Query Optimization in the Databases Distributed by Means of Product Equivalence Relations

1988 ◽  
Vol 11 (3) ◽  
pp. 241-265
Author(s):  
W. Marek ◽  
C. Rauszer
Keyword(s):  
Query Optimization ◽  
Selection Process ◽  
Distributed Databases ◽  
Optimization Techniques ◽  
Equivalence Relations ◽  
Database Operations ◽  
By Products

In this paper, we address the problem of query optimization in distributed databases. We show that horizontal partitions of databases, generated by products of equivalence relations, induce optimization techniques for the basic database operations (i.e., the selection, projection, and join operators). In the case of selection, our method allows for restriction of the number of blocks to be searched in the selection process and subsequent simplification of the selection formula at each block. For the natural join operation, we propose an algorithm that reduces the computation of fragments. Proofs of the correctness of our algorithms are also included.

Coupling Materialized View Selection to Multi Query Optimization

2015 ◽  
Vol 11 (2) ◽  
pp. 62-84 ◽  
Author(s):  
Ahcene Boukorca ◽  
Ladjel Bellatreche ◽  
Sid-Ahmed Benali Senouci ◽  
Zoé Faget
Keyword(s):  
Query Optimization ◽  
Selection Process ◽  
Optimization Techniques ◽  
Global Processing ◽  
Materialized Views ◽  
Hard Problem ◽  
Graph Structure ◽  
View Selection ◽  
Materialized View ◽  
Materialized View Selection

Materialized views are queries whose results are stored and maintained in order to facilitate access to data in their underlying base tables of extremely large databases. Selecting the best materialized views for a given query workload is a hard problem. Studies on view selection have considered sharing common sub expressions and other multi-query optimization techniques. Multi-Query Optimization is a well-studied domain in traditional and advanced databases. It aims at optimizing a workload of queries by finding and reusing common sub-expression between queries. Finding the best shared expression is known as a NP-hard problem. The shared expressions usually identified by graph structure have been used to be candidate for materialized views. This shows the strong interdependency between the problems of materialized view selection (PVS) and multi query optimization (PMQO), since the PVS uses the graph structure of the PMQO. Exploring the existing works on PVS considering the interaction between PVS and PMQO figures two main categories of studies: (i) those considering the PMQO as a black box where the output is the graph and (ii) those preparing the graph to guide the materialized view selection process. In this category, the graph generation is based on individual query plans, an approach that does not scale, especially with the explosion of Big Data applications requiring large number of complex queries with high interaction. To ensure a scalable solution, this work proposes a new technique to generate a global processing plan without using individual plans by borrowing techniques used in the electronic design automation (EDA) domain. This paper first presents a rich state of art regarding the PVS and a classification of the most important existing work. Secondly, an analogy between the MQO problem and the EDA domain, in which large circuits are manipulated, is established. Thirdly, it proposes to model the problem with hypergraphs which are massively used to design and test integrated circuits. Fourthly, it proposes a deterministic algorithm to select materialized views using the global processing plan. Finally, experiments are conducted to show the scalability of our approach.

scholarly journals PatchIndex: exploiting approximate constraints in distributed databases

2021 ◽  
Author(s):  
Steffen Kläbe ◽  
Kai-Uwe Sattler ◽  
Stephan Baumann
Keyword(s):  
Data Analytics ◽  
Distributed Databases ◽  
Database Systems ◽  
Optimization Techniques ◽  
Cloud Data ◽  
Database Administrator ◽  
Small Set ◽  
Parallel Index ◽  
Access Data ◽  
Integrate Data

AbstractCloud data warehouse systems lower the barrier to access data analytics. These applications often lack a database administrator and integrate data from various sources, potentially leading to data not satisfying strict constraints. Automatic schema optimization in self-managing databases is difficult in these environments without prior data cleaning steps. In this paper, we focus on constraint discovery as a subtask of schema optimization. Perfect constraints might not exist in these unclean datasets due to a small set of values violating the constraints. Therefore, we introduce the concept of a generic PatchIndex structure, which handles exceptions to given constraints and enables database systems to define these approximate constraints. We apply the concept to the environment of distributed databases, providing parallel index creation approaches and optimization techniques for parallel queries using PatchIndexes. Furthermore, we describe heuristics for automatic discovery of PatchIndex candidate columns and prove the performance benefit of using PatchIndexes in our evaluation.

Composite Event Processing for Data Streams and Domain Knowledge

2011 ◽  
Vol 219-220 ◽  
pp. 927-931
Author(s):  
Jun Qiang Liu ◽  
Xiao Ling Guan
Keyword(s):  
Query Optimization ◽  
Data Streams ◽  
Domain Knowledge ◽  
Semantic Information ◽  
Query Language ◽  
Processing System ◽  
Optimization Techniques ◽  
Research Attention ◽  
Composite Event ◽  
Solid Foundation

In recent years the processing of composite event queries over data streams has attracted a lot of research attention. Traditional database techniques were not designed for stream processing system. Furthermore, example continuous queries are often formulated in declarative query language without specifying the semantics. To overcome these deficiencies, this article presents the design, implementation, and evaluation of a system that executes data streams with semantic information. Then, a set of optimization techniques are proposed for handling query. So, our approach not only makes it possible to express queries with a sound semantics, but also provides a solid foundation for query optimization. Experiment results show that our approach is effective and efficient for data streams and domain knowledge.

scholarly journals OPTIMAL SOLUTION FOR THE DISTRIBUTION OF BY-PRODUCTS IN DISPOSAL UNIT

2017 ◽  
Vol 5 (4RAST) ◽  
pp. 59-63 ◽  
Author(s):  
Jyothi P ◽  
Vatsala G A ◽  
Radha Gupta
Keyword(s):  
Waste Disposal ◽  
Goal Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Optimization Techniques ◽  
Programming Technique ◽  
Emerging Industries ◽  
Goal Programming Model ◽  
Net Profit ◽  
By Products

In present scenario, Waste disposal unit is one of the emerging industries. The process of collection of wastes, segregation of wastes, recycling the wastes and manufacturing by-products and selling the by-products are the major works are undertaken into consideration.  Any business expectation is to get the profit.  Our study is to formulate goal programming model which helps in maximizing the profit by identifying the deviation of goals in the disposal unit. Goal Programming technique is one of the optimization techniques. Manager of the disposal unit can takes the better decision using the deviation of goals. Pre emptive Goals of the study are (i) minimizing the expenditure of the unit and recycling cost of the wastes ii) boosting the net profit of the unit    iii) Maintaining the supply of by-products to each location within the maximum demand iv) Fulfilling demand of by- products in different locations v) Maintaining the minimum supply of recycled by-products to 5 different locations must be at least one.

Document SQL (DSQL)

2011 ◽  
pp. 316-344
Author(s):  
Arijit Sengupta ◽  
V. Ramesh
Keyword(s):  
Query Optimization ◽  
Ad Hoc ◽  
Query Language ◽  
Optimization Techniques ◽  
Order Logic ◽  
First Order Logic ◽  
Tree Structures ◽  
Easy Integration ◽  
Query Semantics ◽  
Theoretical Foundations

This chapter presents DSQL, a conservative extension of SQL, as an ad-hoc query language for XML. The development of DSQL follows the theoretical foundations of first order logic, and uses common query semantics already accepted for SQL. DSQL represents a core subset of XQuery that lends well to query optimization techniques; while at the same time allows easy integration into current databases and applications that use SQL. The intent of DSQL is not to replace XQuery, the current W3C recommended XML query language, but to serve as an ad-hoc querying frontend to XQuery. Further, the authors present proofs for important query language properties such as complexity and closure. An empirical study comparing DSQL and XQuery for the purpose of ad-hoc querying demonstrates that users perform better with DSQL for both flat and tree structures, in terms of both accuracy and efficiency.

Query Formation and Information Retrieval with Ontology

2007 ◽  
pp. 310-323
Author(s):  
Sheng-Uei Guan
Keyword(s):  
Genetic Algorithms ◽  
Information Retrieval ◽  
Query Optimization ◽  
Formation Process ◽  
Retrieval System ◽  
Mobile Commerce ◽  
Information Retrieval System ◽  
Optimization Techniques ◽  
Tree Structure ◽  
Retrieval Scheme

This chapter presents an ontology-based query formation and information retrieval system under the mobile commerce (m-commerce) agent framework. A query formation approach that combines the usage of ontology and keywords is implemented. This approach takes advantage of the tree structure in ontology to form queries visually and efficiently. It also uses additional aids such as keywords to complete the query formation process more efficiently. The proposed information retrieval scheme focuses on using genetic algorithms (GAs) to improve computational effectiveness. Other query optimization techniques used include query restructuring by logical terms and numerical constraints replacement.

A Query Beehive Algorithm for Data Warehouse Buffer Management and Query Scheduling

2014 ◽  
Vol 10 (3) ◽  
pp. 34-58 ◽  
Author(s):  
Amira Kerkad ◽  
Ladjel Bellatreche ◽  
Pascal Richard ◽  
Carlos Ordonez ◽  
Dominique Geniet
Keyword(s):  
Query Optimization ◽  
Buffer Management ◽  
Optimization Techniques ◽  
Materialized Views ◽  
Star Schema ◽  
Joint Problem ◽  
Fixed Order ◽  
Pass Through ◽  
Np Hardness ◽  
Query Scheduling

Analytical queries, like those used in data warehouses and OLAP, are generally interdependent. This is due to the fact that the database is usually modeled with a denormalized star schema or its variants, where most queries pass through a large central fact table. Such interaction has been largely exploited in query optimization techniques such as materialized views. Nevertheless, such approaches usually ignore buffer management and assume queries have a fixed order and are known in advance. We believe such assumptions are too strong and thus they need to be revisited and simplified. In this paper, we study the combination of two problems: buffer management and query scheduling, in both static and dynamic scenarios. We present an NP-hardness study of the joint problem, highlighting its complexity. We then introduce a new and highly efficient algorithm inspired by a beehive. We conduct an extensive experimental evaluation on a real DBMS showing the superiority of our algorithm compared to previous ones as well as its excellent scalability.

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