text: Time-efficient link discovery is of central importance to implement the vision of the Semantic Web. Some of the most rapid Link Discovery approaches rely internally on planning to execute link specifications. In newer works, linear models have been used to estimate the runtime the fastest planners. However, no other category of models has been studied for this purpose so far. In this paper, we study non-linear runtime estimation functions for runtime estimation. In particular, we study exponential and mixed models for the estimation of the runtimes of planners. To this end, we evaluate three different models for runtime on six datasets using 400 link specifications. We show that exponential and mixed models achieve better fits when trained but are only to be preferred in some cases. Our evaluation also shows that the use of better runtime approximation models has a positive impact on the overall execution of link specifications.
  @cite_9: Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software. This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.
  @cite_18: From the Publisher: This acclaimed revision of a classic database systems text offers a complete background in the basics of database design, languages, and system implementation. It provides the latest information combined with real-world examples to help readers master concepts. All concepts are presented in a technically complete yet easy-to-understand style with notations kept to a minimum. A running example of a bank enterprise illustrates concepts at work. To further optimize comprehension, figures and examples, rather than proofs, portray concepts and anticipate results.
  @cite_3: There has been extensive work in query optimization since the early ‘70s. It is hard to capture the breadth and depth of this large body of work in a short article. Therefore, I have decided to focus primarily on the optimization of SQL queries in relational database systems and present my biased and incomplete view of this field. The goal of this article is not to be comprehensive, but rather to explain the foundations and present samplings of significant work in this area. I would like to apologize to the many contributors in this area whose work I have failed to explicitly acknowledge due to oversight or lack of space. I take the liberty of trading technical precision for ease of presentation.
summary: The task of efficient query execution in database systems is similar to the task of execution optimization using runtime approximations in LD frameworks. Efficient and scalable data management has been of central importance in database systems @cite_9 . Over the past few years, there has been an extensive work on query optimization in databases that is based on statistical information about relations and intermediate results @cite_18 . The author of @cite_3 gives an analytic overview regarding the procedure of query optimization and the different approaches used at each step of the process.