Combine Apache® Spark™ with other cloud services to speed analysis and reveal insights.Whether you want to track how a conversation is trending on Twitter or predict future events based on a trove of existing data, the lighting-fast processing power of Apache® Spark™ can help you crunch large data sets fast. We’ll show you how to harness the power and potential of the Apache® Spark™ engine and programming model.
Why Spark?Apache® Spark™ is the open-source, cluster-computing framework with in-memory processing, which runs up to 100 times faster than other technologies on the market today. One of the nicest things about this technology 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.
Analytics for Apache Spark integrates with SWIFT Object Storage, Cloudant, dashDB, SQLDB, Watson, and other IBM Cloud services. These services all play well together on a single cloud platform, which eases development and lets you bring creativity and breadth to your analysis solutions.
Combined Services in ActionThis video demo shows how you can set up Apache Spark to work with Watson Tone Analyzer to gauge social and emotional tones in a set of tweets.
- Start Developing with Spark and Notebooks
- Sentiment Analysis of Twitter Hashtags
- Realtime Sentiment Analysis of Twitter Hashtags
- Sentiment Analysis of reddit AMAs
- Speed SQL Queries with Spark SQL
- Analytics for Apache Spark
- Spark-Cloudant Connector
- Watson Tone Analyzer
- Message Hub (Apache Kafka)
- Message Connect (event streams)
Blogs ‘n’ Stuff
- Spark Learning Center
- Spark articles
- Journey to Space with SETI and IBM Analytics for Apache Spark
- Status Update from the SETI Institute
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