I often get asked by about fault-tolerance properties of IBM Streams: does it provide exactly-once guarantee? Can it guarantee at least once processing? etc. These can be very important questions with significant business implications
IBM has made a series of announcements recently showing its commitment to Big Data communities including the Open Data Platform (ODP) and Spark. As part of that commitment Streams is adding a number of new capabilities to make it easier to use Streams within your Big Data environment. These include the ability to write Streams applications in Java, using Spark MLlib analytics in Streams and running Streams in an Apache Hadoop Yarn cluster.
The Streams Quick Start Guide is intended to help you get up and running with InfoSphere Streams quickly. We will first introduce the basic concepts and building blocks. And then we will write a very simple Streams application, and demonstrate how you can run and monitor this application in the Streams distributed runtime environment.