本文選題：大數(shù)據(jù) + 大數(shù)據(jù)存儲��； 參考：《Frontiers of Information Technology & Electronic Engineering》2017年08期

【摘要】：對于容量快速增長、日趨多元化的大數(shù)據(jù),業(yè)界亟需開發(fā)可行性更好的存儲工具。為滿足大數(shù)據(jù)存儲需求,存儲機(jī)制已經(jīng)形成從傳統(tǒng)數(shù)據(jù)管理系統(tǒng)到No SQL技術(shù)的結(jié)構(gòu)化轉(zhuǎn)移。然而,目前可用的大數(shù)據(jù)存儲技術(shù)無法為持續(xù)增長的異構(gòu)數(shù)據(jù)提供一致、可擴(kuò)展和可用的解決方案。在科學(xué)實(shí)驗(yàn)、醫(yī)療保健、社交網(wǎng)絡(luò)和電子商務(wù)等實(shí)際應(yīng)用中,存儲是大數(shù)據(jù)分析的第一步。截至目前,亞馬遜、谷歌和阿帕奇等公司形成了大數(shù)據(jù)存儲方案的行業(yè)標(biāo)準(zhǔn),但尚未有關(guān)于大數(shù)據(jù)存儲技術(shù)性能和容量提升的深入調(diào)查和文獻(xiàn)報告。本文旨在對目前可用于大數(shù)據(jù)的最先進(jìn)的存儲技術(shù)進(jìn)行全面調(diào)查,提供了一個明確的大數(shù)據(jù)存儲技術(shù)分類方法,以幫助數(shù)據(jù)分析師和研究人員了解和選擇更適合其需求的存儲機(jī)制。我們使用布魯爾的CAP定理比較和分析了現(xiàn)有存儲方法,評估了不同存儲架構(gòu)的性能,討論了存儲技術(shù)的意義、應(yīng)用及其對其他類別數(shù)據(jù)的支持。為了加快部署可靠和可擴(kuò)展的存儲系統(tǒng),文中還突出了未來研究面臨的幾個挑戰(zhàn)。
[Abstract]:For big data, whose capacity is growing rapidly and diversification day by day, it is urgent for the industry to develop more feasible and better storage tools.In order to meet the storage requirements of big data, the storage mechanism has formed a structured transfer from traditional data management system to No SQL technology.However, the currently available big data storage technology cannot provide consistent, scalable and available solutions for growing heterogeneous data.Storage is the first step in big data's analysis in practical applications such as scientific experiments, healthcare, social networking and e-commerce.So far, companies such as Amazon, Google and Apache have formed the industry standard for big data's storage program, but there have been no in-depth investigations and literature reports on the performance and capacity improvements of big data storage technology.This paper aims to conduct a comprehensive investigation of the most advanced storage technologies currently available to big data, and to provide a clear classification method for big data storage technology.To help data analysts and researchers understand and select storage mechanisms that are better suited to their needs.We use Brewer's CAP theorem to compare and analyze existing storage methods, evaluate the performance of different storage architectures, and discuss the significance of storage technology, its application and its support for other types of data.In order to speed up the deployment of reliable and scalable storage systems, several challenges for future research are highlighted.
【作者單位】： Faculty
【分類號】：TP311.13

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