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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

Thread statistics

Thread statistics

You can use thread statistics in the session log to identify source, target, or transformation bottlenecks.
By default, a mapping uses one reader thread, one transformation thread, and one writer thread. The thread with the highest busy percentage identifies the bottleneck in the mapping run. When a specific transformation is identified as a bottleneck, you can tune the transformation.
The session log provides the following thread statistics:
Run time
Amount of time the thread runs.
Idle time
Amount of time the thread is idle, including the time the thread waits for other thread processing within the application. Idle time includes the time the thread is blocked by the Data Integration Server, but not the time the thread is blocked by the operating system.
Busy time
Percentage of the run time the thread is busy according to the following formula:
(Run time - idle time) / run time X 100
You can ignore high busy percentages when the total run time is short, such as under 60 seconds. This doesn't necessarily indicate a bottleneck.
To determine which transformation in the transformation thread is the bottleneck, view the busy percentage of each transformation in the thread work time breakdown. If the source, target, or transformations don't appear as the bottleneck, task properties could be causing the bottleneck.

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