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There has been an explosion of interest in Apache Spark as a new, alternative computing paradigm for Hadoop. Spark provides a faster and more general data processing platform. Spark lets you run programs up to 100x faster in memory, or 10x faster on disk, than Hadoop. It offers something to interest to everyone from data scientists to functional programmers. Apache Spark comes with an interactive REPL, a SQL interface, distributed functional programming API, streaming interface and implementations of standard machine learning techniques.
This talk Deenar will provide an introduction to Spark to Scala developers, by covering its programming model, language and deployment options.
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Introduction to Apache Spark
Deenar Toraskar is the co-founder of Think Reactive, which provides Spark based responsive, resilient, elastic and ready-to-go data analytics solutions. The solution is built using state-of-the-art technology, end-to-end; from ETL and data pipelines (both batch and streaming), persistence adapters, to analysis and algorithms. All components are packaged using Docker and can run on bare metal or any cloud.