Wednesday, February 17, 2016
11:50 AM
Goergen Hall, Room 101
Ahmed Eldawy
University of Minnesota
SpatialHadoop: A MapReduce Framework for Big Spatial Data

This talk describes SpatialHadoop; an open-source full-fledged system for indexing, querying, and visualizing big spatial data. SpatialHadoop is built as a comprehensive extension to Hadoop that injects spatial data awareness inside each Hadoop layer, namely, language, indexing, operations, and visualization. The language layer provides a simple high-level language with industry-standard spatial data types and functions. The indexing layer introduces a set of spatial indexes that can be built on big spatial datasets, such as, R-tree, Quad-tree, and K-d tree. The operations layer encapsulates a wide range of spatial operations including range query, spatial join, and computational geometry. The visualization layer provides an extensible visualization module that allows users to generate customized images to interactively explore big spatial datasets. This talk will also describe three case studies of applications that use SpatialHadoop as a backbone to process big spatial data. SpatialHadoop is available for download at http://spatialhadoop.cs.umn.edu, along with setup instructions, tutorials, and real datasets to use.

Bio: Ahmed Eldawy is a Ph.D. candidate in Computer Science and Engineering at the University of Minnesota. His research interests lie in the broad area of databases with a focus on big data management. Ahmed is the main architect and designer of SpatialHadoop open-source system, which got a worldwide popularity with 80,000 downloads within a year, and finally licensed to Eclipse Foundation. His work has been published and demonstrated in VLDB, SIGMOD, ICDE, and SIGSPATIAL conferences. Ahmed has extensive industry experience with three summer internships at Microsoft Research and IBM Watson Lab. He was selected as a finalist for Symantec Graduate Fellowship and ACM SIGMOD Programming Contest. Ahmed has received the Doctoral Dissertation Fellowship and the Quality Metrics Fellowship from the University of Minnesota in 2014 and 2015, respectively. For more information, please refer to www.cs.umn.edu/~eldawy