Unlock the Power of Spark with IBM Watson and Twitter
Spark is everywhere, including in IBM's cloud infrastructure. Read up on using Spark for Twitter analysis, and how it fits in with Watson and BlueMix.
By David Taieb (IBM Cloud Data Services).
How's your relationship with your customers? What do they feel about you, your products, or your company?
Answering these questions usually requires building and running complex analytics over a large set of data. This takes time, infrastructure, and the right skills, which don't come cheap.
One solution is to leverage Apache Spark(TM), the open-source, in-memory computing framework for distributed data processing. One of the nicest things about Spark is that it features a simple programming model that hides the complexity inherent to distributed computing. As an added bonus, the APIs come in multiple flavors: Scala, Java, Python, and R.
IBM Analytics for Apache Spark lets you combine the power of Spark with the rich set of data-centric services available on IBM Bluemix in new and innovative ways. For example, you can leverage the growing set of Watson Cognitive Services to enrich your data with new insights and build more powerful analytics.
To show what's possible, I created a simple open-source application that uses Spark Streaming to create a feed of live tweets and enrich the data with emotion/tone scores from the Watson Tone Analyzer service. Read how it works.
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