Performance Tuning in Informatica

The goal of performance tuning is to optimize session performance so sessions run during the available load window for the Informatica Server. You can increase the session performance by following. 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.

Flat files: If ur flat files stored on a machine other than the informatica server, move those files to the machine that consists of informatica server. Relational datasources: Minimize the connections to sources, targets and informatica server to improve session performance. Moving target database into server system may improve session performance.

Staging areas: If u use staging areas u force informatica server to perform multiple data passes. Removing of staging areas may improve session performance.
U can run the multiple informatica servers against the same repository. Distributing the session load to multiple informatica servers may improve session performance.

Running the informatica server in ASCII datamovement mode improves the session performance because ASCII datamovement mode stores a character value in one byte. Unicode mode takes 2 bytes to store a character.

If a session joins multiple source tables in one Source Qualifier, optimizing the query may improve performance. Also, single table select statements with an ORDER BY or GROUP BY clause may benefit from optimization such as adding indexes.

We can improve the session performance by configuring the network packet size, which allows data to cross the network at one time. To do this go to server manger, choose server configure database connections. If u r target consists key constraints and indexes u slow the loading of data. To improve the session performance in this case drop constraints and indexes before u run the session and rebuild them after completion of session.

Running parallel sessions by using concurrent batches will also reduce the time of loading the data. So concurrent batches may also increase the session performance.

Partitioning the session improves the session performance by creating multiple connections to sources and targets and loads data in parallel pipelines.

In some cases if a session contains an aggregator transformation, u can use incremental aggregation to improve session performance. Avoid transformation errors to improve the session performance. If the session contains lookup transformation u can improve the session performance by enabling the look up cache. If U’r session contains filter transformation, create that filter transformation nearer to the sources or u can use filter condition in source qualifier. Aggregator, Rank and joiner transformation may often decrease the session performance because they must group data before processing it. To improve session performance in this case use sorted ports option.