Table of Contents

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  1. Preface
  2. Performance Tuning Overview
  3. Bottlenecks
  4. Optimizing the Target
  5. Optimizing the Source
  6. Optimizing Mappings
  7. Optimizing Transformations
  8. Optimizing Sessions
  9. Optimizing Grid Deployments
  10. Optimizing the PowerCenter Components
  11. Optimizing the System
  12. Using Pipeline Partitions
  13. Appendix A: Performance Counters

Performance Tuning Guide

Performance Tuning Guide

Grid

Grid

You can use a grid to increase session and workflow performance. A grid is an alias assigned to a group of nodes that allows you to automate the distribution of workflows and sessions across nodes.
A Load Balancer distributes tasks to nodes without overloading any node.
When you use a grid, the Integration Service distributes workflow tasks and session threads across multiple nodes. A Load Balancer distributes tasks to nodes without overloading any node. Running workflows and sessions on the nodes of a grid provides the following performance gains:
  • Balances the Integration Service workload.
  • Processes concurrent sessions faster.
  • Processes partitions faster.
The Integration Service requires CPU resources for parsing input data and formatting the output data. A grid can improve performance when you have a performance bottleneck in the extract and load steps of a session.
A grid can improve performance when memory or temporary storage is a performance bottleneck. When a PowerCenter mapping contains a transformation that has cache memory, deploying adequate memory and separate disk storage for each cache instance improves performance.
Running a session on a grid can improve throughput because the grid provides more resources to run the session. Performance improves when you run a few sessions on the grid at a time. Running a session on a grid is more efficient than running a workflow over a grid if the number of concurrent session partitions is less than the number of nodes.
When you run multiple sessions on a grid, session subtasks share node resources with subtasks of other concurrent sessions. Running a session on a grid requires coordination between processes running on different nodes. For some mappings, running a session on a grid requires additional overhead to move data from one node to another node. In addition to loading the memory and CPU resources on each node, running multiple sessions on a grid adds to network traffic.
When you run a workflow on a grid, the Integration Service loads memory and CPU resources on nodes without requiring coordination between the nodes.