本文選題：農(nóng)業(yè)博客 + 分布式存儲(chǔ)��； 參考：《西北農(nóng)林科技大學(xué)》2014年碩士論文

【摘要】：在互聯(lián)網(wǎng)技術(shù)飛速發(fā)展的時(shí)代，人們獲取信息主要來源于網(wǎng)絡(luò)資源，農(nóng)業(yè)領(lǐng)域也是如此，但農(nóng)業(yè)用戶與其他用戶不同，，計(jì)算機(jī)使用知識(shí)的匱乏使農(nóng)業(yè)用戶難以從網(wǎng)絡(luò)上獲得所需信息，尤其是在當(dāng)今網(wǎng)絡(luò)信息數(shù)據(jù)量不斷增加的情況下，如何從海量的復(fù)雜數(shù)據(jù)中得到所需的相關(guān)農(nóng)業(yè)信息更是具有一定的難度。因此，為廣大農(nóng)業(yè)用戶研發(fā)一個(gè)具有實(shí)際意義的互動(dòng)交流平臺(tái)是十分有必要的。博客是一種熱門的用于網(wǎng)絡(luò)信息交流的互聯(lián)網(wǎng)應(yīng)用平臺(tái)，然而現(xiàn)有的博客網(wǎng)站多為綜合性交流平臺(tái)且實(shí)時(shí)性不高，并不適合農(nóng)業(yè)用戶使用。針對(duì)這些問題，本研究以分布式存儲(chǔ)和并行計(jì)算技術(shù)為支撐，研究與實(shí)現(xiàn)了一個(gè)具有分布式、高實(shí)時(shí)和可擴(kuò)展性的農(nóng)業(yè)博客。主要研究?jī)?nèi)容及結(jié)論如下： （1）農(nóng)業(yè)博客基礎(chǔ)模型構(gòu)建。首先根據(jù)廣大農(nóng)業(yè)用戶對(duì)農(nóng)業(yè)博客的應(yīng)用需求，設(shè)計(jì)了農(nóng)業(yè)博客系統(tǒng)的整體系統(tǒng)架構(gòu)。然后針對(duì)其整體架構(gòu)改進(jìn)了現(xiàn)有的博客開發(fā)模式，構(gòu)建了農(nóng)業(yè)博客的分布式存儲(chǔ)模型及數(shù)據(jù)并行處理模型，并對(duì)傳統(tǒng)的推-拉模式進(jìn)行了改進(jìn)。 （2）農(nóng)業(yè)博客系統(tǒng)設(shè)計(jì)與實(shí)現(xiàn)。首先根據(jù)系統(tǒng)的功能需求、服務(wù)體系以及基本的模型規(guī)劃了農(nóng)業(yè)博客系統(tǒng)的總體功能架構(gòu)，設(shè)計(jì)了總體數(shù)據(jù)流，并對(duì)系統(tǒng)的主要功能模塊進(jìn)行詳細(xì)的設(shè)計(jì)，同時(shí)對(duì)主要的數(shù)據(jù)處理過程（存儲(chǔ)與訪問）進(jìn)行了設(shè)計(jì)說明。然后對(duì)數(shù)據(jù)庫(kù)模式進(jìn)行了詳細(xì)的設(shè)計(jì)與說明。最后利用MapReduce實(shí)現(xiàn)了數(shù)據(jù)的并行處理，同時(shí)對(duì)Coprocessor數(shù)據(jù)處理與數(shù)據(jù)訪問服務(wù)的實(shí)現(xiàn)進(jìn)行了具體的說明。 （3）原型測(cè)試與分析。首先根據(jù)Hadoop的框架部署了分布式測(cè)試集群并整合了MyEclipse開發(fā)環(huán)境，然后對(duì)農(nóng)業(yè)博客系統(tǒng)的用戶界面進(jìn)行了系統(tǒng)功能的測(cè)試，最后在模擬大數(shù)據(jù)集的條件下完成了對(duì)系統(tǒng)的性能測(cè)試分析。原型測(cè)試結(jié)果表明系統(tǒng)具有可行性和高效性。
[Abstract]:In the era of rapid development of Internet technology, people obtain information mainly from the network resources, and so is the agricultural field, but agricultural users are different from other users.The lack of knowledge about the use of computers makes it difficult for agricultural users to obtain the required information from the network, especially when the amount of data on the network is increasing.It is more difficult to get the relevant agricultural information from the massive complex data.Therefore, it is necessary to develop a practical interactive communication platform for agricultural users.Blog is a popular Internet application platform for the exchange of information on the Internet. However, most of the existing blog sites are comprehensive communication platforms and the real-time performance is not high, so it is not suitable for agricultural users.To solve these problems, a distributed, real-time and scalable agricultural blog is studied and implemented based on distributed storage and parallel computing technology.The main contents and conclusions are as follows:1) constructing the basic model of agriculture blog.Firstly, according to the application demand of agricultural blog, the whole system structure of agricultural blog system is designed.Then, the existing blog development model is improved according to its overall architecture, the distributed storage model and data parallel processing model of agricultural blog are constructed, and the traditional push-pull model is improved.Agricultural blog system design and implementation.Firstly, according to the functional requirements of the system, the service system and the basic model, the overall functional framework of the agricultural blog system is planned, the overall data flow is designed, and the main functional modules of the system are designed in detail.At the same time, the main data processing procedures (storage and access) are described.Then the database schema is designed and explained in detail.Finally, the parallel processing of data is realized by using MapReduce, and the realization of Coprocessor data processing and data access service is explained in detail.Prototype testing and analysis.First, the distributed test cluster is deployed according to the framework of Hadoop and the MyEclipse development environment is integrated, then the user interface of the agricultural blog system is tested.Finally, the performance of the system is tested and analyzed under the condition of simulating big data set.The prototype test results show that the system is feasible and efficient.
【學(xué)位授予單位】：西北農(nóng)林科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.092

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