Monday, 15 September 2014

How to Recreate The AWR( AUTOMATIC WORK LOAD ) Repository

The best way to deinstall/install AWR is as follows:
1. Disable AWR statistics gathering by setting the statistics level to basic as follows:
Check settings for parameters as follows:
sqlplus /nolog
connect / as sysdba
show parameter cluster_database
show parameter statistics_level
show parameter sga_target

Standby MRP needs old log sequence even after restore of incremental backup at standby


At standby applied incremental backup but  MRP  process at standby is looking for very old sequence.

SQL>SELECT ARCH.THREAD# "Thread", ARCH.SEQUENCE# "Last Sequence Received", APPL.SEQUENCE# "Last Sequence Applied", (ARCH.SEQUENCE# - APPL.SEQUENCE#) "Difference" 
  FROM (SELECT THREAD# ,SEQUENCE# 
  FROM V$ARCHIVED_LOG 

Saturday, 7 June 2014

DBUA error database not in mounted state


 While  upgrading one of my 10.2.0.4 64-bit database to 11.2.0.2 using DBUA it failed  with retrieve db information  and pop up the message
"The Upgrade Assistant failes in bringing up the database XXX. Oracle Home /oracle/OraHome11203 obtained from file /etc/oratab was used to connect to the database.

How to copy schema stats from one schema to another schema


Here we will see  how to copy schema statistics from one schema to another. Basically there are two methods for doing this:
  • using DBMS_STATS or
  • using Data Pump
This is especially useful when doing large data transfers between either schemas or databases and statistics are needed fast. Remember that data density, row chaining or index cluster factor changed due to the data import and index rebuilds.

Method 1: Using DBMS_STATS
Extract the statistics
First we need to login as schema owner which from which we want to extract the statistics. 
In the follwing example the schema owner and schema is is “SCOTT”. Logged in as scott we create a table holding the statistic information:
exec dbms_stats.create_stat_table('SCOTT','STATISTICS');
The arguments required are: <SCHEMANAME>, <TABLENAME>.
To extract the statistics run:
begin
dbms_stats.export_schema_stats(ownname => 'SCOTT',stattab => 'STATISTICS');
end;
/

Transfer the statistics
Now all statistics from that particular schema are stored in the table named “STATISTICS”. The table must be transfered to the destination schema (in the same or another database). This can be done for instance with exp/imp or via a database link.
For exporting the statistics with export/import:
exp system/manager file=stats_table.dmp log=stats_table.log tables=SCOTT.STATISTICS
Importing is done with:
imp system/manager file=stats_table.dmp log=stats_table_imp.log
 fromuser=<source user name> touser=<destination user name>

Import the statistics
Import into another database but with the same schema name
If the schema name in the destination database is identical to the schema name in the source database (“SCOTT” in source and “SCOTT” in destination) the stats can be imported with:
begin
exec dbms_stats.import_schema_stats(ownname => 'SCOTT',stattab => 'STATISTICS');
 end;
 /

Import into another or the same database but with a different schema name
If the name of the destination schema is changed you have to adjust your statistic table before importing the stats. In the following example we import the stats into a schema called “TEST”.
In the stats table the column named “C5″ contains the name of the schema the statistics were exported from and will be imported to. If you want to import the stats into another schema you have to modify this column first:
update statistics set c5='TEST';
and afterwards import the statistics (loggen in as user TEST or SYS):
begin
exec dbms_stats.import_schema_stats(ownname => 'SCOTT',stattab => 'STATISTICS');
 end;
 /

Method 2: Using data pump
Beside using DBMS_STATS you can use data pump to transfer table and index statistics from one database to another.
When doint a normal export/import table and index statistics are transfered along with the data. If you want to transfer only the statistics you can use the following call:

impdp system/manager dumpfile=<directory>:<file> logfile=<directory>:<logfile name>  remap_schema=<source>:<destination> remap_tablespace=<source>:<destination> schemas=<name of source schema(s)> contents=STATISTICS



Sunday, 25 May 2014

Restoring Optimizer Statistics

 

In some cases we may find that gathering fresh statistics has led to the optimizer executing sub-optimal execution plans and we would like to restore the statistics as of a date when we had good performance.

Here we can  restore table statistics to a previous point in the past by using the DBMS_STATS.RESTORE_TABLE_STATS package.
We can check how far back in time we can go to restore statistics.
SQL> select DBMS_STATS.GET_STATS_HISTORY_AVAILABILITY  from dual;

GET_STATS_HISTORY_AVAILABILITY
---------------------------------------------------------------------------
13-MAR-14 10.51.37.266819000 PM +05:30

We can see what the retention period is for the statistics and can also alter the same. In this case we are changing the statistics retention from 10 days to 14 days. The default is 31 days.

SQL> select DBMS_STATS.GET_STATS_HISTORY_RETENTION from dual;

GET_STATS_HISTORY_RETENTION
---------------------------
                         10

SQL> execute DBMS_STATS.ALTER_STATS_HISTORY_RETENTION (14);

PL/SQL procedure successfully completed.

SQL> select DBMS_STATS.GET_STATS_HISTORY_RETENTION from dual;

GET_STATS_HISTORY_RETENTION
---------------------------
                         14

Let us now look at an example of restoring the statistics from a point in time from the past.

SQL> select count(*) from myobjects;

  COUNT(*)
----------
    138353

SQL> select TABLE_NAME, STATS_UPDATE_TIME from dba_tab_stats_history where table_name='MYOBJECTS' and owner='SYSTEM';

TABLE_NAME                     STATS_UPDATE_TIME
------------------------------ ----------------------------------------
MYOBJECTS                      18-MAR-14 10.00.19.496616 PM +05:30
MYOBJECTS                      23-MAR-14 11.29.10.526131 AM +05:30
MYOBJECTS                      23-MAR-14 11.35.47.249720 AM +05:30
MYOBJECTS                      23-MAR-14 11.37.36.050421 AM +05:30
MYOBJECTS                      23-MAR-14 11.38.05.015640 AM +05:30

The table MYOBJECTS has been analyzed several times in the past few days. Let us see what happens if we restore the statistics of the table gathered on the 18th of March.
SQL> execute dbms_stats.restore_table_stats(‘SYSTEM’,'MYOBJECTS’,’18-MAR-14 10.00.19.496616 PM +05:30′);
PL/SQL procedure successfully completed.

The table MYOBJECTS actually has 138353 rows, but the statistics were gathered at a time when it had much fewer rows as shown by the NUM_ROWS column of the DBA_TABLES view.

SQL> select num_rows from dba_tables
  2  where table_name='MYOBJECTS' and owner='SYSTEM';

  NUM_ROWS
----------
     46141

We can now replace these ‘older’ statistics with the most current statistics available in the history.

SQL> execute dbms_stats.restore_table_stats('SYSTEM','MYOBJECTS',’ 23-MAR-14 11.38.05.015640 AM +05:30’);

PL/SQL procedure successfully completed.

Now the NUM_ROWS column shows the row count which is the same as the actual number of rows in the table.
SQL> select num_rows from dba_tables
  2  where table_name='MYOBJECTS' and owner='SYSTEM';

  NUM_ROWS
----------
     138353

It should be noted that we can use the same procedure to not only restore previous statistics of just a table, but we can also do the same for the full schema or entire database as well.

REMEMBER – we gather statistics to ensure that the optimizer chooses the optimal execution plans, but gathering statistics invalidates the parsed representation of the SQL statement and reparsing the statement post gather stats can make the optimizer choose an execution plan which is different (and less optimised) than the original plan.


Refresh of Mview is Throwing ORA-00942


Refresh of Mview is throwing ORA-942 after successful creation.

Create materialized view schema_a.client_mview 
tablespace users build immediate
refresh force start with trunc(sysdate)+1455/1440
next trunc(sysdate)+1455/1440
as
select client_id, username, createdate, swver
from client_req@TEST_LINK
where swver is not null;

Materialized View Created.

select db_link, username from dba_db_links where db_link like 'TEST_LINK';

DB_LINK                      USERNAME
--------------------      ------------------------------
TEST_LINK.COM            SCHEMA_B

On the TEST_LINK.COM database, the db link user SCHEMA_B has select granted directly on the master tables.
select grantee,owner,table_name,privilege from user_tab_privs
where table_name like 'CLIENT%'

GRANTEE        OWNER      TABLE_NAME      PRIVILEGE
-------------     ------------     ------------------    ------------------
SCHEMA_B     SCHEMA_A    CLIENT_REQ     SELECT

Trying to refresh the materialized views returns errors:

SQL> execute dbms_refresh.refresh('"SCHEMA_A"."CLIENT_MVIEW"');
BEGIN dbms_refresh.refresh('"SCHEMA_A"."CLIENT_MVIEW"'); END;

*
ERROR at line 1:
ORA-12018: following error encountered during code generation for "SCHEMA_A"."CLIENT_MVIEW"
ORA-00942: table or view does not exist
ORA-06512: at "SYS.DBMS_SNAPSHOT", line 2255
ORA-06512: at "SYS.DBMS_SNAPSHOT", line 2461
ORA-06512: at "SYS.DBMS_IREFRESH", line 683
ORA-06512: at "SYS.DBMS_REFRESH", line 195
ORA-06512: at line 1

Cause
Database link user (SCHEMA_B) doesn't have select privileges on the MLOG$_CLIENT_REQ.
Log table is in the master table owner's schema (SCHEMA_A).
The problem was identified using the trace file.

Solution
To implement the solution, please execute the following steps:
grant select on MLOG$_<Table Name> to <Database link user>;
or
grant select any table to <Database link user>;

Example:
grant select on MLOG$_CLIENT_REQ to SCHEMA_B;
or
grant select any table to SCHEMA_B;



Saturday, 10 May 2014

LOG MINING IN ORACLE DATABASE


Suppose data in a table has been deleted. Audit trail was not enabled, therefore we do not have a clue of the user who has performed deletion and there are around 30 users that have DELETE rights on that table. Management want to know the name of the user, here we can use Oracle LOG MINING feature to filter out the transactions performed during that period.

Note: Make sure the Archive log must be enabled previously, if you want to use LOG Mining technique.

CONSIDERATIONS
Database : ORCL
Schema : SCOTT Table : STUDENTS
Date of Deletion : 10-MAY-2014

1. Gather Archived Log 
Make archived logs of 10-MAY-2014 available in your local hard disk. In my case it is already available at the Flash Recovery Area.

2 . Create Tablespace for Log Miner 
By default LOG MINER tables resides in SYSAUX tablespace, but it is efficient to keep it in a separate tablespace for easy manageability & maintenance.

SQLPLUS SYS@ORCL AS SYSDBA

CREATE TABLESPACE TS_LOGMNR DATAFILE ‘C:\ORACLE\PRODUCT\10.2.0\ORADATA\ORCL\TS_LOGMNR_01.DBF’ SIZE 25M AUTOEXTEND ON MAXSIZE UNLIMITED;

Use the following statement to move all of LOG MINER objects from SYSAUX to TS_LOGMNR tablespace.
 EXEC DBMS_LOGMNR_D.SET_TABLESPACE(TS_LOGMNR);

3) Start Log Mining Load Archive log file into Log Miner.
BEGIN DBMS_LOGMNR.ADD_LOGFILE(C:\ORACLE\PRODUCT\10.2.0\FLASH_RECOVERY_AREA\ORCLARCHIVELOG\2014_05_12O1_MF_1_2_7JY3ZNWV_.ARC, DBMS_LOGMNR.NEW);
 END;
/

Perform Log Mining 

BEGIN DBMS_LOGMNR.START_LOGMNR(OPTIONS=>DBMS_LOGMNR.DICT_FROM_ONLINE_CATALOG+ DBMS_LOGMNR.COMMITTED_DATA_ONLY);
 END;

Format query results.
SET TRIM ON SET LINES 200
COL USERNAME FORMAT A15
COL TIMESTAMP FORMAT A20
COL SESSION_INFO FORMAT A200

SPOOL C:LOGMNR.TXT
SELECT USERNAME, TO_CHAR(TIMESTAMP,’DD-MON-YYYYY HH24:MI:SS’) TIMESTAMP, SESSION_INFO, SQL_REDO, SQL_UNDO FROM V$LOGMNR_CONTENTS WHERE SEG_OWNER='SCOTT’ AND SEG_NAME=’STUDENTS’ AND OPERATION=’DELETE’;
SPOOL OFF;

Stop Log Miner.
BEGIN DBMS_LOGMNR.END_LOGMNR;
END;
/

Open C:LOGMNR.TXT and look for DELETE statements. If you do not locate the problematic query,repeat the step 2 (above) with another archive log file, and keep repeating it until you caught the query and theuser that has performed the DELETE operation.

Note: V$LOGMNR_CONTENTS has many columns, and you can customize your results by modifying the abovequery.

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