TrajMesa: A Distributed NoSQL Storage Engine for Big Trajectory Data
2020 IEEE 36TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2020)(2020)
摘要
Trajectory data is very useful for many urban applications. However, due to its spatio-temporal and high-volume properties, it is challenging to manage trajectory data. Existing trajectory data management frameworks suffer from scalability problem, and only support limited trajectory queries. This paper proposes a holistic distributed NoSQL trajectory storage engine, TrajMesa, based on GeoMesa, an open-source indexing toolkit for spatio-temporal data. TrajMesa adopts a novel storage schema, which reduces the storage size tremendously. We also devise novel indexing key designs, and propose a bunch of pruning strategies. TrajMesa can support plentiful queries efficiently, including ID-Temporal query, spatial range query, similarity query, and k-NN query. Experimental results show the powerful query efficiency and scalability of TrajMesa.
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关键词
TrajMesa,distributed NoSQL storage engine,big trajectory data,urban applications,high-volume properties,trajectory queries,open-source indexing toolkit,spatio-temporal data,storage schema,storage size,spatial range query,query efficiency,ID-temporal query,distributed NoSQL trajectory storage engine,trajectory data management,GeoMesa,indexing key designs,pruning strategies,similarity query,k-NN query
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