Useful Informatica Performance Tuning Tips 6c4l3n

Useful Informatica Performance Tuning Tips The goal of performance tuning is to optimize session performance so that sessions run complete successfully in the available load window for the Informatica Server. Increase the session performance by following: 1. 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 and so avoid network connections. 2. Flat files: If your flat files are stored on a machine other than the informatica server, move those files to the machine that consists of informatica server. 3. Relational data sources: Minimize the connections to sources, targets and informatica server to improve session performance. Moving target database into server system may improve session performance. 4. Staging areas: If you use staging areas you force informatica server to perform multiple dataes. Removing of staging areas may improve session performance. 5. You can run multiple informatica servers against the same repository. Distributing the session load to multiple informatica servers may improve session performance. 6. Running the informatica server in ASCII data movement mode improves the session performance because ASCII data movement mode stores a character value in one byte. Unicode mode takes 2 bytes to store a character. 7. If a session s 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. 8. 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 manager, choose server configure database connections. 9. If your target consists of key constraints and indexes, it slows the loading of data. To improve the session performance in this case drop constraints and indexes before you run the session and rebuild them after completion of session. 10. 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. 11. Partitioning the session improves the session performance by creating multiple connections to sources and targets and loads data in parallel pipe lines. 12. In some cases if a session contains an aggregator transformation, you can use incremental aggregation to improve session performance. 13. Avoid transformation errors to improve the session performance. 14. If the session contains lookup transformation you can improve the session performance by enabling the look up cache. 15. If your session contains filter transformation, create that filter transformation nearer to the sources or you can use filter condition in source qualifier. 16. Aggregator, Rank and er 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. 17. If the lookup has many records, try creating indexes on the columns used in the lkp condition and try increasing the lookup cache. If this doesn’t increase the performance and if the target has any other indexes, disable them in the target pre load and enable them in the target post load.