Pig as Hadoop Connector, Part One: Pig, MongoDB and Node.js by Russell Jurney.
From the post:
Series Introduction
Apache Pig is a dataflow oriented, scripting interface to Hadoop. Pig enables you to manipulate data as tuples in simple pipelines without thinking about the complexities of MapReduce.
But Pig is more than that. Pig has emerged as the ‘duct tape’ of Big Data, enabling you to send data between distributed systems in a few lines of code. In this series, we’re going to show you how to use Hadoop and Pig to connect different distributed systems, to enable you to process data from wherever and to wherever you like.
Working code for this post as well as setup instructions for the tools we use are available at https://github.com/rjurney/enron-node-mongo and you can download the Enron emails we use in the example in Avro format at http://s3.amazonaws.com/rjurney.public/enron.avro. You can run our example Pig scripts in local mode (without Hadoop) with the
-x localflag:pig -x local. This enables new Hadoop users to try out Pig without a Hadoop cluster.Introduction
In this post we’ll be using Hadoop, Pig, mongo-hadoop, MongoDB and Node.js to turn Avro records into a web service. We do so to illustrate Pig’s ability to act as glue between distributed systems, and to show how easy it is to publish data from Hadoop to the web.
I was tempted to add ‘duct tape’ as a category. But there could only be one entry. 😉
Take an early weekend and have some fun with this tomorrow. August will be over sooner than you think.