IBM Streams 4.2.1
Writing streams processing applications
IBM® Streams provides features and functions to help you write your applications to fulfill your business needs.
- Best practices for developing applications
Use these tips to write operators that perform effectively in their application, and in other applications. - Developing streams processing applications with user-defined parallelism
The @parallel annotation allows developers to easily take advantage of data-parallelism. In the streaming context, data-parallelism means replicating copies of operators, and splitting streams so that different tuples go to each set of replicas. The process of replicating operators, and creating all of the new streams to connect them, is called the parallel transformation. When developers add @parallel to a primitive or composite operator invocation, IBM Streams will perform the parallel transformation at submission time. The goal is to improve overall application throughput by executing the replicas in parallel. - Developing streams processing applications with consistent regions
Because of business requirements, some applications require that all tuples in an application are processed at least once. You can use a consistent region in your streams processing applications to avoid data loss due to software or hardware failure and meet your requirements for at-least-once processing. - Developing streams processing applications with views
To make streaming data available to external programs such as Microsoft Excel 2010 or 2013, your SPL application must create at least one view. A view defines the set of attributes that can appear in a specific viewable data stream in Microsoft Excel.
Parent topic: Developing