Many big data applications such as smart transportation, healthcare, and e-commerce need to store and query large collections of small xml documents, which has become a fundamental problem. However, existing solutions...
详细信息
Many big data applications such as smart transportation, healthcare, and e-commerce need to store and query large collections of small xml documents, which has become a fundamental problem. However, existing solutions are inadequate to deliver satisfactory query performance in such circumstances. In this paper, we propose a framework named xml2HBase to address this problem using HBase, a widely deployed NoSQL database. Within this framework, we design a novel encodingscheme called Pathed-Dewey Order and a two-layer mapping method to store xml documents in HBase tables. xml queries, which are represented as XPath expressions, are evaluated through their translation into queries over HBase tables. Based on an in-depth analysis of the characteristics of the proposed approach, we design and integrate four optimization strategies to reduce storage space and query response time. Extensive experiments on two well-known xml benchmarks demonstrate the superior performance of xml2HBase over three state-of-the-art methods. (C) 2021 Elsevier Inc. All rights reserved.
In the domain of manufacture and logistics, Radio Frequency Identification (RFID) holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight due to an enhanced...
详细信息
ISBN:
(纸本)9780878492992
In the domain of manufacture and logistics, Radio Frequency Identification (RFID) holds the promise of real-time identifying, locating, tracking and monitoring physical objects without line of sight due to an enhanced efficiency, accuracy, and preciseness of object identification, and can be used for a wide range of pervasive computing applications. To achieve these goals, RFID data has to be collected, filtered, and transformed into semantic application data. However, the amount of RFID data is huge. Therefore, it requires much time to extract valuable information from RFID data for object tracing. This paper specifically explores options for modeling and utilizing RFID data set by xml-encoding for tracking queries and path oriented queries. We then propose a method which translates the queries to SQL queries. Based on the xml-encodingscheme, we devise a storage scheme to process tracking queries and path oriented queries efficiently. Finally, we realize the method by programming in a software system for manufacture and logistics laboratory. The system shows that our approach can process the tracing or path queries efficiently.
暂无评论