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  1. Abstract for Profiling Sizing Guidelines
  2. Supported Versions
  3. Profiling and Discovery Sizing Guidelines

Profiling and Discovery Sizing Guidelines

Profiling and Discovery Sizing Guidelines

Functional Architecture of Profiling Service Module

Functional Architecture of Profiling Service Module

The Profiling Service Module is a component of the Data Integration Service and runs profile jobs and returns profile results. The functional architecture consists of tools, services, and databases.
The following figure shows the functional architecture of the Profiling Service Module:
Data Integration Service
The Profiling Service Module runs all the profiling jobs as mappings and uses the scalable and multithreaded Data Integration Service environment. The Profiling Service Module analyzes each profile job to determine the optimal number of mappings and sequence of mappings for the best job performance.
You can configure the Data Integration Service to run on a single node or multiple nodes. In a single-node configuration, all the processing happens on one node. In a multinode configuration, all the processing happens on an Informatica grid. In both configurations, the Data Integration Service is a single service. You cannot differentiate between mappings running on one node or multiple nodes.
Profiling Warehouse
The profiling warehouse stores all the profile results, computes SQL queries, and returns all SQL queries on these results. You can use a set of profiling warehouse views that you can customize for the profile statistics that you want to read. Profiling warehouse relies on standard relational database technology for scalability and performance.
Profiling warehouse maintains the persisted profile job queue. The profile job queue stores jobs based on priority so that the real-time jobs with high priority run first followed by the long-running jobs. This method of running different job types in a nonlinear manner brings out the best throughput.
Data Sources
The Data Integration Service can access all data sources. Based on the type of source data, the Data Integration Service uses pushdown optimization to transfer the profiling logic to the data source for full or partial run.

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