Storage and Use of Provenance Information for Relational Database Queries

2011 ◽  
pp. 429-433
Author(s):  
Zhifeng Bao ◽  
Henning Koehler ◽  
Xiaofang Zhou ◽  
Tok Wang Ling
Keyword(s):  
Relational Database ◽  
Database Queries ◽  
Provenance Information

scholarly journals Multi-objective database queries in combined knapsack and set covering problem domains

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Sean A. Mochocki ◽  
Gary B. Lamont ◽  
Robert C. Leishman ◽  
Kyle J. Kauffman
Keyword(s):  
Relational Database ◽  
Set Covering ◽  
Covering Problem ◽  
Set Covering Problem ◽  
Database Queries ◽  
Multi Objective ◽  
Data Representations ◽  
Np Hard Problem ◽  
Institute Of Technology ◽  
The One

AbstractDatabase queries are one of the most important functions of a relational database. Users are interested in viewing a variety of data representations, and this may vary based on database purpose and the nature of the stored data. The Air Force Institute of Technology has approximately 100 data logs which will be converted to the standardized Scorpion Data Model format. A relational database is designed to house this data and its associated sensor and non-sensor metadata. Deterministic polynomial-time queries were used to test the performance of this schema against two other schemas, with databases of 100 and 1000 logs of repeated data and randomized metadata. Of these approaches, the one that had the best performance was chosen as AFIT’s database solution, and now more complex and useful queries need to be developed to enable filter research. To this end, consider the combined Multi-Objective Knapsack/Set Covering Database Query. Algorithms which address The Set Covering Problem or Knapsack Problem could be used individually to achieve useful results, but together they could offer additional power to a potential user. This paper explores the NP-Hard problem domain of the Multi-Objective KP/SCP, proposes Genetic and Hill Climber algorithms, implements these algorithms using Java, populates their data structures using SQL queries from two test databases, and finally compares how these algorithms perform.

Analysis of Service Compatibility

2010 ◽  
pp. 136-155
Author(s):  
Ken Q. Pu
Keyword(s):  
Relational Database ◽  
Type System ◽  
Large Family ◽  
Service Description ◽  
Worst Case ◽  
Database Queries ◽  
Unification Algorithm ◽  
Data Services ◽  
Wide Range ◽  
Unification Problem

In this chapter, the authors apply type-theoretic techniques to the service description and composition verification. A flexible type system is introduced for modeling instances and mappings of semi-structured data, and is demonstrated to be effective in modeling a wide range of data services, ranging from relational database queries to web services for XML. Type-theoretic analysis and verification are then reduced to the problem of type unification. Some (in)tractability results of the unification problem and the expressiveness of their proposed type system are presented in this chapter. Finally, the auhtors construct a complete unification algorithm which runs in EXP-TIME in the worst case, but runs in polynomial time for a large family of unification problems rising from practical type analysis of service compositions.

scholarly journals Multi-Objective Database Queries in Combined Knapsack and Set Covering Problem Domains

2020 ◽  
Author(s):  
Sean Mochocki ◽  
Gary Lamont ◽  
Robert Leishman ◽  
Kyle Kauffman
Keyword(s):  
Relational Database ◽  
Set Covering ◽  
Covering Problem ◽  
Set Covering Problem ◽  
Database Queries ◽  
Multi Objective ◽  
Data Representations ◽  
Np Hard Problem ◽  
Institute Of Technology ◽  
The One

Abstract Database queries are one of the most important functions of a relational database. Users are interested in viewing a variety of data representations, and this may vary based on database purpose and the nature of the stored data. The Air Force Institute of Technology has approximately 100 data logs which will be converted to the standardized Scorpion Data Model format. A relational database is designed to house this data and its associated sensor and non-sensor metadata. Deterministic polynomialtime queries were used to test the performance of this schema against two other schemas, with databases of 100 and 1000 logs of repeated data and randomized metadata. Of these approaches, the one that had the best performance was chosen as AFIT’s database solution, and now more complex and useful queries need to be developed to enable filter research. To this end, consider the combined Multi-Objective Knapsack-/Set Covering Database Query. Algorithms which address The Set Covering Problem or Knapsack Problem could be used individually to achieve useful results, but together they could offer additional power to a potential user. This paper explores the NP-Hard problem domain of the Multi-Objective KP/SCP, proposes Genetic and Hill Climber algorithms, implements these algorithms using Java, populates their data structures using SQL queries from two test databases, and finally compares how these algorithms perform.

scholarly journals Data dependencies for query optimization: a survey

2021 ◽  
Author(s):  
Jan Kossmann ◽  
Thorsten Papenbrock ◽  
Felix Naumann
Keyword(s):  
Query Optimization ◽  
Relational Database ◽  
Database Management ◽  
Optimization Techniques ◽  
Database Management System ◽  
Database Queries ◽  
Data Dependencies ◽  
Open Research ◽  
Core Feature ◽  
Research Questions

AbstractEffective query optimization is a core feature of any database management system. While most query optimization techniques make use of simple metadata, such as cardinalities and other basic statistics, other optimization techniques are based on more advanced metadata including data dependencies, such as functional, uniqueness, order, or inclusion dependencies. This survey provides an overview, intuitive descriptions, and classifications of query optimization and execution strategies that are enabled by data dependencies. We consider the most popular types of data dependencies and focus on optimization strategies that target the optimization of relational database queries. The survey supports database vendors to identify optimization opportunities as well as DBMS researchers to find related work and open research questions.

scholarly journals Queryng data in NoSQL databases

2019 ◽  
Vol 7 (1) ◽  
pp. 257-270
Author(s):  
Andrea Babić ◽  
Danijela Jakšić ◽  
Patrizia Poščić
Keyword(s):  
Relational Database ◽  
Database Queries ◽  
Nosql Databases ◽  
Related Research ◽  
Nosql Database

The goal of this paper is to give an overview of fundamental concepts and types of NoSQL databases, to show some examples of database queries, some related research, and the implementation of those queries in an original practical example. The introduction is a brief representation and description of the NoSQL database. There are also several comparisons of NoSQL database with the relational database. The next chapter contains a review of the basic NoSQL databases and their prototypes. In each of the following subchapters, the types of NoSQL databases are described in more detail and various queries which can be performed over them are presented. In the last chapter there is also a practical example of querying one of these databases.

FuzzyBase: A fuzzy logic aid for relational database queries

1995 ◽  
pp. 385-394 ◽  
Author(s):  
D. Gazzotti ◽  
L. Piancastelli ◽  
C. Sartori ◽  
D. Beneventano
Keyword(s):  
Fuzzy Logic ◽  
Relational Database ◽  
Database Queries
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