【摘要】：隨著互聯(lián)網(wǎng)用戶規(guī)模的增加,互聯(lián)網(wǎng)廣告行業(yè)也在迅速發(fā)展。近幾年出現(xiàn)的廣告實時競價的模式與傳統(tǒng)廣告投放模式有很大區(qū)別。RTB廣告(實時競價廣告)使廣告投放的重心轉(zhuǎn)移到受眾身上,通過對用戶數(shù)據(jù)的搜集和用戶屬性的挖掘,來實現(xiàn)廣告投放效果的最大化。RTB廣告近幾年在美國發(fā)展迅速,并于2012年由谷歌公司引入中國。 DSP是RTB廣告投放系統(tǒng)中的買方平臺。DSP為廣告商提供管理廣告的功能,同時DSP搜集互聯(lián)網(wǎng)受眾的信息,從大量受眾數(shù)據(jù)中分析出受眾的興趣、購物傾向等屬性,再根據(jù)這些屬性進行針對性的廣告投放,以提升廣告效果。根據(jù)受眾屬性和興趣投放廣告,是DSP業(yè)務(wù)的核心競爭力。其中用于存放受眾數(shù)據(jù)的存儲系統(tǒng)必須有良好的可伸縮性,傳統(tǒng)關(guān)系數(shù)據(jù)庫在可伸縮性方面很難滿足DSP的要求,所以設(shè)計合理的并且擁有良好的可伸縮性的大數(shù)據(jù)存儲方案顯得尤為重要。 DSP系統(tǒng)中使用鍵值存儲策略來存放受眾數(shù)據(jù)。DSP系統(tǒng)中的受眾數(shù)據(jù)在廣告投放過程中將不斷的增多,因此受眾數(shù)據(jù)的存儲系統(tǒng)必須擁有良好的可擴展性,同時還要有良好的查詢性能。本文研究了目前存在的一些常見的鍵值數(shù)據(jù)庫,設(shè)計了適合本DSP系統(tǒng)的鍵值存儲方案。鍵值存儲的關(guān)鍵問題是數(shù)據(jù)劃分、數(shù)據(jù)備份和負載均衡。本文使用改進的一致性哈希算法解決數(shù)據(jù)劃分問題。引入虛擬節(jié)點的概念,數(shù)據(jù)主鍵與物理存儲節(jié)點的映射過程分為兩個步驟,第一步將數(shù)據(jù)主鍵通過一致性哈希算法映射到虛擬節(jié)點,第二步以虛擬節(jié)點為單位完成其與物理數(shù)據(jù)節(jié)點的映射。傳統(tǒng)的一致性哈希算法難以實現(xiàn)動態(tài)負載均衡,本文的負載均衡算法是以虛擬節(jié)點為單位進行的,使動態(tài)負載均衡的實現(xiàn)成為可能。 DSP系統(tǒng)的主要用戶是廣告商和廣告代理商。廣告商上傳廣告到DSP系統(tǒng),為廣告定制投放定向和投放計劃,DSP系統(tǒng)根據(jù)廣告投放計劃為用戶投放廣告。DSP為廣告商提供了地域定向、語言定向和設(shè)備定向等七種定向,并綜合多種因素對廣告請求進行出價。DSP系統(tǒng)的前端界面使用了三級菜單,將系統(tǒng)功能充分展示在用戶面前,為用戶提供友好的使用界面。在架構(gòu)上盡量減少網(wǎng)頁的深度,使開發(fā)邏輯清晰。DSP使用多個廣告競價服務(wù)器處理競價請求,利用web服務(wù)器將高頻率的競價請求分散到各個競價服務(wù)器,來達到應(yīng)用級別的負載均衡。
[Abstract]:With the increase in the size of Internet users, the Internet advertising industry is also developing rapidly. In recent years, the pattern of real-time advertising bidding has been very different from the traditional advertising mode. RTB advertising (real-time bidding advertising) makes the focus of advertising to the audience, through the collection of user data and the mining of user attributes. RTB has grown rapidly in the United States in recent years and was introduced to China by Google in 2012. DSP is the buyer's platform in the RTB advertising delivery system. DSP provides advertisers with the function of managing advertising. At the same time, DSP collects the information of the Internet audience, analyzes the audience's interest, shopping tendency and other attributes from a large number of audience data. Then according to these attributes targeted advertising, in order to improve the advertising effect. According to the audience attributes and interest in advertising, is the core competitiveness of DSP business. The storage system used to store the audience data must have good scalability, and the traditional relational database is difficult to meet the requirements of DSP in scalability. Therefore, the design of reasonable and have good scalability big data storage scheme is particularly important. In DSP system, the key storage strategy is used to store the audience data. The audience data in the DSP system will increase continuously in the process of advertising, so the storage system of the audience data must have good expansibility. At the same time also have good query performance. In this paper, some common key and value databases are studied, and the key and value storage scheme suitable for this DSP system is designed. Key issues in key storage are data partitioning, data backup and load balancing. In this paper, the improved consistency hash algorithm is used to solve the data partition problem. The concept of virtual node is introduced. The mapping process of data primary key and physical storage node is divided into two steps. The first step maps the data primary key to virtual node through the consistent hash algorithm. The second step is to map the virtual node to the physical data node. The traditional uniform hash algorithm is difficult to realize dynamic load balancing. The load balancing algorithm in this paper is based on virtual nodes, which makes the realization of dynamic load balancing possible. The main users of the DSP system are advertisers and advertising agencies. Advertisers upload ads to the DSP system, and the DSP system provides users with advertisements according to the advertising plan. DSP provides advertisers with seven kinds of orientation, such as regional orientation, language orientation and device orientation. The front-end interface of the DSP system uses a three-level menu to fully display the functions of the system in front of the user and provides a friendly interface for the user. DSP uses multiple ad auction servers to process bidding requests, and uses web server to spread high frequency bidding requests to each bidding server. To achieve application-level load balancing.
【學(xué)位授予單位】：華中師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP311.13;TP393.09

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