發(fā)布時間：2018-01-19 09:48

  本文關鍵詞： GML同步復制 GML更新 MongoDB GML ArcGIS10 分布式GML　出處：《江西理工大學》2012年碩士論文　論文類型：學位論文

【摘要】：GML作為一項地理信息共享標準,當前在單機環(huán)境上的存儲管理理論己日趨成熟,國內(nèi)先后有相關方面的研究成果,但在分布式存儲并行計算環(huán)境下的理論則尚未有顯著成果。分布式并行計算概念在國內(nèi)外已經(jīng)趨之若鶩,前幾年在學術界興起的網(wǎng)格計算,當今熱門的云計算,以及物聯(lián)網(wǎng)、智慧城市等,都涉及到分布式存儲和并行計算處理范疇。隨著知識發(fā)現(xiàn)與技術進步,越來越多的數(shù)據(jù)需要用空間構(gòu)成3D,甚至加上時間構(gòu)成4D來呈現(xiàn)在人們面前,這些數(shù)據(jù)是相當海量的,單機情況下的存儲已經(jīng)不能適應大數(shù)據(jù)量的存儲處理要求,而且涉及到空間數(shù)據(jù)格式問題,為此研究分布式存儲海量數(shù)據(jù)、高性能并行計算處理GML數(shù)據(jù)就是必然的。 本文以單機環(huán)境GML相關存儲管理理論為基礎,研究分布式并行計算下GML空間數(shù)據(jù)同步復制和更新相關方面的理論,并以分布式開源數(shù)據(jù)庫MongoDB為例進行實驗和測試,主要包括以下4個方面： (1)分布式GML存儲,提出分布式GML空間數(shù)據(jù)庫內(nèi)涵和3種設計方案,并以開源NoSQL數(shù)據(jù)庫MongoDB為例,設計相關分布式存儲方案和索引查詢語言,提出云GML管理理論,并在實驗中搭建分布式環(huán)境進行驗證； (2)并行GML同步復制策略,對傳統(tǒng)空間數(shù)據(jù)庫和分布式空間數(shù)據(jù)庫進行說明,闡述分布式數(shù)據(jù)庫復制體系結(jié)構(gòu)和原理,以ArcGIS10的GDB版本化同步復制為參考,提出分布式GML數(shù)據(jù)“要素分組”同步復制策略,以此處理海量GML數(shù)據(jù)在分布式集群中分發(fā)數(shù)據(jù)處理的問題,并提出沖突及解決方案； (3)分布式GML數(shù)據(jù)更新機制,分布式數(shù)據(jù)更新會造成并發(fā)和一致性問題,從分布式事務管理出發(fā),闡述一致性更新核心技術,對ArcGIS10的長事務處理和拓撲機制進行分析,以此探討GML幾何拓撲更新一致性問題,提出分布式“GML文檔化更新模型”,豐富分布式GML空間數(shù)據(jù)更新理論； (4) MongoDB GML復制更新設計,根據(jù)提出的GML同步復制和更新策略,在MongoDB搭建的分布式并行計算環(huán)境中,試驗分布式GML數(shù)據(jù)同步復制和更新效率,使用分布式測試工具JMeter來測試執(zhí)行情況； 最終通過在分布式并行計算環(huán)境中,對GML空間數(shù)據(jù)存儲管理做了底層研究,從而深入研究了其分布式數(shù)據(jù)復制和同步更新的效率機制,為GML在分布式并行計算領域開拓了一片天地。
[Abstract]:GML as a geographical information sharing standard, the current storage management theory in the single computer environment has become more and more mature, there have been related research results in China. However, the theory in distributed storage parallel computing environment has not yet achieved remarkable results. The concept of distributed parallel computing has been flocking in the world. Grid computing, which rose in academic circles a few years ago, is a hot cloud computing. As well as the Internet of things intelligent cities and so on are involved in distributed storage and parallel computing processing. With the development of knowledge discovery and technology more and more data need to use space to form 3D. Even add time to the formation of 4D to present in front of people, these data is quite massive, single-machine storage can no longer adapt to the large amount of data storage processing requirements, and involves the spatial data format problem. For this reason, it is necessary to study the distributed storage of massive data and process GML data with high performance parallel computing. Based on the theory of GML storage management in single computer environment, this paper studies the theory of synchronous replication and update of GML spatial data under distributed parallel computing. And take distributed open source database MongoDB as an example to carry on the experiment and the test, mainly includes the following four aspects: 1) distributed GML storage, the connotation and three design schemes of distributed GML spatial database are put forward, and the open source NoSQL database MongoDB is taken as an example. The related distributed storage scheme and index query language are designed, cloud GML management theory is proposed, and the distributed environment is built for verification in the experiment. 2) parallel GML synchronous replication strategy, the traditional spatial database and distributed spatial database are explained, and the architecture and principle of distributed database replication system are expounded. Taking GDB version synchronous replication of ArcGIS10 as reference, this paper proposes a synchronous replication strategy for distributed GML data "element grouping". In order to deal with the problem of distributing massive GML data in distributed cluster, the paper puts forward the conflict and solution. 3) distributed GML data update mechanism, distributed data update will cause concurrency and consistency problem, from distributed transaction management, this paper expounds the core technology of consistency update. This paper analyzes the long transaction processing and topology mechanism of ArcGIS10, discusses the consistency of GML geometric topology update, and proposes a distributed "GML document update model". Enrich the theory of spatial data updating of distributed GML; 4) MongoDB GML replication update design, according to the proposed GML synchronous replication and update strategy, in the distributed parallel computing environment built by MongoDB. The efficiency of synchronous replication and update of distributed GML data is tested, and the execution is tested using distributed testing tool JMeter. Finally, through the research of GML spatial data storage management in distributed parallel computing environment, the efficiency mechanism of distributed data replication and synchronous update is deeply studied. It opens up a world for GML in the field of distributed parallel computing.
【學位授予單位】：江西理工大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：P208;TP338.6

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