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A demonstration of ST-hadoop: a MapReduce framework for big spatio-temporal data

Published:01 August 2017Publication History
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Abstract

This demo presents ST-Hadoop; the first full-fledged open-source MapReduce framework with a native support for spatio-temporal data. ST-Hadoop injects spatio-temporal awareness in the Hadoop base code, which results in achieving order(s) of magnitude better performance than Hadoop and SpatialHadoop when dealing with spatio-temporal data and queries. The key idea behind ST-Hadoop is its ability in indexing spatio-temporal data within Hadoop Distributed File System (HDFS). A real system prototype of ST-Hadoop, running on a local cluster of 24 machines, is demonstrated with two big-spatio-temporal datasets of Twitter and NYC Taxi data, each of around one billion records.

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          cover image Proceedings of the VLDB Endowment
          Proceedings of the VLDB Endowment  Volume 10, Issue 12
          August 2017
          427 pages
          ISSN:2150-8097
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          VLDB Endowment

          Publication History

          • Published: 1 August 2017
          Published in pvldb Volume 10, Issue 12

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