IBM Streams 4.2 introduces two new features designed to make it easier to attain high performance: automatic submission time fusion and the automatic threading model. Automatic submission time fusion means that you can achieve a reasonable number of PEs for your system without having to manually fuse operators, and the automatic threading model means that you can take advantage of multiple cores per host, without having to manually place threaded ports in your application.
Automatic Fusion and Threading
READ: Developer Playground for Real-time Visual Analytics
Learn how to use the READ toolkit to rapidly create real-time visualizations of data produced by Streams applications.
Performance of Guaranteed Processing
In Streams v4.0, we have introduced a new feature called Consistent Region in the product. This feature enables applications to guarantee processing of all tuples. This article discusses how the checkpoint process affects applications performance.
Parallelized File Processing with the Parse Operator
Reading from an external source—such as the network or filesystem—is often a performance bottleneck. When source operators are the performance bottleneck for a streaming application, we have a tendency to blame the reading from the external source. But, that is not always the case. Particularly for large tuples which have many attributes, the actual performance bottleneck can be parsing.
Streams Console: detecting operator memory leaks
Performance Best Practices
InfoSphere Streams Version 4 is a major new release with significant advances in high availability and ease of use. Leveraging these requires careful consideration of performance related configuration options.
Visualize running application state using custom operator metrics
Learn how to create custom operator metrics and custom color schemes for Streams Studio.