This paper presents ST-Hadoop; the first full-fledged open-source MapReduce framework with a native support for spatio-temporal data. ST-Hadoop is a comprehensive extension to Hadoop and SpatialHadoop that injects spatio-temporal data awareness inside each of their layers, mainly, language, indexing, and operations layers. In the language layer, ST-Hadoop provides built in spatio-temporal data types and operations. In the indexing layer, ST-Hadoop spatiotemporally loads and divides data across computation nodes in Hadoop Distributed File System in a way that mimics spatio-temporal index structures, which result in achieving orders of magnitude better performance than Hadoop and SpatialHadoop when dealing with spatio-temporal data and queries. In the operations layer, ST-Hadoop shipped with support for two fundamental spatio-temporal queries, namely, spatio-temporal range and join queries. Extensibility of ST-Hadoop allows others to expand features and operations easily using similar approach described in the paper. Extensive experiments conducted on large-scale dataset of size 10Â TB that contains over 1 Billion spatio-temporal records, to show that ST-Hadoop achieves orders of magnitude better performance than Hadoop and SpaitalHadoop when dealing with spatio-temporal data and operations. The key idea behind the performance gained in ST-Hadoop is its ability in indexing spatio-temporal data within Hadoop Distributed File System.
|Original language||English (US)|
|Title of host publication||Advances in Spatial and Temporal Databases - 15th International Symposium, SSTD 2017, Proceedings|
|Editors||Wei-Shinn Ku, Agnes Voisard, Haiquan Chen, Chang-Tien Lu, Siva Ravada, Matthias Renz, Yan Huang, Michael Gertz, Liang Tang, Chengyang Zhang, Erik Hoel, Xiaofang Zhou|
|Number of pages||21|
|State||Published - 2017|
|Event||15th International Symposium on Spatial and Temporal Databases, SSTD 2017 - Arlington, United States|
Duration: Aug 21 2017 → Aug 23 2017
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||15th International Symposium on Spatial and Temporal Databases, SSTD 2017|
|Period||8/21/17 → 8/23/17|
Bibliographical noteFunding Information:
This work is partially supported by the National Science Foundation, USA, under Grants IIS-1525953, CNS-1512877, IIS-1218168, and by a scholarship from the College of Computers & Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia.
© Springer International Publishing AG 2017.