| COMPUTER SCIENCE AND TECHNOLOGY |
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Time-series data aggregation index |
| HUANG Xiangdong1, ZHENG Liangfan1, QIU Mingming1, ZHANG Jinrui1, WANG Jianmin1,2 |
1. School of Software, Tsinghua University, Beijing 100084, China;
2. Tsinghua National Laboratory for Information Science and Technology(TNList), Beijing 100084, China |
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Abstract Time-series data is the key to industrial development, with the aggregation of the data an important step in practice. However, traditional relational databases fail to support vast amounts of time-series data. The NoSQL databases are inefficient and require time-consuming calculation to aggregate of time-series data. This paper presents an efficient index mechanism that supports time-series data aggregation by combining a synopsis table and a segment tree. A query algorithm based on this mechanism introduces the synopsis table into the NoSQL database and builds a segment tree from the synopsis table for archiving that is lbn the size of the original query set. This query algorithm can directly locate a series of index data to be queried without the recursive operations in traditional trees and effectively reduces I/O overhead. This study shows the efficiency of this index mechanism by comparisons with general index mechanisms.
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| Keywords
index
aggregate operation
time-series data
synopsis table
segment tree
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Issue Date: 15 March 2016
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2016,
Vol. 56
