Massive growth in the size of business datasets leads many companies to Hadoop, an emerging architecture for parallel data processing (and top-level Apache project). However, the migration path can be challenging, in part because MapReduce analyses use programming languages like Java and Python rather than SQL. Apache Pig is a high-level framework built on top of Hadoop that offers a powerful yet vastly simplified way to analyze data in Hadoop. It allows businesses to leverage the power of Hadoop in a simple language readily learnable by anyone that understands SQL. In this presentation, I will introduce Pig and show how it’s been used at Twitter to solve numerous analytics challenges that became intractable with our former MySQL-based architecture.
Kevin Weil leads the analytics team at Twitter, building distributed infrastructure and leveraging data analysis at a massive scale to help grow the popular micro-blogging service. With millions of monthly site visitors and many more interacting through API-based third party applications, Twitter has one of the world’s most varied and interesting datasets. Prior to joining Twitter, Kevin led the analytics team at the Kleiner Perkins-backed web media startup Cooliris. Kevin earned his bachelor’s degree in Mathematics and Physics from Harvard University, and has a master’s degree in Physics from Stanford University.
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