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  • Common Content for Data Engineering 10.5
  • All Products

Table of Contents

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  1. Preface
  2. Performance Tuning Overview
  3. Target Optimization
  4. Source Optimization
  5. Transformation Optimization
  6. Mapping Optimization
  7. Partitioned Mapping Optimization
  8. Run-time Optimization
  9. SQL Data Service Optimization
  10. Web Service Optimization
  11. Connections Optimization
  12. Data Transformation Optimization

Performance Tuning Guide

Performance Tuning Guide

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Partitioned Mapping Optimization Overview

Partitioned Mapping Optimization Overview

If you have the partitioning option, you can enable the Data Integration Service to maximize parallelism when it runs mappings. When you maximize parallelism, the Data Integration Service dynamically divides the underlying data into partitions and processes all of the partitions concurrently.
If mappings process large data sets or contain transformations that perform complicated calculations, the mappings can take a long time to process and can cause low data throughput. When you enable partitioning for these mappings, the Data Integration Service uses additional threads to process the mapping.
You can optimize the performance of partitioned mappings by performing the following tasks:
  • Use multiple CPUs on the nodes that run mappings.
  • Increase the maximum parallelism value for the Data Integration Service.
  • Configure properties on flat file data objects.
  • Configure relational databases to optimize partitioning.
  • Configure properties on transformations.
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