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From our Customers

With foursquare's growing popularity, we were fast approaching the point where it would no longer be feasible to store user checkins on a single physical machine. MongoDB's auto-sharding capabilities enabled us to easily transition to a multi-node cluster that will enable us to continue to grow for the foreseeable future.

Harry Heymann Engineering Lead, foursquare

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Hadoop Plugin for MongoDB

Brendan McAdams, 10gen

bwmcadams     @rit

Video

Learn how to integrate MongoDB with Hadoop for large-scale distributed data processing. Using tools like MapReduce, Pig and Streaming you will learn how to do analytics and ETL on large datasets with the ability to load and save data against MongoDB. With Hadoop MapReduce, Java and Scala programmers will find a native solution for using MapReduce to process their data with MongoDB. Programmers of all kinds will find a new way to work with ETL using Pig to extract and analyze large datasets and persist the results to MongoDB. Python and Ruby Programmers can rejoice as well in a new way to write native Mongo MapReduce using the Hadoop Streaming interfaces.

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