{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:02:18Z","timestamp":1760241738586,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,9,12]],"date-time":"2018-09-12T00:00:00Z","timestamp":1536710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFC0840200"],"award-info":[{"award-number":["2017YFC0840200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2017JBZ107"],"award-info":[{"award-number":["2017JBZ107"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Big data gathered from real systems, such as public infrastructure, healthcare, smart homes, industries, and so on, by sensor networks contain enormous value, and need to be mined deeply, which depends on a data storing and retrieving service. HBase is playing an increasingly important part in the big data environment since it provides a flexible pattern for storing extremely large amounts of unstructured data. Despite the fast-speed reading by RowKey, HBase does not natively support multi-conditional query, which is a common demand and operation in relational databases, especially for data analysis of ubiquitous sensing applications. In this paper, we introduce a method to construct a linear index by employing a Hilbert space-filling curve. As a RowKey generating schema, the proposed method maps multiple index-columns into a one-dimensional encoded sequence, and then constructs a new RowKey. We also provide a R-tree-based optimization to reduce the computational cost of encoding query conditions. Without using a secondary index mode, experimental results indicate that the proposed method has better performance in multi-conditional queries.<\/jats:p>","DOI":"10.3390\/s18093064","type":"journal-article","created":{"date-parts":[[2018,9,12]],"date-time":"2018-09-12T10:26:36Z","timestamp":1536747996000},"page":"3064","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Method of HBase Multi-Conditional Query for Ubiquitous Sensing Applications"],"prefix":"10.3390","volume":"18","author":[{"given":"Bo","family":"Shen","sequence":"first","affiliation":[{"name":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China"},{"name":"Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, Beijing 100031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi-Chen","family":"Liao","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Han-Chieh","family":"Chao","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Fujian University of Technology, Fuzhou 350118, China"},{"name":"School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430023, China"},{"name":"Department of Electrical Engineering, National Dong Hwa University, Hualien 97401, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Huang, B.X., Liu, A.F., Zhang, C.Y., Xiong, N.X., Zeng, Z.W., and Cai, Z.P. 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