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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 worker nodes

Optimizing worker nodes

Provision worker nodes with enough resources to process jobs.
The following table lists the worker node configuration based on the
advanced cluster
type:
Advanced cluster
type
Worker node configuration
Fully-managed cluster
Minimum of 8 CPUs and 32 GB memory.
For better performance, use 16 CPUs and 64 GB memory.
Local cluster
Minimum of 4 CPUs and 16 GB memory.
For better performance, use 8 CPUs and 32 GB memory.
The number of worker nodes that you provision depends on your SLA.

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