Query from OEM uses more resources

AWR Report shows the following SQL was using the High resource like CPU and other resources

/* OracleOEM */ WITH blocked_resources AS (select id1 , id2 , SUM(ctime) as blocked_secs , MAX(request) as max_request , COUNT(1) as blocked_count from v$lock where request > 0 group by id1, id2 ) , blockers AS (select L.* , BR.blocked_secs , BR.blocked_count from v$lock L , blocked_resources BR where BR.id1 = L.id1 and BR.id2 = L.id2 and L.lmode > 0 and L.block <> 0 ) select B.id1||’_'||B.id2||’_'||S.sid||’_'||S.serial# as id , ‘SID, SERIAL:’||S.sid||’, ‘||S.serial#||’, LOCK_TYPE:’||B.type||’, PROGRAM:’||S.program||’, MODULE:’||S.module||’, ACTION:’||S.action||’, MACHINE:’||S.machine||’, OSUSER:’||S.osuser||’, USERNAME:’||S.username as info , B.blocked_secs , B.blocked_count from v$session S , blockers B where B.sid = S.sid

You can confirm whether this slowness is because of the System fixed object analysis please check the following SQL.

SQL> select OWNER, TABLE_NAME, LAST_ANALYZED from dba_tab_statistics where table_name IN (‘X$KGLDP’,'X$KSUSE’,'X$KDNSSF’,'X$KSQEQ’,'X$KTADM’);

This above sql may show the Last Analyzed column as NULL as those objects are not analyzed.

Solution:

You should execute the following PL/SQL block to analyze the fixed objects

exec dbms_stats.GATHER_FIXED_OBJECTS_STATS

You should check Metalink Note for more Details

Doc ID 1328789.1: “Query Against v$lock Run from OEM Performs Slowly”.

Solution I – AWR Report:

The first solution that comes in our mind is to go through AWR report for DBA_HIST_SESSMETRIC_HISTORY view. Oracle DBA_HIST_SESSMETRIC_HISTORY displays the history of several important session metrics and we hope to get clue to our problem by analyzing the metrics of past sessions. Unfortunately sometimes we find no rows after querying the view.

Solution II – Enabling Oracle Session History Metrics in DBCONSOLE:

This solution suggests you to enable Oracle Session History Metrics in DBCONSOLE. You can set a small value of Redo Writes per second.

Solution III – Calculating Metric for Redo Generated:

If you are not using Enterprise Manager then you will have to calculate the metric information manually. You can calculate the metric for Redo Generated per second with the formula DeltaRedoSize / Seconds where DeltaRedoSize is the difference in select value from v$sysstat where name=’redo size” between end and start of sample period and Seconds is the number of seconds in sample period.

Solution IV – Querying Oracle V$SESS_IO View:

When undo is generated in any transaction then it will automatically generate redo as well. This solution examines the amount of undo generated in order to find the sessions that are generating lots of redo.

Oracle V$SESS_IO view lists I/O statistics for each user session. The column BLOCK_CHANGES shows the number of blocks changed by the session. High value for this column means your session is generating lots of redo. You will have to run below query multiple times and examine the delta between each occurrence of BLOCK_CHANGES. If you get large deltas then it shows high redo generation by the session. You use this solution to check for programs that are generating lots of redo when these programs activate more than one transaction.

SQL> SELECT S1.SID, S1.SERIAL_NUM, S1.USER_NAME, S1.PROGRAM, I1.BLOCK_CHANGES
FROM V$SESSION S1, V$SESS_IO I1 WHERE S1.SID = I1.SID ORDER BY 5 DESC, 1, 2, 3, 4; 

Solution V – Querying Oracle V$TRANSACTION View:

Oracle V$TRANSACTION is a Data Dictionary view that lists the active transactions in the system. This view can be used to track undo by session. The USED_UBLK column of this view shows the number of undo blocks used and the USED_UREC column shows the number of undo records used by the transaction.

Below query can help you find out the particular transactions that are generating redo. Running the query multiple times and analyzing the delta between each occurrence of USED_UBLK and SED_UREC will help you infer that large deltas indicate high redo generation by the session.

SQL> SELECT S1.SID, S1.SERIAL_NUM, S1.USER_NAME, S1.PROGRAM, T1.USED_UBLK, T1.USED_UREC
FROM V$SESSION S1, V$TRANSACTION T1 WHERE S1.TADDR = T1.ADDR ORDER BY 5 DESC, 6 DESC, 1, 2, 3, 4; 

Solution VI – Tracking Undo Generated By All Sessions:
The following statement displays a record for all sessions that have generated undo. It shows both how many undo blocks and undo records a session made.

SELECT S1.SID, S1.USER_NAME, R1.NAME, T1.START_TIME, T1.USED_UBLK , T1.USED_UREC
FROM V$SESSION S1, V$TRANSACTION T1, V$ROLLNAME R1 WHERE T1.ADDR = S1.TADDR AND R1.USN = T1.XIDUSN;

Solution VII – Collecting Statistics from V$SESSTAT to AWR:

Oracle V$SESSTAT view records the statistical data about the session that accesses it. You will have query the V$STATNAME view in order to find the name of the statistic associated with each statistic number. In this solution we will collects statistics from V$SESSTAT view into our private AWR views.

SELECT s.sid, s.serial#, s.username, s.program,
i.block_changes
FROM v$session s, v$sess_io i
WHERE s.sid = i.sid
ORDER BY 5 desc;

SELECT s.sid, s.serial#, s.username, s.program,
t.used_ublk, t.used_urec
FROM v$session s, v$transaction t
WHERE s.taddr = t.addr
ORDER BY 5,6 desc;

select nam.indx+1 numb,
             nam.ksppinm name,
             val.ksppstvl value,
             nam.ksppity type,
             val.ksppstdf is_default,
            decode(bitand(nam.ksppiflg/256,1), 1,’True’, ‘False’ ) is_session_modifiable,
            decode(bitand(nam.ksppiflg/65536,3), 1,’Immediate’, 2,’Deferred’ , 3,’Immediate’, ‘False’ ) is_system_modifiable,
            decode(bitand(val.ksppstvf,7), 1,’Modified’, 4,’System Modified’, ‘False’ ) is_modified,
            decode(bitand(val.ksppstvf,2), 2,’True’, ‘False’ ) is_adjusted,
            nam.ksppdesc description
from
           x$ksppi nam,
           x$ksppcv val
where
            nam.indx = val.indx ;

select nam.indx+1 numb,
             nam.ksppinm name,
             val.ksppstvl value,
             nam.ksppity type,
             val.ksppstdf is_default,
            decode(bitand(nam.ksppiflg/256,1), 1,’True’, ‘False’ ) is_session_modifiable,
            decode(bitand(nam.ksppiflg/65536,3), 1,’Immediate’, 2,’Deferred’ , 3,’Immediate’, ‘False’ ) is_system_modifiable,
            decode(bitand(val.ksppstvf,7), 1,’Modified’, 4,’System Modified’, ‘False’ ) is_modified,
            decode(bitand(val.ksppstvf,2), 2,’True’, ‘False’ ) is_adjusted,
            nam.ksppdesc description
from
           x$ksppi nam,
           x$ksppsv val
where
            nam.indx = val.indx ;

How to replace a bulk comman with new line in an Editor?

   We can easily do it in Winword. Use the replace tool to search for “,” and replace with “^l”

rman backup at different directory structure .then how can recover and restore datafile and logfile

1. which dbms package we can use in mount mode..
2. how to exculde table during stats gather with dbms package

Q. What type of repositories can be created using Informatica Repository Manager?

A. Informatica PowerCenter includeds following type of repositories :

•Standalone Repository : A repository that functions individually and this is unrelated to any other repositories.
•Global Repository : This is a centralized repository in a domain. This repository can contain shared objects across the repositories in a domain. The objects are shared through global shortcuts.
•Local Repository : Local repository is within a domain and it’s not a global repository. Local repository can connect to a global repository using global shortcuts and can use objects in it’s shared folders.
•Versioned Repository : This can either be local or global repository but it allows version control for the repository. A versioned repository can store multiple copies, or versions of an object. This features allows to efficiently develop, test and deploy metadata in the production environment.
Q. What is a code page?

A. A code page contains encoding to specify characters in a set of one or more languages. The code page is selected based on source of the data. For example if source contains Japanese text then the code page should be selected to support Japanese text.

When a code page is chosen, the program or application for which the code page is set, refers to a specific set of data that describes the characters the application recognizes. This influences the way that application stores, receives, and sends character data.

Q. Which all databases PowerCenter Server on Windows can connect to?

A. PowerCenter Server on Windows can connect to following databases:

•IBM DB2
•Informix
•Microsoft Access
•Microsoft Excel
•Microsoft SQL Server
•Oracle
•Sybase
•Teradata
Q. Which all databases PowerCenter Server on UNIX can connect to?

A. PowerCenter Server on UNIX can connect to following databases:

•IBM DB2
•Informix
•Oracle
•Sybase
•Teradata

Informatica Mapping Designer
Q. How to execute PL/SQL script from Informatica mapping?

A. Stored Procedure (SP) transformation can be used to execute PL/SQL Scripts. In SP Transformation PL/SQL procedure name can be specified. Whenever the session is executed, the session will call the pl/sql procedure.

Q. How can you define a transformation? What are different types of transformations available in Informatica?

A. A transformation is a repository object that generates, modifies, or passes data. The Designer provides a set of transformations that perform specific functions. For example, an Aggregator transformation performs calculations on groups of data. Below are the various transformations available in Informatica:
•Aggregator
•Application Source Qualifier
•Custom
•Expression
•External Procedure
•Filter
•Input
•Joiner
•Lookup
•Normalizer
•Output
•Rank
•Router
•Sequence Generator
•Sorter
•Source Qualifier
•Stored Procedure
•Transaction Control
•Union
•Update Strategy
•XML Generator
•XML Parser
•XML Source Qualifier

Q. What is a source qualifier? What is meant by Query Override?

A. Source Qualifier represents the rows that the PowerCenter Server reads from a relational or flat file source when it runs a session. When a relational or a flat file source definition is added to a mapping, it is connected to a Source Qualifier transformation.

PowerCenter Server generates a query for each Source Qualifier Transformation whenever it runs the session. The default query is SELET statement containing all the source columns. Source Qualifier has capability to override this default query by changing the default settings of the transformation properties. The list of selected ports or the order they appear in the default query should not be changed in overridden query.

Q. What is aggregator transformation?

A. The Aggregator transformation allows performing aggregate calculations, such as averages and sums. Unlike Expression Transformation, the Aggregator transformation can only be used to perform calculations on groups. The Expression transformation permits calculations on a row-by-row basis only.

Aggregator Transformation contains group by ports that indicate how to group the data. While grouping the data, the aggregator transformation outputs the last row of each group unless otherwise specified in the transformation properties.

Various group by functions available in Informatica are : AVG, COUNT, FIRST, LAST, MAX, MEDIAN, MIN, PERCENTILE, STDDEV, SUM, VARIANCE.

Q. What is Incremental Aggregation?

A. Whenever a session is created for a mapping Aggregate Transformation, the session option for Incremental Aggregation can be enabled. When PowerCenter performs incremental aggregation, it passes new source data through the mapping and uses historical cache data to perform new aggregation calculations incrementally.

Q. How Union Transformation is used?

A. The union transformation is a multiple input group transformation that can be used to merge data from various sources (or pipelines). This transformation works just like UNION ALL statement in SQL, that is used to combine result set of two SELECT statements.

Q. Can two flat files be joined with Joiner Transformation?

A. Yes, joiner transformation can be used to join data from two flat file sources.

Q. What is a look up transformation?

A. This transformation is used to lookup data in a flat file or a relational table, view or synonym. It compares lookup transformation ports (input ports) to the source column values based on the lookup condition. Later returned values can be passed to other transformations.

Q. Can a lookup be done on Flat Files?

A. Yes.

Q. What is the difference between a connected look up and unconnected look up?

A. Connected lookup takes input values directly from other transformations in the pipleline.

Unconnected lookup doesn’t take inputs directly from any other transformation, but it can be used in any transformation (like expression) and can be invoked as a function using :LKP expression. So, an unconnected lookup can be called multiple times in a mapping.

Q. What is a mapplet?

A. A mapplet is a reusable object that is created using mapplet designer. The mapplet contains set of transformations and it allows us to reuse that transformation logic in multiple mappings.

Q. What does reusable transformation mean?

A. Reusable transformations can be used multiple times in a mapping. The reusable transformation is stored as a metadata separate from any other mapping that uses the transformation. Whenever any changes to a reusable transformation are made, all the mappings where the transformation is used will be invalidated.

Q. What is update strategy and what are the options for update strategy?

A. Informatica processes the source data row-by-row. By default every row is marked to be inserted in the target table. If the row has to be updated/inserted based on some logic Update Strategy transformation is used. The condition can be specified in Update Strategy to mark the processed row for update or insert.

Following options are available for update strategy :
•DD_INSERT : If this is used the Update Strategy flags the row for insertion. Equivalent numeric value of DD_INSERT is 0.
•DD_UPDATE : If this is used the Update Strategy flags the row for update. Equivalent numeric value of DD_UPDATE is 1.
•DD_DELETE : If this is used the Update Strategy flags the row for deletion. Equivalent numeric value of DD_DELETE is 2.
•DD_REJECT : If this is used the Update Strategy flags the row for rejection. Equivalent numeric value of DD_REJECT is 3.

Simple example/sample tnsnames.ora

TEST = (DESCRIPTION = (ADDRESS_LIST = (ADDRESS = (PROTOCOL = TCP) (HOST = UNIX01)(PORT = 1521)) ) (CONNECT_DATA = (SID = TEST)) )