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About 2,804 papers for “distributed query processing”

Distributed Query Processing on the Web

Nalin Gupta Jayant, Jayant R. Haritsa · 2000

this paper, we present an alternative "query shipping" approach wherein queries emanating from the user-site are forwarded from one site to another on the Web, the query is processed at each recipient site, and the associated results are returned to the user. Our design does not require co-ordination from any "master site", making it a truly distributed scheme. It has been implemented as part of DIASPORA (DIstributed Answering System for Processing of Remote Agents), a new Java-based Web database system that is currently operational and is undergoing field trials on our campus network [2]

Cited by 0

Using constraints for distributed query processing

Jongpil Yoon · 2002

Constraints are combined with join operations to minimize the amount of data transmission required for distributed query processing. We identify and exploit two important concepts: reducers and abstractors. A constraint can serve as a reducer if it is a sufficient and/or necessary condition for a query. Through replacing a distributed query by a reducer, the query is converted to be processed only at the local site. This converted query, however, requires "compensation" if the constraint is not a necessarily sufficient condition of the query. Although the compensation of the converted query is typically of database tuples, it can also be of the form of abstraction. This paper also shows that a constraint serves as an abstractor to produce a cooperative answer.

Cited by 0

Distributed Query Processing using Suffix Arrays

Mauricio Marı́n, Gonzalo Navarro · 2003

Abstract. Suffix arrays are more efficient than inverted files for solving complex queries in a number of applications related to text databases. Examples arise when dealing with biological or musical data or with texts written in oriental languages, and when searching for phrases, approximate patterns and, in general, regular expressions involving separators. In this paper we propose algorithms for processing in parallel batches of queries upon distributed text databases. We present efficient alternatives for speeding up query processing using distributed realizations of suffix arrays. Empirical results obtained from natural language text on a cluster of PCs show that the proposed algorithms are efficient in practice. 1

Cited by 0

Improved Centralized XML Query Processing Using Distributed Query Workload

Samini Subramaniam, Su-Cheng Haw, Lay-Ki Soon · Greater South Information System · 2021

eXtensible Markup Language (XML) is used widely to transfer data among a wide variety of systems.Due to an increase in query workloads and management of larger datasets, centralized processing is no longer feasible for XML query processing.To address this issue, we propose a technique that improves XML query processing through query workload distribution.An effective distributed XML query processing can be affected by several criteria such as indexing, fragmentation, distribution strategy, and well as the query handling in the distributed servers.However, we believe that an efficient labeling mechanism and an inexpensive centralized query processors or a pruning method at dedicated servers contribute greatly to the overall performance of a distributed query processor.In this paper, we present an effective centralized pruning technique that is adopted into our proposed distributed XML query processing technique to process XML queries robustly.Experimental evaluations showed that the proposed distributed query processor superseded the performance of centralized query processor.

Cited by 0Open access

Improved Centralized XML Query Processing Using Distributed Query Workload

Samini Subramaniam, Su-Cheng Haw, Lay-Ki Soon · Greater South Information System · 2021

eXtensible Markup Language (XML) is used widely to transfer data among a wide variety of systems.Due to an increase in query workloads and management of larger datasets, centralized processing is no longer feasible for XML query processing.To address this issue, we propose a technique that improves XML query processing through query workload distribution.An effective distributed XML query processing can be affected by several criteria such as indexing, fragmentation, distribution strategy, and well as the query handling in the distributed servers.However, we believe that an efficient labeling mechanism and an inexpensive centralized query processors or a pruning method at dedicated servers contribute greatly to the overall performance of a distributed query processor.In this paper, we present an effective centralized pruning technique that is adopted into our proposed distributed XML query processing technique to process XML queries robustly.Experimental evaluations showed that the proposed distributed query processor superseded the performance of centralized query processor.

Cited by 0Open access

Improved Centralized XML Query Processing Using Distributed Query Workload

Samini Subramaniam, Su-Cheng Haw, Lay-Ki Soon · IEEE Access · 2021

eXtensible Markup Language (XML) is used widely to transfer data among a wide variety of systems. Due to an increase in query workloads and management of larger datasets, centralized processing is no longer feasible for XML query processing. To address this issue, we propose a technique that improves XML query processing through query workload distribution. An effective distributed XML query processing can be affected by several criteria such as indexing, fragmentation, distribution strategy, and well as the query handling in the distributed servers. However, we believe that an efficient labeling mechanism and an inexpensive centralized query processors or a pruning method at dedicated servers contribute greatly to the overall performance of a distributed query processor. In this paper, we present an effective centralized pruning technique that is adopted into our proposed distributed XML query processing technique to process XML queries robustly. Experimental evaluations showed that the proposed distributed query processor superseded the performance of centralized query processor.

Cited by 9Open access

Distributed Arrays – An Algebra for Generic Distributed Query Processing

Güting, Ralf, Behr, Thomas, Nidzwetzki, Jan · University Library Hagen (UB Hagen) · 2020

We propose a simple model for distributed query processing based on the concept of a distributed array. Such an array has fields of some data type whose values can be stored on different machines. It offers operations to manipulate all fields in parallel within the distributed algebra. Distributed arrays rest on a given set of data types and operations called the basic algebra implemented by some piece of software called the basic engine. It can create and delete objects of such types and evaluate expressions (queries) over objects, constants, and operations of the basic algebra. Data types comprise simple types such as integers or strings, but also relations or indexes on disk or in memory. Hence a basic engine provides a complete environment for query processing on a single machine. We assume this environment is also extensible by types and operations. Operations on distributed arrays are implemented by one basic engine called the master which controls a set of basic engines called the workers. It maps operations on distributed arrays to the respective operations on their fieelds executed by workers. The distributed algebra is completely generic: any type or operation added in the extensible basic engine will be immediately available for distributed query processing. To demonstrate the use of the distributed algebra as a language for distributed query processing, we describe a fairly complex algorithm for distributed density-based similarity clustering. The algorithm is a novel contribution by itself. Its complete implementationmis shown in terms of the distributed algebra and the basic algebra. As a basic engine thenSecondo system is used, a rich environment for extensible query processing, providing useful tools such as main memory M-trees, graphs, or a DBScan implementation.

Cited by 0Open access

Query Compilation based Distributed Morsel-driven Parallel Spatial Query Processing

Rahul Sahni, Xiaozheng Zhang, Sudip Chatterjee et al. · 2024

Driven by the need to support spatial data applications, most relational databases offer spatial SQL query features. However, traditional relational databases are not scalable, and their query processing follows a pull-based tuple-at-a-time model, which is not efficient for large data volumes. Although several specialized spatial data processing systems were developed by extending frameworks, such as Spark and Hadoop, these systems offer limited or no support for spatial SQL query execution. The few systems that support SQL querying, suffer from the overheads of the pull-based model.

Cited by 1