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Hierarchical query execution in a parallel object-oriented database system

parallel COMPUTING 1996年第7期22卷 1017-1048页

作者： Bassiliades, N Vlahavas, I Department of Informatics Aristotle University of Thessaloniki 54006 Thessaloniki Greece

We present a hierarchical query execution strategy for a parallel object-oriented database (OODB) system. The system, named PRACTIC, is based on a concurrent active class management model and is mapped to an abstract hierarchical multiprocessor architecture. The proposed strategy is studied analytically and by simulation on a transputer-based machine, verifying the theoretical results. Although the analysis suits both main-memory and disk-based database systems, it becomes significant for main-memory systems where the multiprocessor initialization and communication overheads are comparable to the actual workload. The hierarchical query execution strategy is proved much better than the usual flat strategy of parallel database systems, except some clearly identified extreme cases, where flat processing is better. Furthermore, we propose a declustering scheme for space optimization to improve processor utilization and single-class query performance, by having different classes share memory and computation power of neighboring processing elements.

关键词： parallel main-memory database system object-oriented databases multiprocessor architecture parallel query execution analytic performance model simulation

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query execution scheduling in parallel object-oriented databases

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INFORMATION AND SOFTWARE TECHNOLOGY 1999年第3期41卷 163-178页

作者： Taniar, D Leung, CHC RMIT Univ Dept Comp Sci Melbourne Vic 3001 Australia Victoria Univ Technol Sch Commun & Informat Melbourne Vic 8001 Australia

Complex object-oriented queries generally consist of path expressions and explicit join operations. Since explicit join operations have been acknowledged as the most expensive operations, query executions normally start from the path expressions, Each path expression may form a sub-query. There are two existing strategies to sub-queries processing: 'serial' and 'parallel' execution scheduling strategies. Serial sub-queries execution corresponds to an execution of the sub-queries one-by-one, whereas parallel sub-queries execution corresponds to simultaneous execution of the sub-queries. When a sub-query is being processed, parallelization techniques may be applied. In this paper, we focus on the scheduling issues of the sub-queries, rather than the parallelization of the sub-queries themselves. Rules are formulated to guide the parallel query execution process. Our analysis shows that when there is no load skew, the serial scheduling strategy is preferred, otherwise the parallel scheduling strategy should be used. (C) 1999 Elsevier Science B.V. All lights reserved.

关键词： scheduling access plans parallel query execution parallel object-oriented databases

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CONTROL VERSUS DATA-FLOW IN parallel DATABASE MACHINES

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 1993年第11期4卷 1265-1279页

作者： TEEUW, WB BLANKEN, HM Department of Computer Science Information Systems-Databases University of Twente Enschede Netherlands

The execution of a query in a parallel database machine can be controlled in either a control flow way, or in a data flow way. In the former case a single system node controls the entire query execution. In the latter case the processes that execute the query, although possibly running on different nodes of the system, trigger each other. Lately, many database research projects focus on data Bow control since it should enhance response times and throughput. In this paper, we study control versus data flow with regard to controlling the execution of database queries. An analytical model is used to compare control and data flow in order to gain insights into the question which mechanism is better under which circumstances. Also, some systems using data how techniques are described, and we will investigate to which degree they are really data flow. Our results show that for particular types of queries data flow is very attractive, since it reduces the number of control messages and balances these messages over the nodes.

关键词： CONTROL FLOW DATA HOW DATABASE SYSTEM PERFORMANCE DISTRIBUTED DATABASES LOCAL AREA NETWORKS MESSAGE MANAGEMENT parallel query execution

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Extending a multi-set relational algebra to a parallel environment

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DISTRIBUTED AND parallel DATABASES 1996年第1期4卷 81-99页

作者： Grefen, PWPJ Flokstra, J University of Twente

parallel database systems will very probably be the future for high-performance data-intensive applications. In the past decade, many parallel database systems have been developed, together with many languages and approaches to specify operations in these systems. A common background is still missing, however. This paper proposes an extended relational algebra for this purpose, based on the well-known standard relational algebra. The extended algebra provides both complete database manipulation language features, and data distribution and process allocation primitives to describe parallelism. It is defined in terms of multi-sets of tuples to allow handling of duplicates and to obtain a close connection to the world of high-performance data processing. Due to its algebraic nature, the language is well suited for optimization and parallelization through expression rewriting. The proposed language can be used as a database manipulation language on its own, as has been done in the PRISMA parallel database project, or as a formal basis for other languages, like SQL.

关键词： relational algebra multi-set query optimization parallel query execution

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parallel visual information retrieval in VizIR

Parallel visual information retrieval in VizIR

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Conference on Internet Multimedia Management Systems V

作者： Eidenberger, H Vienna Univ Technol Inst Software Technol & Ineteract Syst A-1040 Vienna Austria

ISBN: (纸本)0819455547

This paper describes how parallel retrieval is implemented in the content-based visual information retrieval framework VizIR. Generally, two major use cases for parallelisation exist in visual retrieval systems: distributed querying and simultaneous multi-user querying. Distributed querying includes parallel query execution and querying multiple databases. Content-based querying is a two-step process: transformation of feature space to distance space using distance measures and selection of result set elements from distance space. parallel distance measurement is implemented by sharing example media and query parameters between querying threads. In VizIR, parallelisation is heavily based on caching strategies. querying multiple distributed databases is already supported by standard relational database management systems. The most relevant issues here are error handling and minimisation of network bandwidth consumption. Moreover, we describe strategies for distributed similarity measurement and content-based indexing. Simultaneous multi-user querying raises problems such as caching of querying results and usage of relevance feedback and user preferences for query refinement. We propose a 'real' multi-user querying environment that allows users to interact in defining queries and browse through result sets simultaneously. The proposed approach opens an entirely new field of applications for visual information retrieval systems.

关键词： content-based visual information retrieval parallel query execution peer to peer networks database design distributed databases reliability

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parallel and Distributed Intra query Transient Fault Tolerance Model via Parity Checking 14

Parallel and Distributed Intra Query Transient Fault Toleran...

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14th International Conference on Electronics Computer and Computation (ICECCO)

作者： Yusuf, Salisu Ibrahim Junaidu, Sahalu B. Nile Univ Nigeria Dept Comp Sci Abuja Nigeria Ahmadu Bello Univ Dept Comp Sci Abuja Nigeria

ISBN: (纸本)9781728101323

In a distributed parallel query execution, complex queries are executed by splitting them into partially related simple subqueries executing each on a different node, communication between machines is often done by message exchange for shared-nothing architecture based grid. Integrity of messages can be lost by temporary or permanent interference along the communication network. Fault tolerance strategies are used to keep the system running in the presence of fault. This is traditionally done through query restart, replication or check pointing and other variations of these approaches to improve latency, restoration time and reduce cost of execution. These processes include: monitoring, detection and tolerance. Transient faults are caused by interference in the medium of exchange which may pass undetected but yielding an incorrect query result. Moreover, the traditional fault tolerance, there is a strong dependency between the nodes. In this research we proposed a model of a fault tolerance strategy that will allow self-detection and tolerate transient fault with less dependency between nodes. The model will be compared with the tradition strategies in terms of detection ability, inter node dependency, and cost of execution.

关键词： Distributed query processing intra-query fault tolerance transient fault shared nothing parallel query execution

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Speeding up Spatial Database query execution using GPUs

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Procedia Computer Science 2012年 9卷 1870-1879页

作者： Bogdan Simion Suprio Ray Angela Demke Brown Department of Computer Science University of Toronto

Spatial databases are used in a wide variety of real-world applications, such as land surveying, urban planning, and environmental assessments, as well as geospatial Web services. As uses of spatial databases become more widespread, there is a growing need for good performance of spatial applications. In spatial workloads, queries tend to be computationally-intensive due to the complex processing of geometric relationships. Furthermore, a signiﬁcant fraction of spatial query execution time is spent on CPU stalls due to memory accesses, caused by the ever-increasing processor-memory speed gap. With the advent of massively-parallel graphics-processing hardware (GPUs) and frameworks like CUDA, opportunities for speeding up spatial processing have emerged. In addition to massive parallelism, GPUs can also better hide the memory *** aim to speed up spatial query execution using CUDA and recent GPU cards. One of the main challenges in using GPUs is the transfer time from main memory to GPU memory. We implement a set of six typical spatial queries and achieve a baseline speedup (without the transfer cost) of 62-318x over the CPU counterparts. We show that the transfer cost can be amortized over the execution of each individual query. For simpler spatial queries, the transfer time is a signiﬁcant fraction of the query execution time, but we still achieve a 6-10x speedup. For more complex spatial queries, the transfer time becomes negligible compared to the processing time, and we obtain a 62-240x speedup.

关键词： Spatial databases parallel query execution GPU processing

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