MIA: Matei Zaharia, Scaling analysis with Apache Spark; Tim Poterba, Jon Bloom, Distributed compute

Models, Inference and Algorithms
Broad Institute of MIT and Harvard
Spring 2016

MIA Meeting: https://youtu.be/1FyG2YlAGmU?t=2879

Matei Zaharia,
MIT CSAIL, EECS; Cofounder/CTO, Databricks;

Scaling data analysis with Apache Spark

Apache Spark is an open-source, cluster-computing framework for data analysis that handles the details of data parallelism and
fault-tolerance. In this talk, I'll discuss the "big data" problem,
the concepts underlying MapReduce and Spark, and several applications.

Visit the link below to advance to the MIA Meeting with Matei Zaharia.

MIA Primer
Tim Poterba and Jon Bloom, Neale Lab
Introduction to distributed computation

As a primer for Matei (the original author of Apache Spark), we'll
discuss distributed architecture, the MapReduce framework in the
context of genetic data, and distributed approaches to model inference
in linear regression, neural networks, and Bayesian graphical models.


For more information about Models, Inference and Algorithms visit: http://www.broadinstitute.org/mia

Copyright Broad Institute, 2016. All rights reserved.

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  • Science & Technology

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