Data Analytics

Streaming Analytics: New Service Enhancements

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The IBM Streaming Analytics service is an advanced analytic platform allowing user-developed applications to quickly ingest, analyze, and correlate information as it arrives from a wide variety of real-time data sources. A new version of the service has been released, upgrading the to the IBM Streams product version 4.2 as its basis. This version includes a number of exciting new features and enhancements, which can increase the power, performance and simplicity of your real-time analytic applications.

Current users of Streaming Analytics do not need to take any action to continue to use the service. Your Streams instance has already been upgraded to the new version. Existing applications created using earlier Streams 4.x versions are still compatible with your upgraded Streams instance. However, if you want to exploit new features of Streams 4.2 in your applications, you need to upgrade to Streams 4.2 in your development environment. See the Streaming Analytics Development Guide for instructions on how to set up a development environment.

Streaming Analytics Key Features and Enhancements

Streams 4.2 adds a number of new capabilities that can be exploited in the Bluemix environment:

  • Develop Streams applications in Python Python developers can now create Streams applications and operators purely in Python. The Streams Python Application API is similar to the Streams Java Application API released in Streams 4.1. It uses a functional style with operations on Streams and windows making it natural for Python developers while also mixing in powerful Stream processing concepts. Python has become a very popular language for data scientists with a large number of analytics available in modules like SciKits. These analytic modules can be used within Streams applications written in Python. You may also develop your Streams Python application interactively in a Jupyter Notebook, viewing Streams data and plotting visualizations in the Notebook.
  • Let Streams optimize performance for you Streams 4.2 will intelligently perform an optimization on your Streams application that had to be done manually in the past. Fusion is the assignment of Streams operators to processes. Fusion has always been a key element in performance tuning of Streams applications. Now in Streams 4.2, fusion can be performed automatically at run-time, based on the resources available to host the application. You still have the ability to manually control fusion in any or all parts of your app, but for the parts you do not wish to control, an intelligent fusion configuration will be generated by default.
  • Compile business rules directly into your Streams application Streams 4.2 supports a deeper integration with IBM Operational Decision Manager (ODM). ODM provides a rules language for easily describing business rules and a rich set of tooling to create and manage the rules. Streams 4.2 introduces a rules compiler that generates Streams operators, which are embedded directly into your Streams applications to achieve execution optimized for high performance and low latency. Compiled rules can also be dynamically updated in Streams applications while they are running. In addition, your Streams 4.2 development environment, Streams Studio, now offers a business rules project with the ODM rules designer embedded within it. Once you’ve built your Streams application with compiled rules in your development environment, you can deploy the resulting application bundle to run in your Streaming Analytics instance in Bluemix.
  • Extend your analytic applications to the edge Streams applications are often used to process data from sensors and other edge devices. In February, IBM announced an open source project to build a community for accelerating analytics at the edge that is now undergoing incubation at the Apache Software foundation as Apache Edgent. Streams V4.2 includes an integration with Apache Edgent and Watson IoT Platform to provide a hierarchy of edge to center analytics across devices. The ability to run analytics on edge devices in conjunction with a Streams application running in the cloud enables solutions to react locally to events, and to immediately send only relevant data to the central analytic systems, instead of relying on periodic transfers of all device data.

In addition to Streams 4.2 highlights listed above, there are many more enhancements in Streams 4.2 in areas including performance, toolkits, Streams console, security, and application deployment. For a more detailed description of Streams 4.2 enhancements, see What’s new in Streams 4.2.

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