13 Jul 2016 Informatica Performance – Optimization techniques

Informatica provides the market´s leading data integration platform. ETL Mappings are designed for data loading into the data warehouse environment to achieve better reporting which in turn helps you to understand business trends better. The major problem faced by anyone working with Informatica ETL is to design a mapping(s) that doesn’t compromise its performance. Often we end up creating a mapping that achieves only the functionality but suffers in terms of performance.

The article explains the steps to identify the performance bottlenecks and the advanced optimization techniques that are available in Informatica to overcome them.

Following topics are discussed in detail:

* Optimizing sources, Targets and Buffer Blocks:
Performance bottlenecks can occur when the Integration Service reads from a source database or writes to a target database. Depending on the source, target data, you may need to increase or decrease the buffer block size. In this article we list the steps you have to take to ensure that the sources and the Targets are fully utilized to optimum level and how to calculate Buffer block size.

* Push down Optimization (PDO):
Push Down Optimization Option enables data transformation processing to be pushed down into any relational database to make the best use of database processing power.

* Session Partitioning & Dynamic Session Partitioning:
The Session Partitioning Option increases the performance of Power Center through parallel data processing. In dynamic partitioning, Integration Service determines the number of partitions to create at run time based on factors such as source database partitions or the number of nodes in a grid.

* Concurrent Workflow Execution:
A workflow configured for Concurrent Execution can run as multiple instances concurrently. In the article we illustrate this functionality by using a workflow that is configured with multiple instances to process data belonging to multiple sites simultaneously.

* Load Balancing:
Load balancing is a mechanism which distributes the workloads across the nodes in the gird. In the article we see how to assigning Service Levels to Workflows to achieve Load Balancing.

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