WebSphere Message Broker, Version 8.0.0.7
Operating Systems: AIX, HP-Itanium, Linux, Solaris, Windows, z/OS
See information about the latest product version
See information about the latest product version
Resolving problems with performance
Use the advice given here to help you to resolve common problems with performance.
- Scenario: You are experiencing problems with performance,
such as:
- Poor response times in the WebSphere® Message Broker Toolkit when developing message flows
- Poor response time at deployment
- Individual messages taking a long time to process
- Poor overall performance, or performance that does not scale well
- Solution: Possible solutions are:
- Tune the broker
- Speed up WebSphere MQ persistent messaging by optimizing the I/O (input/output)
- Speed up database access by optimizing I/O
- Increase system memory
- Use additional instances or multiple execution groups
- Optimize ESQL statements for best performance
A good source of information about performance is the set of reports in WebSphere MQ Family Category 2 (freeware) SupportPacs, available for download from the WebSphere MQ SupportPacs web page.
For more information, read Do you have a component that is running slowly?.
This topic
contains advice for dealing with some common performance problems
that can arise:
- A WHILE loop in a large XML array takes a long time to process
- Message flow performance is reduced when you access message trees with many repeating records
- You are experiencing poor performance in the WebSphere Message Broker Toolkit when working with large projects
- Performance is reduced when you run Web Services with small message sizes
A WHILE loop in a large XML array takes a long time to process
Message flow performance is reduced when you access message trees with many repeating records
You are experiencing poor performance in the WebSphere Message Broker Toolkit when working with large projects
- Scenario: You are experiencing poor performance in the WebSphere Message Broker Toolkit when working with large or complex projects.
- Explanation: Performance is reduced because of frequent project changes, such as adding and removing projects, or using . Complete project updates use large amounts of memory due to the size, number, and connections between files.
- Solution: Increase your system memory.