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 STHadoop, 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.
|Original language||English (US)|
|Number of pages||4|
|Journal||Proceedings of the VLDB Endowment|
|State||Published - Aug 1 2017|
|Event||43rd International Conference on Very Large Data Bases, VLDB 2017 - Munich, Germany|
Duration: Aug 28 2017 → Sep 1 2017
Bibliographical notePublisher Copyright:
© 2017 VLDB.