Table of Contents

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  1. Preface
  2. Mappings
  3. Mapplets
  4. Mapping Parameters
  5. Mapping Outputs
  6. Generate a Mapping from an SQL Query
  7. Dynamic Mappings
  8. How to Develop and Run a Dynamic Mapping
  9. Dynamic Mapping Use Cases
  10. Mapping Administration
  11. Export to PowerCenter
  12. Import From PowerCenter
  13. Performance Tuning
  14. Pushdown Optimization
  15. Partitioned Mappings
  16. Developer Tool Naming Conventions

Developer Mapping Guide

Developer Mapping Guide

Performance Tuning Overview

Performance Tuning Overview

The Data Integration Service optimizes mappings to improve the performance of a mapping.
The Data Integration Service can perform the following optimizations:
Filter data to reduce the number of rows to be processed.
The Data Integration Service applies optimization methods in an attempt to reduce the amount of data to process. When you run a mapping, you can choose an optimizer level that determines which optimization methods the Data Integration Service can apply to the mapping. For example, the Data Integration Service can use early selection optimization to move a filter closer to the source. It can use pushdown optimization to push transformation logic to a database. It can use the cost-based optimization method to change the join processing order.
The Data Integration Service can apply multiple optimization methods to a mapping at the same time. For example, the Data Integration Service applies the early projection, predicate optimization, early selection, branch pruning, or push-into optimization methods when you select the normal optimizer level.
Determine the partitioning strategy to maximize parallel processing.
If you have the partitioning option, the Data Integration Service can maximize parallelism for mappings. The Data Integration Service dynamically determines the partitioning strategy for mappings. The partitioning strategy includes the location of partition points, the optimal number of partitions for each pipeline stage, and the partitioning types that best redistribute data across each partition point. For more information about partitioning, see Partitioned Mappings Overview.
You can also set constraints on relational sources, logical data objects, physical data objects, and virtual tables in a mapping to filter unnecessary rows. The Data Integration Service can process constraints to improve mapping performance.

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