE MATERIALIZED VIEW LOG ON emp;

Materialized views are not eligible for fast refresh if the defined subquery contains an analytic function.

Refresh Method – COMPLETE Clause

The complete refresh re-creates the entire materialized view. If you request a complete refresh, Oracle performs a complete refresh even if a fast refresh is possible.

Refresh Method – FORCE Clause

When you specify a FORCE clause, Oracle will perform a fast refresh if one is possible or a complete refresh otherwise. If you do not specify a refresh method (FAST, COMPLETE, or FORCE), FORCE is the default.

PRIMARY KEY and ROWID Clause

WITH PRIMARY KEY is used to create a primary key materialized view i.e. the materialized view is based on the primary key of the master table instead of ROWID (for ROWID clause). PRIMARY KEY is the default option. To use the PRIMARY KEY clause you should have defined PRIMARY KEY on the master table or else you should use ROWID based materialized views.

Primary key materialized views allow materialized view master tables to be reorganized without affecting the eligibility of the materialized view for fast refresh.

Rowid materialized views should have a single master table and cannot contain any of the following:

• Distinct or aggregate functions
• GROUP BY Subqueries , Joins & Set operations

Timing the refresh

The START WITH clause tells the database when to perform the first replication from the master table to the local base table. It should evaluate to a future point in time. The NEXT clause specifies the interval between refreshes

CREATE MATERIALIZED VIEW mv_emp_pk
REFRESH FAST
START WITH SYSDATE
NEXT SYSDATE + 2
WITH PRIMARY KEY
AS
SELECT * FROM emp@remote_db;

In the above example, the first copy of the materialized view is made at SYSDATE and the interval at which the refresh has to be performed is every two days.

(Sources www.oracle.com and www.databasejournal.com)

Prerequisite

1 : Before setting up a logical standby database, ensure the logical standby database can maintain the data types and tables in your primary database. See Appendix C of the dataguard documentation for a complete list of data type and storage type considerations.

2 : Ensure Table Rows in the Primary Database Can Be Uniquely Identified.

2.1 : Find Tables Without Unique Logical Identifier in the Primary Database.

Use following query to display a list of tables that SQL Apply may not be able to uniquely identify:

SQL>SELECT OWNER, TABLE_NAME FROM DBA_LOGSTDBY_NOT_UNIQUE WHERE (OWNER, TABLE_NAME) NOT IN (SELECT DISTINCT OWNER,TABLE_NAME FROM DBA_LOGSTDBY_UNSUPPORTED) AND BAD_COLUMN = ‘Y’;

2.2 : If your application ensures the rows in a table are unique, you can create a disabled primary key RELY constraint on the table. Use ALTER TABLE command to add a disabled primary-key RELY constraint.

The following example creates a disabled RELY constraint on a table named mytab, for which rows can be uniquely identified using the id and name columns:

SQL>ALTER TABLE mytab ADD PRIMARY KEY (id, name) RELY DISABLE;

Creating a Logical Standby Database:

Step 1 Create a Physical Standby Database

Create a Physical Standby Database and make sure that there is no error in remote archiving to Standby from Primary Database.

Step 2 Make Sure that Physical Standby is in Sync with Primary Database

Use following query on Standby to check:

SQL>SELECT MAX(AL.SEQUENCE#) "LAST SEQ RECEIVED", MAX(LH.SEQUENCE#) "LAST SEQ APPLIED" FROM V$ARCHIVED_LOG AL, V$LOG_HISTORY LH;

There should not be any difference in Last Seq Received and Last Seq Applied on Physical Standby.

Step 3 Stop Redo Apply on the Physical Standby Database

SQL> ALTER DATABASE RECOVER MANAGED STANDBY DATABASE CANCEL;

Step 4 Set Parameters for Logical Standby in Primary

4.1. Change VALID_FOR in LOG_ARCHIVE_DEST_1 on Primary to (ONLINE_LOGFILES,ALL_ROLES)

LOG_ARCHIVE_DEST_1= 'LOCATION=/u01/arch/online/ VALID_FOR=(ONLINE_LOGFILES,ALL_ROLES) DB_UNIQUE_NAME=prim1'

4.2. Set LOG_ARCHIVE_DEST_3 for logs which will received on Standby from Primary

LOG_ARCHIVE_DEST_3= 'LOCATION=/u01/arch/standby/ VALID_FOR=(STANDBY_LOGFILES,STANDBY_ROLE) DB_UNIQUE_NAME=prim1'
LOG_ARCHIVE_DEST_STATE_3=ENABLE

Note: LOG_ARCHIVE_DEST_3 only takes effect when the primary database is transitioned to the logical standby role.

Step 5 Build a Dictionary in the Redo Data on Primary Database

SQL> EXECUTE DBMS_LOGSTDBY.BUILD;

The DBMS_LOGSTDBY.BUILD procedure waits for all existing transactions to complete. Long-running transactions executed on the primary database will affect the timeliness of this command.

Step 6 Convert to a Logical Standby Database

SQL> ALTER DATABASE RECOVER TO LOGICAL STANDBY <db_name>;

For db_name, specify a database name to identify the new logical standby database. If you are using a spfile for standby, then command will update the db_name parameter otherwise it will issues a message reminding you to set the name of the DB_NAME parameter after shutting down the database.

Step 7 Create a New Password File for Logical Standby Database

$ORAPWD FILE=<filename> PASSWORD=<password> ENTRIES=<max_users>

This step is required in 10.2 only and should not be performed in 11g.

Step 8 Shutdown and Startup Logical Standby Database in Mount Stage

SQL> SHUTDOWN;
SQL> STARTUP MOUNT;

Step 9 Adjust Initialization Parameter on Logical Standby Database

LOG_ARCHIVE_DEST_1= 'LOCATION=/u01/arch/online/ VALID_FOR=(ONLINE_LOGFILES,ALL_ROLES) DB_UNIQUE_NAME=logstd1'
LOG_ARCHIVE_DEST_2= 'SERVICE=prim1 LGWR ASYNC VALID_FOR=(ONLINE_LOGFILES,PRIMARY_ROLE) DB_UNIQUE_NAME=prim1'
LOG_ARCHIVE_DEST_3= 'LOCATION=/u01/arch/standby/ VALID_FOR=(STANDBY_LOGFILES,STANDBY_ROLE) DB_UNIQUE_NAME=logstd1'
LOG_ARCHIVE_DEST_STATE_1=ENABLE
LOG_ARCHIVE_DEST_STATE_2=ENABLE
LOG_ARCHIVE_DEST_STATE_3=ENABLE

Step 10 Open the Logical Standby Database

SQL> ALTER DATABASE OPEN RESETLOGS;

Step 11 Start Logical Apply on Standby

SQL> ALTER DATABASE START LOGICAL STANDBY APPLY IMMEDIATE;