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  1. Preface
  2. Data Integration performance tuning overview
  3. Optimizing targets
  4. Optimizing sources
  5. Optimizing mappings
  6. Optimizing mapping tasks
  7. Optimizing advanced clusters
  8. Optimizing system performance

Data Integration Performance Tuning

Data Integration Performance Tuning

Optimizing Aggregator transformations

Optimizing Aggregator transformations

Aggregator transformations often slow performance because they group data before processing it. Aggregator transformations need additional memory to hold intermediate group results.
For optimal performance, place Aggregator transformations as close to the Source transformation as possible.
Use the following guidelines to optimize the performance of an Aggregator transformation:
  • Group by simple columns.
  • Use sorted input.
  • Filter data before you aggregate it.
  • Limit field connections.

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