Documentation: Streams concepts

Watch: Dynamic and Elastic Scaling in Streams v4.3

IBM Streams allows you to scale up your applications by adding parallel data processing. By using the @parallel annotation in your application, you could indicate...

Optional Data Types in the SPL Programming Language

IBM Streams 4.3 introduces a new type to the SPL programming language to better allow Streams applications to interoperate with external data sources such as...

New in Streams 4.3: Using Complex Expressions in the Import Operator

Learn how to use complex, bitwise and nested expressions to filter data from a dynamic connection.

Sliding and Tumbling Windows explained

Windowing allows you to process a snapshot of streaming data.  These two posts explain sliding and tumbling windows in SPL and are a great way...

How to Change Connections at Runtime with Export and Import

If you have an application that uses the Import and Export operators, you might want to change the export properties or import subscription. This...

Automatic Fusion and Threading

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....

Streams Console 4.2: Secure Configuration Repository – RabbitMQ Example

New for the 4.2 release of Streams is a feature giving users the ability to securely store application specific configuration information or parameters that can...

Hourly Moving Average — Streams makes it simple

In a recent discussion around using Streams, the following use case was considered problematic for an existing system. Given a set of devices that produce...

Getting your SPL application ready for the cloud

This article describes SPL application constructs and patterns that may function differently in the cloud, and provides advice on how to make SPL applications that...

Using the Modify Operator to Reduce Copying

This post explains how you can use the new Modify operator to optimize your application by reducing tuple copying.

IBM Streams V4.1 and Incremental Checkpointing

Fang Zheng is a member of the IBM Streams development team. In his presentation, Fang provides an introduction to the incremental checkpointing feature that is...

C++ Primitive Operator with Sliding Window

Illustrates how to create a non-generic C++ primitive operator which uses a sliding window. The code is header-only and uses the pimpl idiom to...

RuntimeFilter: A Filter You Can Change at Runtime

Streams 4.0.1 introduced the evalPredicate function which allows you to evaluate a predicate specified as rstring (eg "x==5") for a limited class of predicates. In...

Extending Streams Functionality with Native Functions

This post demonstrates how to write C++ native functions to add functionality to Streams. When we need to wrap a library so that we...

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...