Proactive Policy for Efficiently Updating Join Views on Continuous Queries Over Data Streams and Linked Data

Abstract

Modern data analytic systems benefit from the fusion of streaming data and linked data distributed on the Web. Accessing the linked data at query time is prohibited as usual due to its expensive cost. To reduce the high cost, most of the database systems have used a materialized view (a view) that stores local copies of the data. However, views by conventional maintenance policies such as immediate, deferred, and periodic fail to achieve high accuracy of answers to queries on data streams and linked data. To cope with the limitations, we propose a maintenance policy that releases expensive jobs of copying the latest version of linked data into views at the idle time. In other words, we pre-fetch a portion of linked data in advance according to their update pattern and query evaluation semantics. Our multiple maintenance policies that take into account changes of linked data alleviate the degradation of performance at run-time. Using real-world datasets we report that the proposed method has a significant improvement in terms of the response time, compared to the state-of-the-art methods.

Construction and Knowledge Mining of Traditional Chinese Medicine Ancient Books Bibliographic Abstracts Database Based on Genetic Algorithm and BP Neural Network

“…At present, the bibliographic database of TCMAB is mainly concentrated in colleges and universities of traditional Chinese medicine, scientific research institutes and their libraries, mainly to reveal the collection, serve teaching and scientific research. At present, many traditional Chinese medicine libraries and scientific research institutions have bibliographic databases in their collections of ancient books, but due to the inconsistency of standards, the depth and breadth of documents revealed by the database are also different [9][10][11][12][13][14]. For example, the Chinese medical code has collected more than 1000 major works of traditional Chinese medicine in the past dynasties.…”

A new solution for asynchronous incremental maintenance of materialized views

“…After the work [8], almost asynchronous incremental maintenance is studied for warehousing and distributed environment [12][13][14][15][16] employing a versioning mechanism of the database management systems. The work [12] delivers that in the very large scale distributed shared-nothing data storage systems, remote view tables are better for index, equijoin, and selection MV, while local ones are more useful for MV with aggregations so that those two types of MV implementation can provide a good tradeoff between system throughput and minimizing view staleness.…”

“…The work [13] shows the effectiveness of combining eager and lazy MV maintenance policies for social networking applications on a database management system using a distributed memory cache, but there is a tradeoff between accuracy and freshness of the MV. The work [14] tends to find the cost metric which helps to balance the accuracy, the latency, and the source utilization effectively for updating policies of MV with joins on continuous queries over data stream and linked data.…”

“…The MV manager uses generated SQL script and compiled trigger functions code in .dll to register trigger. All the codes implementing expressions (13) and (14) are synthesized at this stage. The structure "…((SELECT all_columns FROM new_table EX-CEPT SELECT all_collums FROM dnew_table) UNION SELECT all_collums FROM dold_table) AS table…" is used to implement expression (12) to access the pre-update state of a base table.…”