Published on February 07, 2014
IBM Form #: SG24-8139-00
Authors: Chuck Ballard, Oliver Brandt, Bharath Devaraju, Daniel Farrell, Kevin Foster, Chris Howard, Peter Nicholls, Ankit Pasricha, Roger Rea, Norbert Schulz, Tetsuya Shimada, John Thorson, Sandra Tucker and Robert Uleman
This IBM® Redbooks® publication describes visual development, visualization, adapters, analytics, and accelerators for IBM InfoSphere® Streams (V3), a key component of the IBM Big Data platform. Streams was designed to analyze data in motion, and can perform analysis on incredibly high volumes with high velocity, using a wide variety of analytic functions and data types.
The Visual Development environment extends Streams Studio with drag-and-drop development, provides round tripping with existing text editors, and is ideal for rapid prototyping. Adapters facilitate getting data in and out of Streams, and V3 supports WebSphere MQ, Apache Hadoop Distributed File System, and IBM InfoSphere DataStage. Significant analytics include the native Streams Processing Language, SPSS Modeler analytics, Complex Event Processing, TimeSeries Toolkit for machine learning and predictive analytics, Geospatial Toolkit for location-based applications, and Annotation Query Language for natural language processing applications. Accelerators for Social Media Analysis and Telecommunications Event Data Analysis sample programs can be modified to build production level applications.
Want to learn how to analyze high volumes of streaming data or implement systems requiring high performance across nodes in a cluster? Then this book is for you.
Chapter 1. Introduction
Chapter 2. Application programming using Streams Studio
Chapter 3. Visualizing stream data
Chapter 4. Analytics entirely with SPL
Chapter 5. Streams and DataStage integration
Chapter 6. Streams integration with IBM BigInsights
Chapter 7. Complex event processing
Chapter 8. WebSphere MQ, XMSSource, XMSSink
Chapter 9. XML, XMLParse, XPath, and xquery
Chapter 10. Geospatial Toolkit
Chapter 11. TimeSeries Toolkit
Chapter 12. Developing Java primitive operators
Chapter 13. Text Analytics, AQL
Chapter 14. IBM Accelerator for Telecommunications Event Data Analytics V1.2
Chapter 15. SPSS Toolkit
Appendix A. Additional material