China
Africa
Explore chapters and articles related to this topic
Data Aggregation in Wireless Sensor Networks
Published in Ankur Dumka, Sandip K. Chaurasiya, Arindam Biswas, Hardwari Lal Mandoria, A Complete Guide to Wireless Sensor Networks, 2019
Ankur Dumka, Sandip K. Chaurasiya, Arindam Biswas, Hardwari Lal Mandoria
Query optimization is related to relational database management systems (RDBMSs) for transmission of query. Query optimization helps in quick processing of query, minimizing per query cost, increases the performance of process, provides effective procedures for database engine, and also uses less memory. There are two types of query optimization: logical optimization and physical optimization. Logical optimization is used to create a series of relational database whereas physical optimization establishes the functions for effectual query processing.
Multi connection query optimization in data warehouse dependent on multiple linear regression algorithm
Published in International Journal of Computers and Applications, 2019
If several queries cannot be shared, it is clear that the overall cost of the MCQODW strategy is the smallest. And it can be seen that for the registration and deletion of queries, Algorithms 1 and 2 can easily adjust the query plan. From the discussion in Figure 1, it can be known that there are two kinds of methods for the multi connection query optimization of the data warehouse: (1) n-ary DR, that is, whether to update the query plan is determined in accordance with the adjusted cost; (2) MCQODW strategy. Obviously, when the weight is close to the first method, relatively good performance can be obtained. In the next section, the worst case performance under the MCQODW strategy is analyzed in two scenarios as the following.
Optimizing segmented trajectory data storage with HBase for improved spatio-temporal query efficiency
Published in International Journal of Digital Earth, 2023
Yi Bao, Zhou Huang, Xuri Gong, Yuyang Zhang, Ganmin Yin, Han Wang
The trajectory storage and management, as the basis of computation and mining, can provide the function of trajectory data storage and basic query, and plays an important role in various fields of trajectory data application. We have investigated the trajectory segments storage method and its associated optimization techniques in a distributed NoSQL database, covering aspects such as segmentation, indexing, serialization, query optimization, and calculation. Based on the HBase database, we implement the prototype system of segmented trajectory storage, verify the effect of various designs and optimizations with real data, and compare it with Geomesa to show the advantages and characteristics of the segmented storage model.