Processing Lots of Data with MapReduce - Google
MapReduce is a programming model used at Google to solve highly parallelisable computing problems. It runs well on large clusters of machines using distributed file systems and it can recover from machine failures. This workshop will give an introduction to the programming model and will illustrate it with examples from Google products such as Maps.
Speaker: Kathrin Paschen
Kathrin Paschen joined Google in London two years ago as a Software Engineer. During that time she has been both a Tech Lead and an individual contributor in development and design for products in CRM and Google's AdWords and AdSense programs. Prior to Google, Kathrin spent three years as a developer at software houses in London and Stuttgart, creating trading room software and bespoke client applications. She also spent a year at CERN, the European Organisation for Nuclear Research in Geneva, working on grid computing simulations for the Large Hadron Collider (LHC). Kathrin has a PhD in Computer Science from the University of Karlsruhe, Germany. As an undergraduate she began to study computational linguistics, then moved to computer science after she learned to program and became interested in mathematics. She maintains an interest in linguistics, speaking multiple European languages and is currently learning Mandarin.