We’re continuing our series of quick interviews with Apache Hadoop project committers at Hortonworks.
This week Alan Gates, Hortonworks Co-Founder and Apache Pig Committer, discusses using Apache Pig for efficiently managing MapReduce workloads. Pig is ideal for transforming data in Hadoop: joining it, grouping it, sorting it and filtering it.
Alan explains how Pig takes scripts written in a language called Pig Latin and translates those into MapReduce jobs.
Listen to Alan describe the future of Pig in Hadoop 2.0. Work going on in the open community, focused in the Apache Tez project, will make Pig faster and more efficient while not requiring Pig users to change their Pig Latin scripts or their UDFs.
This is the latest in our series of quick interviews with Apache Hadoop project committers at Hortonworks.