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A Demonstration of ST-Hadoop: A MapReduce Framework for Big Spatio-temporal Data

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PROCEEDINGS OF THE VLDB ENDOWMENT
卷 10, 期 12, 页码 1961-1964

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ASSOC COMPUTING MACHINERY
DOI: 10.14778/3137765.3137819

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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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