本文選題：DOA + 元數(shù)據(jù)存儲(chǔ)　； 參考：《成都理工大學(xué)》2013年碩士論文

【摘要】：伴隨國(guó)家信息化建設(shè)的快速發(fā)展,各種各類數(shù)據(jù)信息不斷涌現(xiàn),時(shí)時(shí)刻刻為人們的日常生活生產(chǎn)提供信息服務(wù)。Internet的全世界普及,使數(shù)據(jù)每一時(shí)刻都在網(wǎng)絡(luò)中流動(dòng),使數(shù)據(jù)散落在不同的數(shù)據(jù)存儲(chǔ)系統(tǒng)與設(shè)備中。為實(shí)現(xiàn)數(shù)據(jù)在客戶端匯聚,G/S模式應(yīng)運(yùn)而生。它采用“請(qǐng)求(request)-聚合(Polymerization)-服務(wù)(Service)"機(jī)制對(duì)所有的數(shù)據(jù)信息服務(wù)過(guò)程進(jìn)行組織與管理,在客戶端實(shí)現(xiàn)數(shù)據(jù)信息匯聚和服務(wù)聚合。G/S模式解決了數(shù)據(jù)的匯聚問(wèn)題,但是如何管理各種數(shù)據(jù),G/S模式并沒(méi)有提出有效的解決方法。為了能夠更快更好的獲取數(shù)據(jù),為G/S模式服務(wù),成都理工大學(xué)教授苗放老師提出了以數(shù)據(jù)為中心,以標(biāo)識(shí)為主線的面向數(shù)據(jù)的體系結(jié)構(gòu)——DOA,運(yùn)用數(shù)據(jù)的元數(shù)據(jù)實(shí)現(xiàn)對(duì)數(shù)據(jù)的統(tǒng)一管理。要管理各種類型數(shù)據(jù),首先要有相關(guān)數(shù)據(jù)的元數(shù)據(jù),所以數(shù)據(jù)的元數(shù)據(jù)存儲(chǔ)問(wèn)題,成為了DOA首要考慮的問(wèn)題。DOA要求數(shù)據(jù)注冊(cè)中心能夠快速提供數(shù)據(jù)的元數(shù)據(jù)信息,如何存儲(chǔ)才能快速提供元數(shù)據(jù),成為DOA下元數(shù)據(jù)管理數(shù)據(jù)的瓶頸,也是本文研究的問(wèn)題,解決DOA下的數(shù)據(jù)注冊(cè)中心元數(shù)據(jù)快速獲取的存儲(chǔ)問(wèn)題,成為當(dāng)務(wù)之急。本文首先對(duì)G/S模式和DOA進(jìn)行了全面概述,分析了它們的層次結(jié)構(gòu)與對(duì)數(shù)據(jù)匯聚和管理的作用,促使了對(duì)元數(shù)據(jù)存儲(chǔ)策略的研究。通過(guò)對(duì)元數(shù)據(jù)標(biāo)準(zhǔn)和開發(fā)設(shè)計(jì)框架基礎(chǔ)知識(shí)的概述,為設(shè)計(jì)了元數(shù)據(jù)存儲(chǔ)規(guī)范準(zhǔn)備了基礎(chǔ)知識(shí)。本文的工作如下：(1)研究數(shù)據(jù)注冊(cè)中心元數(shù)據(jù)存儲(chǔ)策略由于DOA使用元數(shù)據(jù)統(tǒng)一管理各種數(shù)據(jù),所以元數(shù)據(jù)的獲取速度決定了DOA的性能。因而,如何存儲(chǔ)元數(shù)據(jù)成為元數(shù)據(jù)快速獲取的關(guān)鍵。在分析研究文件系統(tǒng)方式、LDAP目錄存儲(chǔ)方式、各種關(guān)系數(shù)據(jù)庫(kù)存儲(chǔ)方式和內(nèi)存數(shù)據(jù)存儲(chǔ)方式的存儲(chǔ)優(yōu)缺點(diǎn)的基礎(chǔ)上,對(duì)使用何種存儲(chǔ)方式才能使數(shù)據(jù)注冊(cè)中心元數(shù)據(jù)被快速獲取進(jìn)行了分析研究。并依據(jù)研究成果,設(shè)計(jì)了一種能夠?qū)崿F(xiàn)元數(shù)據(jù)快速獲取的元數(shù)據(jù)存儲(chǔ)結(jié)構(gòu)模型。(2)研究元數(shù)據(jù)存儲(chǔ)的相關(guān)算法基于內(nèi)存容量的大小和元數(shù)據(jù)被訪問(wèn)頻率的問(wèn)題,研究為內(nèi)存提供存儲(chǔ)元數(shù)據(jù)的相關(guān)算法。研究了一種基于代價(jià)函數(shù)的緩存替換算法,為數(shù)據(jù)注冊(cè)中心在緩存中動(dòng)態(tài)存儲(chǔ)最近有可能被經(jīng)常訪問(wèn)的元數(shù)據(jù)。同時(shí)進(jìn)一步研究了在緩存中選取高訪問(wèn)頻率元數(shù)據(jù)表的算法,以實(shí)現(xiàn)通常訪問(wèn)的元數(shù)據(jù)信息存入內(nèi)存數(shù)據(jù)庫(kù)。通過(guò)這兩種算法,把訪問(wèn)頻率高的元數(shù)據(jù)存入內(nèi)存,提高了數(shù)據(jù)注冊(cè)中心對(duì)元數(shù)據(jù)的獲取速度。本文的創(chuàng)新點(diǎn)與研究成果有：(1)提出了一種DOA下的數(shù)據(jù)注冊(cè)中心元數(shù)據(jù)快速獲取存儲(chǔ)策略。本元數(shù)據(jù)存儲(chǔ)策略,依據(jù)DOA下的元數(shù)據(jù)統(tǒng)一管理數(shù)據(jù)的要求,利用關(guān)系數(shù)據(jù)庫(kù)的存儲(chǔ)容量、內(nèi)存數(shù)據(jù)庫(kù)的訪問(wèn)效率和緩存動(dòng)態(tài)存儲(chǔ)作用,通過(guò)基于代價(jià)的緩存替換算法實(shí)現(xiàn)在緩存中動(dòng)態(tài)存儲(chǔ)最近有可能被經(jīng)常訪問(wèn)的元數(shù)據(jù),以提高元數(shù)據(jù)的獲取速度與積累元數(shù)據(jù)的被訪問(wèn)頻率；再通過(guò)基于代價(jià)函數(shù)的緩存選取算法,選取緩存中訪問(wèn)頻率最高的元數(shù)據(jù)表存入內(nèi)存數(shù)據(jù)庫(kù),完成元數(shù)據(jù)的內(nèi)存數(shù)據(jù)庫(kù)存儲(chǔ)。在此基礎(chǔ)上,設(shè)計(jì)了DOA下的數(shù)據(jù)注冊(cè)中心的元數(shù)據(jù)存儲(chǔ)結(jié)構(gòu)模型,并依據(jù)此模型設(shè)計(jì)了DOA下的數(shù)據(jù)注冊(cè)中心元數(shù)據(jù)存儲(chǔ)系統(tǒng)。(2)提出了一種數(shù)據(jù)注冊(cè)中心的替換緩存中訪問(wèn)權(quán)值最低元數(shù)據(jù)表的算法。通過(guò)對(duì)現(xiàn)存的幾種常用緩存替換算法分析研究,從函數(shù)的角度,利用緩存數(shù)據(jù)表大小、訪問(wèn)次數(shù)、訪問(wèn)時(shí)間和獲取緩存數(shù)據(jù)表的CPU時(shí)間,設(shè)計(jì)了一種基于代價(jià)函數(shù)的緩存替換算法,實(shí)現(xiàn)最近有可能被經(jīng)常訪問(wèn)的數(shù)據(jù)表在緩存中的存儲(chǔ)。(3)提出了一種數(shù)據(jù)注冊(cè)中心的選取高訪問(wèn)頻率元數(shù)據(jù)表存入內(nèi)存數(shù)據(jù)庫(kù)的算法。在對(duì)現(xiàn)存緩存替換算法研究的基礎(chǔ)上,從函數(shù)的角度,利用緩存數(shù)據(jù)表大小、訪問(wèn)次數(shù)、訪問(wèn)時(shí)間和訪問(wèn)密度,設(shè)計(jì)了一種基于代價(jià)函數(shù)的緩存數(shù)據(jù)表選取算法,實(shí)現(xiàn)高訪問(wèn)頻率元數(shù)據(jù)表從緩存到內(nèi)存數(shù)據(jù)庫(kù)的存儲(chǔ)。
[Abstract]:With the rapid development of national information construction, various kinds of data and information are constantly emerging. The information service of.Internet is popularized all the time for people's daily life. The data will flow in the network at every moment, so that data are scattered in different data storage and storage systems and equipment. G/S mode comes into being. It uses "request" - aggregation (Polymerization) - Service (Service) "mechanism to organize and manage all the data information service processes. The data aggregation problem is solved by data aggregation and service aggregation.G/S mode in the client, but how to manage all kinds of data, G/S mode is not In order to get the data faster and better, to serve the G/S mode faster and better, Professor Miao Fang of Chengdu University of Technology put forward a data centric, identification oriented data oriented architecture, DOA, using data metadata to realize the unified management of the logarithm data. First, to manage various types of data, first In order to have metadata of relevant data, the problem of metadata storage of data has become the primary concern of DOA..DOA requires that data registration center can provide metadata information quickly, how to store metadata quickly, become the bottleneck of metadata management data under DOA, and the problem of this paper, to solve DOA The fast acquisition of data registry metadata has become a top priority. This paper first gives a comprehensive overview of the G/S model and DOA, analyzes their hierarchical structure and the function of data convergence and management, and promotes the research of metadata storage strategy. The basic knowledge is prepared for the design of metadata storage specification. The work of this paper is as follows: (1) study the metadata storage strategy of data registration center because DOA uses metadata to manage all kinds of data, so the speed of metadata acquisition determines the performance of DOA. Therefore, how to store metadata is the key to the rapid acquisition of metadata. On the basis of analyzing the methods of file system, the storage mode of LDAP directory, the storage mode of all kinds of relational databases and the memory of memory data storage methods, this paper analyzes and studies what kind of storage methods used to make the metadata of the data registration center be obtained quickly. And a kind of realization is designed based on the research results. The metadata storage structure model is quickly acquired. (2) the related algorithms of metadata storage are based on the size of memory capacity and the frequency of the metadata being accessed, and the related algorithms for storing metadata for memory are studied. A caching replacement algorithm based on cost function is studied, which is used to move the data registry in the cache. State storage of metadata that may be frequently accessed recently. At the same time, the algorithm of selecting high access frequency metadata in the cache is further studied to save the commonly accessed metadata information into the memory database. Through these two algorithms, the metadata with high frequency of access is stored in the memory, and the data registry is improved to the metadata. The innovation points and research results of this paper are as follows: (1) a fast acquisition strategy for data registration center metadata under DOA is proposed. This metadata storage strategy is based on the requirements of unified management of data under the metadata under DOA, using the storage capacity of the relational database, the access efficiency of the memory database and the dynamic storage of the cache. Use the cost based cache replacement algorithm to dynamically store the most frequently accessed metadata that may be frequently accessed in the cache to improve the speed of metadata acquisition and the access frequency of the accumulated metadata; then, the cache selection algorithm based on the cost function is used to select the metadata with the highest access frequency in the cache and save the memory. On the basis of this, the metadata storage structure model of the data registration center under DOA is designed, and the data registration center metadata storage system under DOA is designed based on this model. (2) a calculation of the minimum metadata table of access weight in the replacement caching of the data registration center is proposed. By analyzing several existing common cache replacement algorithms, from the point of view of function, using the size of the cached data table, the number of access, access time and the CPU time of obtaining the cached data table, a cache replacement algorithm based on the cost function is designed to realize the storage of the data table that may be frequently accessed recently in the cache. (3) an algorithm for selecting the high access frequency metadata table to be stored in the memory database is proposed. On the basis of the existing cache replacement algorithm, a cost function based caching data table is designed from the function point of view, using the size of the cached data table, access times, access time and access density. The algorithm implements the storage of high access frequency metadata tables from cache to memory database.
【學(xué)位授予單位】：成都理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP333

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