On the Expressivity of ASK Queries in SPARQL

As a major query type in SPARQL, ASK queries are boolean queries and have found applications in several domains such as semantic SPARQL optimization. This paper is a first systematic study of the relative expressive power of various fragments of ASK queries in SPARQL. Among many new results, a surprising one is that the operator UNION is redundant for ASK queries. The results in this paper as a whole paint a rich picture for the expressivity of fragments of ASK queries with the four basic operators of SPARQL 1.0 possibly together with a negation. The work in this paper provides a guideline for future SPARQL query optimization and implementation.

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An Optimal Framework for Spatial Query Optimization Using Hadoop in Big Data Analytics

Recent Patents on Computer Science ◽

10.2174/2213275912666190419215231 ◽

2019 ◽

Vol 12 ◽

Author(s):

Pankaj Dadheech ◽

Dinesh Goyal ◽

Sumit Srivastava ◽

Ankit Kumar

Keyword(s):

Big Data ◽

Query Optimization ◽

Spatial Data ◽

Spatial Information ◽

Big Data Analytics ◽

Spatial Query ◽

Data Process ◽

Boolean Queries ◽

Spatial Query Optimization ◽

Hadoop System

Spatial queries frequently used in Hadoop for significant data process. However, vast and massive size of spatial information makes it difficult to process the spatial inquiries proficiently, so they utilized the Hadoop system for process Big Data. We have used Boolean Queries & Geometry Boolean Spatial Data for Query Optimization using Hadoop System. In this paper, we show a lightweight and adaptable spatial data index for big data which will process in Hadoop frameworks. Results demonstrate the proficiency and adequacy of our spatial ordering system for various spatial inquiries.

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Query Optimization of Distributed RDF Data Based on MapReduce

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.441.970 ◽

2013 ◽

Vol 441 ◽

pp. 970-973

Author(s):

Yan Qin Zhang ◽

Jing Bin Wang

Keyword(s):

Query Optimization ◽

Query Language ◽

Sparql Query ◽

Query Execution ◽

Data Set ◽

Greedy Strategy ◽

Lehigh University ◽

Join Algorithm ◽

Simple Protocol ◽

Rdf Data

As the development of the semantic web, RDF data set has grown rapidly, thus causing the query problem of massive RDF. Using distributed technique to complete the SPARQL (Simple Protocol and RDF Query Language) Query is a new way of solving the large amounts of RDF query problem. At present, most of the RDF query strategies based on Hadoop have to use multiple MapReduce jobs to complete the task, resulting in waste of time. In order to overcome this drawback, MRQJ (using MapReduce to query and join) algorithm is proposed in the paper, which firstly uses a greedy strategy to generate join plan, then only one MapReduce job should be created to get the query results in SPARQL query execution. Finally, a contrast experiment on the LUBM (Lehigh University Benchmark) test data set is conducted, the results of which show that MRQJ method has a great advantage in the case that the query is more complicated.

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SPARQL Query Optimization on Top of DHTs

Lecture Notes in Computer Science - The Semantic Web – ISWC 2010 ◽

10.1007/978-3-642-17746-0_27 ◽

2010 ◽

pp. 418-435 ◽

Cited By ~ 23

Author(s):

Zoi Kaoudi ◽

Kostis Kyzirakos ◽

Manolis Koubarakis

Keyword(s):

Query Optimization ◽

Sparql Query

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Distance-Based Triple Reordering for SPARQL Query Optimization

2017 IEEE 33rd International Conference on Data Engineering (ICDE) ◽

10.1109/icde.2017.227 ◽

2017 ◽

Cited By ~ 3

Author(s):

Marios Meimaris ◽

George Papastefanatos

Keyword(s):

Query Optimization ◽

Sparql Query

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From Relation Algebra to Semi-join Algebra: An Approach to Graph Query Optimization

The Computer Journal ◽

10.1093/comjnl/bxaa031 ◽

2020 ◽

Author(s):

Jelle Hellings ◽

Catherine L Pilachowski ◽

Dirk Van Gucht ◽

Marc Gyssens ◽

Yuqing Wu

Keyword(s):

Query Optimization ◽

Relation Algebra ◽

Expressive Power ◽

Query Languages ◽

Query Evaluation ◽

Relation Algebras ◽

Ordered Trees ◽

Graph Query ◽

Study Techniques ◽

The Relationship

Abstract Many graph query languages rely on composition to navigate graphs and select nodes of interest, even though evaluating compositions of relations can be costly. Often, this need for composition can be reduced by rewriting toward queries using semi-joins instead, resulting in a significant reduction of the query evaluation cost. We study techniques to recognize and apply such rewritings. Concretely, we study the relationship between the expressive power of the relation algebras, which heavily rely on composition, and the semi-join algebras, which replace composition in favor of semi-joins. Our main result is that each fragment of the relation algebras where intersection and/or difference is only used on edges (and not on complex compositions) is expressively equivalent to a fragment of the semi-join algebras. This expressive equivalence holds for node queries evaluating to sets of nodes. For practical relevance, we exhibit constructive rules for rewriting relation algebra queries to semi-join algebra queries and prove that they lead to only a well-bounded increase in the number of steps needed to evaluate the rewritten queries. In addition, on sibling-ordered trees, we establish new relationships among the expressive power of Regular XPath, Conditional XPath, FO-logic and the semi-join algebra augmented with restricted fixpoint operators.

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