Query Processing over Incomplete Databases PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Query Processing over Incomplete Databases PDF full book. Access full book title Query Processing over Incomplete Databases by Yunjun Gao. Download full books in PDF and EPUB format.
Author: Yunjun Gao Publisher: Springer Nature ISBN: 303101863X Category : Computers Languages : en Pages : 106
Book Description
Incomplete data is part of life and almost all areas of scientific studies. Users tend to skip certain fields when they fill out online forms; participants choose to ignore sensitive questions on surveys; sensors fail, resulting in the loss of certain readings; publicly viewable satellite map services have missing data in many mobile applications; and in privacy-preserving applications, the data is incomplete deliberately in order to preserve the sensitivity of some attribute values. Query processing is a fundamental problem in computer science, and is useful in a variety of applications. In this book, we mostly focus on the query processing over incomplete databases, which involves finding a set of qualified objects from a specified incomplete dataset in order to support a wide spectrum of real-life applications. We first elaborate the three general kinds of methods of handling incomplete data, including (i) discarding the data with missing values, (ii) imputation for the missing values, and (iii) just depending on the observed data values. For the third method type, we introduce the semantics of k-nearest neighbor (kNN) search, skyline query, and top-k dominating query on incomplete data, respectively. In terms of the three representative queries over incomplete data, we investigate some advanced techniques to process incomplete data queries, including indexing, pruning as well as crowdsourcing techniques.
Author: Yunjun Gao Publisher: Springer Nature ISBN: 303101863X Category : Computers Languages : en Pages : 106
Book Description
Incomplete data is part of life and almost all areas of scientific studies. Users tend to skip certain fields when they fill out online forms; participants choose to ignore sensitive questions on surveys; sensors fail, resulting in the loss of certain readings; publicly viewable satellite map services have missing data in many mobile applications; and in privacy-preserving applications, the data is incomplete deliberately in order to preserve the sensitivity of some attribute values. Query processing is a fundamental problem in computer science, and is useful in a variety of applications. In this book, we mostly focus on the query processing over incomplete databases, which involves finding a set of qualified objects from a specified incomplete dataset in order to support a wide spectrum of real-life applications. We first elaborate the three general kinds of methods of handling incomplete data, including (i) discarding the data with missing values, (ii) imputation for the missing values, and (iii) just depending on the observed data values. For the third method type, we introduce the semantics of k-nearest neighbor (kNN) search, skyline query, and top-k dominating query on incomplete data, respectively. In terms of the three representative queries over incomplete data, we investigate some advanced techniques to process incomplete data queries, including indexing, pruning as well as crowdsourcing techniques.
Author: W. Kim Publisher: Springer Science & Business Media ISBN: 3642823750 Category : Computers Languages : en Pages : 367
Book Description
This book is an anthology of the results of research and development in database query processing during the past decade. The relational model of data provided tremendous impetus for research into query processing. Since a relational query does not specify access paths to the stored data, the database management system (DBMS) must provide an intelligent query-processing subsystem which will evaluate a number of potentially efficient strategies for processing the query and select the one that optimizes a given performance measure. The degree of sophistication of this subsystem, often called the optimizer, critically affects the performance of the DBMS. Research into query processing thus started has taken off in several directions during the past decade. The emergence of research into distributed databases has enormously complicated the tasks of the optimizer. In a distributed environment, the database may be partitioned into horizontal or vertical fragments of relations. Replicas of the fragments may be stored in different sites of a network and even migrate to other sites. The measure of performance of a query in a distributed system must include the communication cost between sites. To minimize communication costs for-queries involving multiple relations across multiple sites, optimizers may also have to consider semi-join techniques.
Author: Yunjun Gao Publisher: Morgan & Claypool ISBN: 9781681734224 Category : Computers Languages : en Pages : 122
Book Description
Incomplete data is part of life and almost all areas of scientific studies. Users tend to skip certain fields when they fill out online forms; participants choose to ignore sensitive questions on surveys; sensors fail, resulting in the loss of certain readings; publicly viewable satellite map services have missing data in many mobile applications; and in privacy-preserving applications, the data is incomplete deliberately in order to preserve the sensitivity of some attribute values. Query processing is a fundamental problem in computer science, and is useful in a variety of applications. In this book, we mostly focus on the query processing over incomplete databases, which involves finding a set of qualified objects from a specified incomplete dataset in order to support a wide spectrum of real-life applications. We first elaborate the three general kinds of methods of handling incomplete data, including (i) discarding the data with missing values, (ii) imputation for the missing values, and (iii) just depending on the observed data values. For the third method type, we introduce the semantics of k-nearest neighbor (kNN) search, skyline query, and top-k dominating query on incomplete data, respectively. In terms of the three representative queries over incomplete data, we investigate some advanced techniques to process incomplete data queries, including indexing, pruning as well as crowdsourcing techniques.
Author: Lei Chen Publisher: Springer Nature ISBN: 3031018966 Category : Computers Languages : en Pages : 91
Book Description
Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real applications. However, query processing techniques for deterministic data cannot be directly applied to uncertain data because they do not have mechanisms to handle data uncertainty. Therefore, efficient and effective manipulation of uncertain data is a practical yet challenging research topic. In this book, we start from the data models for imprecise and uncertain data, move on to defining different semantics for queries on uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book serves as a comprehensive guideline for query processing over uncertain databases. Table of Contents: Introduction / Uncertain Data Models / Spatial Query Semantics over Uncertain Data Models / Spatial Query Processing over Uncertain Databases / Conclusion
Author: Bruhathi Handanahal Sundarmurthy Publisher: ISBN: Category : Languages : en Pages : 0
Book Description
There are numerous challenges in distributed query processing. The focus of this thesis is to provide solutions to three problem areas: (a) querying incomplete data, (b) approximate query processing (AQP) over subsets of data, and (c) high cost of shuffling data while processing distributed queries. In distributed databases, large volumes of data are generally stored partitioned across multiple nodes and a user query typically spans many nodes. As the number of nodes accessed by a query increases, the probability of nodes being unavailable also increases; additionally, the amount of data shuffled across nodes also increases, thus increasing communication costs. To provide fast responses to queries over distributed databases, AQP has been proposed. In AQP, queries are processed over a representative subset of the database and estimates of the query result are provided along with confidence bounds. While AQP provides estimates of query results in a fraction of the time required to run the query over all data, quickly obtaining representative samples for a query in a distributed setting is challenging. We first consider the problem of querying over incomplete data. In failure and straggler scenarios, parts of the database that are still available form an incomplete database. We propose m-tables, a new representation system for representing and querying over incomplete databases. Next, we consider the problem of AQP over subsets of data. We propose the ASAP (Approximation Strategies for Aggregate queries through Partitioning) framework to provide estimates and confidence bounds for aggregate queries using any subset of a database when the database is co-hash partitioned. A database is co-hash partitioned when some tables are hash partitioned, and the remaining tables are co-located through join predicates. Finally, we study the problem of high cost of shuffling data across nodes for distributed query processing. Ideally, given a query and data distribution, we want to execute the query without any communication: in this case, the query is said to be parallel-correct w.r.t. the distribution. We again consider co-hash distribution schemes and as our main result, we determine the conditions for a given query to be parallel-correct for a given co-hash distribution scheme.
Author: Amol Deshpande Publisher: Now Publishers Inc ISBN: 1601980345 Category : Computers Languages : en Pages : 156
Book Description
Adaptive Query Processing surveys the fundamental issues, techniques, costs, and benefits of adaptive query processing. It begins with a broad overview of the field, identifying the dimensions of adaptive techniques. It then looks at the spectrum of approaches available to adapt query execution at runtime - primarily in a non-streaming context. The emphasis is on simplifying and abstracting the key concepts of each technique, rather than reproducing the full details available in the papers. The authors identify the strengths and limitations of the different techniques, demonstrate when they are most useful, and suggest possible avenues of future research. Adaptive Query Processing serves as a valuable reference for students of databases, providing a thorough survey of the area. Database researchers will benefit from a more complete point of view, including a number of approaches which they may not have focused on within the scope of their own research.
Author: Yunjun Gao
Author: Yunjun Gao
Author: Sheldon Hsienlin Shen
Author: Sheldon Hsienlin Shen
Author: W. Kim
Author: Sheldon Hsienlin Shen
Author: Yunjun Gao
Author: Lei Chen
Author: Bruhathi Handanahal Sundarmurthy
Author: Rutgers University. Department of Computer Science
Author: Amol Deshpande