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Saturday, December 11, 2010

Oracle 10g Database New Features

Oracle 10g Database New Features



Simplicity vs Flexibility


        Automatic statistics gathering
        Advisories
        Automatic tuning
        Less than 30 basic (init.ora) parameters
       Basic, advanced, hidden parameters
        Easier operations
       alter tablespace rename
       flashback queries
       “undrop” table


Manageability

        SGA_TARGET
       Sets total size for all SGA components
       Buffer Cache, Shared Pool, Large Pool, Java Pool
       Dynamically and automatically adjustable
       Automatic changes persist in SPFILE
        PGA_AGGREGATE_TARGET
       Available since 9i
       Sets total size target for all server processes
       sort_area_size, sort_area_retained_size,
hash_area_size, bitmap_merge_area_size
       Contents automatically managed



Basic Parameters

COMPATIBLE
CONTROL_FILES
DB_BLOCK_SIZE
DB_CREATE_FILE_DEST
DB_CREATE_ONLINE_LOG_DEST
DB_DOMAIN
DB_NAME
DB_RECOVERY_FILE_DEST
DB_RECOVERY_FILE_DEST_SIZE
INSTANCE_NUMBER
JOB_QUEUE_PROCESSES
LOG_ARCHIVE_DEST_n
LOG_ARCHIVE_DEST_STATE_n
NLS_LANGUAGE
NLS_TERRITORY
OPEN_CURSORS
PROCESSES
REMOTE_LISTENER
REMOTE_LOGIN_PASSWORDFILE
ROLLBACK_SEGMENTS
SESSIONS
SHARED_SERVERS
STAR_TRANSFORMATION_ENABLED
UNDO_MANAGEMENT
UNDO_TABLESPACE



Rename Tablespace


        Useful in Transportable Tablespace scenarios
        ALTER TABLESPACE prod RENAME to arc1;
       Can’t rename SYSTEM or SYSAUX
       Tablespace and all datafiles must be online
       Can also rename READ ONLY tablespaces

Bigfile Tablespaces


        Support for sizes up to 8 Exabytes!
       8 000 000 Terabytes
       Max 65535 files in database
       SYSTEM & SYSAUX can’t be bigfile tablespaces


Crossplatform Transportable TS


RMAN> CONVERT TABLESPACE sales_1,sales_2
2> TO PLATFORM ’Microsoft Windows NT’
3> FORMAT ’/temp/%U’;
...
Transporting Tablespaces Between Databases
input datafile fno=00004 name=/u01/oracle/oradata/salesdb/sales_101.dbf
converted datafile=/temp/data_D-10_I-3295731590_TS-EXAMPLE_FNO-4_06ek24vl
channel ORA_DISK_1: datafile conversion complete, elapsed time: 00:00:45



Data Pump


        A server-managed data transportation tool
        Direct load/extract capabilities
        Very high performance/efficient with large data sets
        Replacement for exp/imp
       old exp/imp remain supported


        Commands expdp/impdp
        Can use files or direct network transfer
        Dynamic configuration, resumable operations
        Client can detach and reconnect
        Can be parallelized using PARALLEL
       Even loads to/from external text files
       Parallelization level can be changed on the fly for long running jobs
        Monitored through DBA_DATAPUMP_JOBS
        Fine-Grained Object Selection
       exclude=function
       exclude=procedure
       exclude=package:”like ‘PAYROLL%’ ”
       include=table
       content=metadata_only | data_only | both
       query=“modify_date > sysdate-1”
        DDL Transformations, DDL extract


FlashBack Database

        Flash Recovery Area must be configured
       Flashback logs are stored there
       Consisting of old database block images
       Fast “rollback” of database, no redologs  required


FlashBack Database

Configuration parameters:
        DB_RECOVERY_FILE_DEST
        DB_RECOVERY_FILE_DEST_SIZE
        DB_FLASHBACK_RETENTION_TARGET
Commands:
        ALTER DATABASE FLASHBACK ON;
        ALTER DATABASE FLASHBACK OFF;
        ALTER TABLESPACE test1 FLASHBACK OFF;
        ALTER TABLESPACE test1 FLASHBACK ON;



Flashback Row History


SELECT versions_xid XID, versions_startscn START_SCN,
versions_endscn END_SCN, versions_operation OPERATION,
empname, salary FROM hr.employees_demo
VERSIONS BETWEEN SCN MINVALUE AND MAXVALUE
where empno = 111;
XID START_SCN END_SCN OPERATION EMPNAME SALARY
--- --------- ------- --------- ------- ------
0004000700000058 113855        I Tom  927
000200030000002D 113564        D Mike 555
000200030000002E 112670 113564 I Mike 555
3 rows selected
        Useful for auditing


Flashback Transaction History


select xid, start_scn, commit_scn, operation,
undo_sql, table_name
from dba_transaction_query where xid = ’000200030000002D’;
XID START_SCN COMMIT_SCN OPERATION UNDO_SQL
--- --------- ---------- --------- -------------------------
000200030000002D 112670 113565 D insert into "SCOTT"."EMP"
("EMPNO","EMPNAME","SALARY") values ('111','Mike','655')

000200030000002D 112670 113565 I delete from "SCOTT"."DEPT"
where "DEPTNO" = '20' and "DEPTNAME" = 'Finance'

000200030000002D 112670 113565 D update “SCOTT”.”EMP”
set “SALARY” = ‘555’ where “EMPNO” = ‘111’ and ”EMPNAME” = ‘Mike’ and “SALARY”
= ‘655’
3 rows selected


Table Recovery using Flashback


        DROP TABLE X;
       Table is renamed internally, not dropped
       Indexes & other structures remain
       Table is purged when out of free space or quota
        SELECT * FROM RECYCLEBIN;
       Systemwide recyclebin DBA_RECYCLEBIN
       Or show recyclebin command in sqlplus
        FLASHBACK TABLE RB$$3560$TABLE$1
TO BEFORE DROP RENAME TO scott.emp;
        PURGE RECYCLEBIN;
        DROP TABLE X PURGE;


Performance Tuning


        RBO is dead, long live the CBO!
       Even data dictionary, SYS tables using CBO
       However, RBO is gone nowhere, it’s available
        Optimizer able to use run-time statistics
       exec dbms_stats.gather_system_statistics(…)
       OPTIMIZER_DYNAMIC_SAMPLING (default: 2)
        Multiple Advisors
       SQL Access & Tuning Advisor
       Memory Advisors (SGA, Shared Pool, etc..)
       Segment Advisor (Fragmentation, etc..)
       Undo Advisor

Performance Troubleshooting


        Automatic Workload Repository
       Runtime execution statistics are gathered in memory
       MMON background process flushes stats to disk
        V$SQL_BIND_CAPTURE
       Samples bind variables for all sessions
       Faster than sql_trace (10046 trace on level 4)
       But doesn’t capture all variable types
       And doesn’t capture occurences of bindings
        _cursor_bind_capture_interval defaults to 900 seconds
       Good for getting samples of database operations



SQLPLUS Changes


Improvements
        SPOOL CREATE | REPLACE | APPEND
       also works for SAVE command
        SHOW RECYCLE BIN
        SQLPROMPT runtime variable substitution
       SET SQLPROMPT "_USER'@'_CONNECT_IDENTIFIER >"
        glogin.sql and login.sql scripts are executed also on CONNECT



Other


        dbms_scheduler
       calendar Expressions: Yearly, Monthly, Weekly, Daily, Hourly, Minutely, Secondely
        alter system flush buffer_cache;
        drop database;
       database must be closed
       mounted exclusively
       restricted
        default user tablespace
       specifies default tablespace for new users, similar to default temporary tablespace in 9i

* NYOUG General Meeting March 2004

Tuesday, December 7, 2010

Oracle 10g application server installation steps




A Black screen will appear (Dos) and perform some checks e.g. Display colors, swap/ Page file space

Note: your OS (Windows) Page File size must be Greater then 1535. if not then increase it by  Right Click on my computer - properties - Advance
Under Performance tab click Settings – Advance – Change
Change maximum Size value to 1550
Press set and ok.








Press Next







give location (PATH) where to Install









Click Ok







Select Language.








keep this option to Automatic and press Next.











Specify SMTP outgoing mail server if you have , else dont do any think and Leave it BLANK












Instance_name              iasora
Ias_admin password     abce12345
Confirm password        abce12345

Note: you may write password as u wish.













Click on Install














When Installation Ends Press Exit. 














to open Oracle Application Server Control 
on your Browser type
http://machine-name:18100


where machine-name is the name of your computer










Thursday, December 2, 2010

Setting Up iSQL*Plus for SYSDBA Access



>>>>>>>>CMD<<<<<<<<



Microsoft Windows XP [Version 5.1.2600]
(C) Copyright 1985-2001 Microsoft Corp.

C:\Documents and Settings\orasoft>d:

D:\>set oracle_home=d:\oracle\product\10.2.0\db_1

D:\>set java_home=%oracle_home%\jdk

D:\>set oracle_home
oracle_home=d:\oracle\product\10.2.0\db_1

D:\>set java_home
java_home=d:\oracle\product\10.2.0\db_1\jdk

D:\>cd %oracle_home%\oc4j\j2ee\isqlplus\application-deployments\isqlplus

D:\oracle\product\10.2.0\db_1\oc4j\j2ee\isqlplus\application-deployments\isqlplu
s>

%java_home%\bin\java -Djava.security.properties=%oracle_home%\oc4j\j2ee\home\c
onfig\jazn.security.props -jar %oracle_home%\oc4j\j2ee\home\jazn.jar -user "iSQL
*Plus DBA/admin" -password welcome -shell



JAZN:> adduser "iSQL*Plus DBA" orasoft orasoft
JAZN:> grantrole webDba "iSQL*Plus DBA" orasoft
JAZN:> exit
JAZN:>


D:\oracle\product\10.2.0\db_1\oc4j\j2ee\isqlplus\application-deployments\isqlplu
s>exit


now type following URL or your browser

http://pc-name:port_number/isqlplus/dba


to get your host name type following query on SQL Prompt

select host_name from v$instance;

to get Port number check in file .

oracle_home\install\portlist.ini

Wednesday, December 1, 2010

Statspack

Installing Statspack

The statspack feature should be installed by running the following SQL scripts as the SYS user:

$ORACLE_HOME/rdbms/admin/spcreate.sql

run from sqlplus as follows:

SQL> @?/rdbms/admin/spcreate.sql

Note: the symbol “?” means Oracle_home

The script will install the statspack schema owned by a new user called PERFSTAT.  The script will ask you to supply the PERFSTAT user’s password, default tablespace and temporary tablespace.

The default tablespace is the tablespace that shall be used to store the statspack schema tables.  It is therefore recommended to create a new tablespace for this purpose before running the spcreate.sql script.

Running Statspack

A statspack snapshot is taken by running the following procedure as the PERFSTAT user:

Sql> Execute statspack.snap;

Snapshots can also be run using different levels of information.  Level 5 is the default level; however sometimes level 7 as this will give additional information regarding I/O performance.  For example:

SQL> Execute statspack.snap(i_snap_level => 7);

The following table details what other snap levels are available:

SNAP LEVEL
Definition
0
This level captures general statistics, including rollback segment, row cache, SGA, system events, background events, session events, system statistics, wait statistics, lock statistics, and Latch information.
5
This level includes capturing high resource usage SQL Statements, along with all data captured by lower levels.
6
This level includes capturing SQL plan and SQL plan usage information for high resource usage SQL Statements, along with all data captured by lower levels.
7
This level captures segment level statistics, including logical and physical reads, row lock, itl and buffer busy waits, along with all data captured by lower levels.
10
This level includes capturing Child Latch statistics, along with all data captured by lower levels.

For storing general performance information it is common to run the statspack.snap (default level of 5) process via a background job every hour. 

However, when investigating a specific performance problem this may not be frequent enough.  For example imagine that it takes you 1 hour to complete a 5 mile trip.  This may sound fairly reasonable until further analysis shows that 45 minutes of the trip was spent driving down a 1 mile strip of road where you had to stop at 7 traffic lights.  Obviously this 1 mile was a big bottleneck to the journey and if an alternative quicker route could be taken this would sufficiently cut down the overall travel time.

Therefore when investigating a specific performance issue more frequent snapshots may be required to capture where the bottlenecks are taking place; Personally if I was monitoring a task which took 1 hour to complete I would take snapshots at least once every 15 minutes.

If you want to gather more frequent (less than an hour) statspack reports on an on-going basis it may be advisable to run a level 0 snapshot.  For example for a general idea of on-going performance levels you should be able to run a level 0 snapshot every 15 minutes via a background job without causing much of an overhead to general Oracle resources.

 

Generating Statspack Reports

Statspack reports are generated by running the script spreport.sql as the PERFSTAT user as follows:

SQL> @?/rdbms/admin/spreport.sql

The report will you provide a list of available snapshots with a relevant id and time of the snapshot.

You will be asked to enter a snapshot id for the starting point of the report, snapshot id for the ending point of the report as well as the name of the report.

The script will then generate a file, based on the provided inputs, containing the statspack report.

Analysing Wait Events

Oracle performance is based on the formula:

Response Time = Service Time + Wait Time

Service Time is the value of “CPU used by this session” from the statspack report; this is calculated using the formula:

Service Time = CPU Parse + CPU Recursive + CPU Other

CPU Parse is the value of “parse time cpu” from the statspack report.

CPU Recursive is the value of “recursive cpu usage” from the statspack report.

Therefore CPU Other is calculated using the formula:

Service Time – CPU Parse – CPU Recursive

The following statspack statistics are measured in centiseconds (one hundredth of a second) - which is apparently also how long it takes for a stroke of lightning to strike:

Statistic
Example Value
CPU used by this session
1,150,887
parse time cpu
18,975
Recursive cpu usage
535,372

From Oracle 9i the “%Total Elapsed Time” from the “Top 5 Timed Wait Events” section of the statspack report is a direct % of Response Time.


Top 5 Timed Wait Events

Event
Waits
Time (s)
% Total Elapsed Time
wait for unread message on broadcast channel
24,457
24,603
52.90
CPU time

11,509
24.74
Db file sequential read
2,013,123
3,045
6.55
Library cache load lock
1,889
1,833
3.94
ARCH wait on SENDREQ
6,570
1,683
3.62

The CPU time in the top 5 timed wait events equates to Service Time.

CPU Other (using the above example values) = 596,540 cs

CPU time can be broken down further using the calculation:

%CPU Statistic = CPU Statistic / Service Time * %Total Elapsed CPU Time

For example:

Of the 24.74% total elapsed time spent waiting on CPU time:

% CPU Other        = 596,540 cs   / 1,150,887 cs  x  24.74 % = 12.82%
% CPU Parse        = 18,975 cs     / 1,150,887 cs  x   24.74 % = 0.41%
% CPU Recursive = 535,372 cs   / 1,150,887 cs  x   24.74 % = 11.51%

Although the majority (52.90%) of the overall wait times is on “wait for unread message on broadcast channel”; this is actually an idle event and as such is unlikely to cause any performance issues.  So the next significant values to investigate are CPU Other and CPU Recursive.

 Identifying Problem Areas from the Wait Event Data

CPU Other

If % CPU Other value is significant the next step would be to look in the SQL ordered by Gets section of the statspack report to find queries with a high number of buffer gets (logical I/Os) and identify candidates for tuning.

CPU Parse

If % CPU Parse value is significant, this can be caused by cursors being repeatedly opened and closed every time they are executed instead of being opened once, kept open for multiple executions and only closed when they are no longer required.  The SQL ordered by Parse Calls section of the statspack report can help identify such cursors.

CPU Recursive

A significantly high % CPU Recursive value is caused by Oracle performing Recursive calls, this can be defined as follows:

Sometimes, to execute a SQL statement, the Oracle Server must issue additional statements.  Such Statements are called recursive calls or recursive SQL statements.  For example, if you insert a row into a table that does not have enough space to hold that row, the Oracle Server makes recursive calls to allocate the space dynamically if dictionary managed tablespaces are being used.

Recursive calls are also generated due to the unavailability of dictionary info in the dictionary cache, firing of database triggers, execution of DDL, execution of SQL within PL/SQL blocks, functions or stored procedures and enforcement of referential integrity constraints.

Probably a good starting point for tackling a significant % CPU Recursive value is to look in SQL ordered by Gets section of the statspack report to find queries with a high number of buffer gets (logical I/Os) and identify candidates for tuning.

Also look in the Dictionary Cache Stats section of the statspack report to check how efficiently the Dictionary Cache is being utilised.

Disk I/O related waits

If there is a significantly high value of disk related wait events (e.g. db file scattered read or db file sequential read) then check the SQL ordered by Reads section of the statspack report to find queries performing the most reads from disk and identify candidates for tuning.

There are also two sections that provide an analysis of how the underlying file systems are performing; these are “Tablespace IO Stats for DB” and “File IO Stats for DB”.  If IO rates are approaching or are above 20 ms then this suggests a review of the file systems are required to see if they can be configured more optimally or whether faster disks can be deployed.

Latch related waits

Statspack has 2 sections to help identify causes of Library Cache / Shared Pool Latch issues; SQL ordered by Sharable Memory and SQL ordered by Version Count.  Statements with many versions (multiple child cursors with the same parent cursor i.e. identical SQL text but different properties such as owning schema of objects, optimizer session settings, types & lengths of bind variables, etc.) are un-sharable.  This means they can consume excessive memory resources in the Shared Pool and cause performance problems related to parsing e.g. Library Cache and Shared Pool latch contention or lookup time e.g. Library Cache latch contention.




Analysing inefficient SQL within the statspack report


The below is an extract from a statspack report showing the SQL with the highest amount of buffer gets (logical IOs) for the duration of the report.

SQL ordered by Gets for DB: PIPR  Instance: PIPR1  Snaps: 13890 -13907
-> End Buffer Gets Threshold:   10000
-> Note that resources reported for PL/SQL includes the resources used by
   all SQL statements called within the PL/SQL code.  As individual SQL
   statements are also reported, it is possible and valid for the summed
   total % to exceed 100

                                                     CPU      Elapsd
  Buffer Gets    Executions  Gets per Exec  %Total Time (s)  Time (s) Hash Value
--------------- ------------ -------------- ------ -------- --------- ----------
     27,582,160       15,533        1,775.7   11.0  2291.33   3554.56  883547115
Module: JDBC Thin Client
call pk_bdslplus_data.p_get_instrument_data(:1,:2,:3)

     24,534,650       15,534        1,579.4    9.8  2207.23   3288.46 2592888974
Module: JDBC Thin Client
SELECT 'true' POS_IND FROM C_ADHD_AS_DEALT_HOLDING ADHD, C_BF_BA
SE_FUND BF, C_IN_INSTRUMENT CIN WHERE NVL(ADHD.C_ADHD_INDIRECT_M
KR,'N') = 'N' AND BF.C_BF_CODE = ADHD.C_ADHD_BF_CODE AND CIN.C_I
N_ID = ADHD.C_ADHD_IN_ID AND ADHD.C_ADHD_EXP_VALUE IS NOT NULL A
ND CIN.C_IN_SEDOL = :B1 AND CIN.C_IN_INTERNAL_IND != 'Y'

     18,016,650            1   18,016,650.0    7.2   254.74    324.61  864021573
Module: txpu2250.exe@mgunix61a (TNS V1-V3)
SELECT tb1.a_tb_tf_code,        slh.a_slh_linkage_ind,        sl
h.a_slh_error_text,        tb1.a_tb_in_sedol,         tb1.a_tb_i
n_id,         NVL(tb1.a_tb_units_bal,0),         NVL(tb1.a_tb_82
_cost_bal,0),        NVL(tb1.a_tb_np_cost_bal,0),        NVL(tb1
.a_tb_unindexed_82_cost_bal,0),        tir1.c_tirt_bond_tax_basi

     17,557,086       15,345        1,144.2    7.0  1886.30   2127.02  885803753
Module: JDBC Thin Client
SELECT /*+ INDEX(cin c_in_x_2) */ CIN.C_IN_SEDOL "@sedol", TO_CH
AR(SYSDATE,'YYYY-MM-DD')||'T'||TO_CHAR(SYSDATE,'HH24:MI:SS')||'-
00:00' "@datetime", CIN.C_IN_ID "fodbId", NVL(CIN.C_IN_CLEAN_PRI
CE,0) "price", NVL(CIN.C_IN_PRICE_DATE,CTL.C_CTL_VALUATION_DATE)
 "priceDate", CIN.C_IN_PRICE_CR_CODE "priceCrCode", CIN.C_IN_MOD

The SQL statements in this section may appear there for different reasons; for example:

  • The SQL may be very efficient when executed individually; but still appears in the statspack report because it has a high number of executions.  The aim for these SQL statements is to see if the code can be changed to reduce the number of executions. 
  • The SQL has a low number of executions but has an expensive explain plan cost; for example perhaps the code is doing a full table scan on a table with many rows. The aim for these SQL statements is to see if the code can be tuned more optimally.
  • A combination of above where the code is inefficient as well as executed many times.  The aim for these types of SQL statements is to reduce the number of executions while also seeing if the code can be tuned more optimally.

Divide the elapsed time by the number of executions to see how efficient the code is as a single execution.
The HASH VALUE can be used to identify the full SQL statement; for example if the code hasn’t been aged out of the Shared Pool; you can run:

SELECT * from V$SQLTEXT
WHERE HASH_VALUE =
ORDER BY PIECE;

However, Oracle supplies another utility to view not only the full SQL but also the explain plan for any given HASH_VALUE in the statspack report.  This report can be generated by running the script as the PERFSTAT user:

SQL> @?/rdbms/admin/sprepsql.sql

The sprepsql.sql script will ask you for the starting and ending snapshot id of the report as well as the hash_value of the relevant SQL statement and name of the report to be generated.  Below is a sample of such a report using the hash_value 885803753:

STATSPACK SQL report for Hash Value: 885803753  Module: JDBC Thin Client

DB Name         DB Id    Instance     Inst Num Release     Cluster Host
------------ ----------- ------------ -------- ----------- ------- ------------
PIPR           767093029 PIPR1               1 9.2.0.5.0   YES    mgunix60a

 Start Id     Start Time         End Id      End Time       Duration(mins)
--------- ------------------- --------- ------------------- --------------
    13890 19-Nov-07 22:00:05      13907 20-Nov-07 05:00:01          419.93

SQL Statistics
~~~~~~~~~~~~~~
-> CPU and Elapsed Time are in seconds (s) for Statement Total and in
   milliseconds (ms) for Per Execute
                                                       % Snap
                     Statement Total      Per Execute   Total
                     ---------------  ---------------  ------
        Buffer Gets:      17,557,086          1,144.2    7.02
         Disk Reads:          24,261              1.6     .22
     Rows processed:          15,343              1.0
     CPU Time(s/ms):           1,886            122.9
 Elapsed Time(s/ms):           2,127            138.6
              Sorts:          15,344              1.0
        Parse Calls:          15,346              1.0
      Invalidations:               0
      Version count:               4
    Sharable Mem(K):             205
         Executions:          15,345

SQL Text
~~~~~~~~
SELECT /*+ INDEX(cin c_in_x_2) */ CIN.C_IN_SEDOL "@sedol", TO_CH
AR(SYSDATE,'YYYY-MM-DD')||'T'||TO_CHAR(SYSDATE,'HH24:MI:SS')||'-
00:00' "@datetime", CIN.C_IN_ID "fodbId", NVL(CIN.C_IN_CLEAN_PRI
CE,0) "price", NVL(CIN.C_IN_PRICE_DATE,CTL.C_CTL_VALUATION_DATE)
 "priceDate", CIN.C_IN_PRICE_CR_CODE "priceCrCode", CIN.C_IN_MOD
IFIED_DURATION "modifiedDuration", CIN.C_IN_GROSS_REDEM_YIELD "g
rossRedemYield", NVL(PK_INST_PROP.F_GET_IPV_VALUE(CIN.C_IN_ID,'I
C_CRI'), 'UNKNOWN') "sector", DECODE(CIN.C_IN_CHECK_CODE,'Y','tr
ue','false') "checked", DECODE(CIN.C_IN_LIVE_DEAD_MKR,'L','false
','true') "dead", CIN.C_IN_PRICE_BASIS "priceBasis", NVL(CIN.C_I
N_HOLDINGS_MKR,'N') "holdingsMkr", CIN.C_IN_UNITISED_CF_CODE "un
itisedClientFundcode" , PK_BDSL_DATA.IN_FODB_FUND(:B1) "in_fodb_
fund_ind", CIN.C_IN_PRICE_XD_MKR "priceXdMkr" FROM C_IN_INSTRUME
NT CIN,C_CTL_CONTROL CTL WHERE C_IN_CURRENT_MKR = 'Y' AND CIN.C_
IN_SEDOL = :B1

All Optimizer Plan(s) for this Hash Value
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Shows all known Optimizer Plans for this Hash value, and the Snap Id's they
were first found in the shared pool
-> ordered by Snap Id

    Plan
 Hash Value  Snap Id        Cost Optimizer
------------ -------- ---------- --------------------
  2958655084    12579       289  CHOOSE
  2958655084    12756       291  CHOOSE
  2958655084    13122       326  CHOOSE
  2958655084    13516       329  CHOOSE
  2958655084    13867       240  CHOOSE
  2958655084    14212       241  CHOOSE

Plans in shared pool between Begin and End Snap Ids
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Shows the Execution Plans found in the shared pool between the begin and end
snapshots specified.  The values for Rows, Bytes and Cost shown below are those
which existed at the time the first-ever snapshot captured this plan - these
values often change over time, and so may not be indicative of current values
-> Rows indicates Cardinality, PHV is Plan Hash Value
-> ordered by Plan Hash Value

--------------------------------------------------------------------------------
| Operation                      | PHV/Object Name      Rows | Bytes|  Cost |
--------------------------------------------------------------------------------
|SELECT STATEMENT                |----- 2958655084 ----|       |     |      5 |
|MERGE JOIN CARTESIAN            |                     |     1 |   47 |      5 |
| TABLE ACCESS FULL              |C_CTL_CONTROL        |     1 |    8 |      2 |
| BUFFER SORT                    |                     |     1 |   39 |      3 |
 TABLE ACCESS BY INDEX ROWID   |C_IN_INSTRUMENT      |     1 |   39 |      3 |
|   INDEX RANGE SCAN             |C_IN_X_2             |     1 |     |      2 |
--------------------------------------------------------------------------------

End of Report


If you are taking statspack snapshots on a regular basis it is a good idea to clean up and remove old snapshots from the database to avoid excessive use of disk space.

Oracle provides a script to do this which can be run as the PERFSTAT user as follows:

SQL> @?/rdbms/admin/spurge.sql

The script will provide a list of snapshot ids; and will ask you to select the starting and ending id for which it will purge all snapshots in between that range.

Once complete the transaction will still be open (uncommitted) so you can either commit (confirm the action) or rollback (undo the action) at that point.