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Optimizing the Bottleneck’s 

1.  If the source is a flat file, ensure that the flat file is local to the Informatica server. If 

source is a relational table, then try not to use synonyms or aliases.

2. 

If the source is a flat file, reduce the number of bytes (By default it is 1024 bytes per line)the Informatica reads per line. If we do this, we can decrease the Line Sequential Buffer

Length setting of the session properties.3.  If possible, give a conditional query in the source qualifier so that the records are filtered

off as soon as possible in the process.

4.  In the source qualifier, if the query has ORDER BY or GROUP BY, then create an indexon the source table and order by the index field of the source table.

PERFORMANCE TUNING OF TARGETS 

If the target is a flat file, ensure that the flat file is local to the Informatica server. If target is a

relational table, then try not to use synonyms or aliases.

1.  Use bulk load whenever possible.

2.  Increase the commit level.3.  Drop constraints and indexes of the table before loading.

PERFORMANCE TUNING OF MAPPINGS 

Mapping helps to channel the flow of data from source to target with all the transformations in

between. Mapping is the skeleton of Informatica loading process.

1. 

Avoid executing major sql queries from mapplets or mappings.2.  Use optimized queries when we are using them.3.  Reduce the number of transformations in the mapping. Active transformations like rank,

 joiner, filter, aggregator etc should be used as less as possible.

4.  Remove all the unnecessary links between the transformations from mapping.5.  If a single mapping contains many targets, then dividing them into separate mappings can

improve performance.

6.  If we need to use a single source more than once in a mapping, then keep only one sourceand source qualifier in the mapping. Then create different data flows as required into

different targets or same target.

7.  If a session joins many source tables in one source qualifier, then an optimizing query

will improve performance.8.  In the sql query that Informatica generates, ORDERBY will be present. Remove the

ORDER BY clause if not needed or at least reduce the number of column names in that

list. For better performance it is best to order by the index field of that table.

9.  Combine the mappings that use same set of source data.10. On a mapping, field with the same information should be given the same type and length

throughout the mapping. Otherwise time will be spent on field conversions.

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8.  String functions like substring, ltrim, and rtrim reduce the performance. In the sources,

use delimited strings in case the source flat files or use varchar data type.9.  Manipulating high precision data types will slow down Informatica server. So disable

‘high precision’.

10. Localize all source and target tables, stored procedures, views, sequences etc. Try not to

connect across synonyms. Synonyms and aliases slow down the performance.

DATABASE OPTIMISATION 

To gain the best Informatica performance, the database tables, stored procedures and queries

used in Informatica should be tuned well.

1.  If the source and target are flat files, then they should be present in the system in which

the Informatica server is present.2.  Increase the network packet size.

3.  The performance of the Informatica server is related to network connections.Data

generally moves across a network at less than 1 MB per second, whereas a local disk moves data five to twenty times faster. Thus network connections often affect on session

performance. So avoid network connections.

4.  Optimize target databases