Abstract
Interval queries are widely used in social networks, information retrieval and database domains. As an important query type, interval query has been explored in depth by researchers long ago. However, the works to study interval indexing and querying on cloud platform are few. The paper analyzes the shortcomings of existing work of interval indexing and searching on key-value store. To reduce the space overhead and respond time, we propose a new index structure and corresponding searching algorithms. The index structure takes full advantage of the features of key-value store to improve the query performance. The extensive experiments based on real and simulated data sets show that our approach is effective and efficient.
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Acknowledgments
Thank the author of paper [9] for sharing his source code. Our work is supported by “the Fundamental Research Funds for the Central Universities, No. 3132016031”, and “National Natural Science Foundation of China, No. 61371090 and No. 61073057”.
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Zhou, X., Zhang, J., Li, G. (2016). Efficient Interval Indexing and Searching on Cloud. In: Song, S., Tong, Y. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9998. Springer, Cham. https://doi.org/10.1007/978-3-319-47121-1_24
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DOI: https://doi.org/10.1007/978-3-319-47121-1_24
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