發(fā)布時(shí)間：2018-07-05 02:11

  本文選題：Web應(yīng)用 + 海量數(shù)據(jù)　； 參考：《浙江大學(xué)》2013年碩士論文

【摘要】：隨著Internet的飛速發(fā)展,證券、銀行等大型金融信息系統(tǒng)積累了海量的用戶數(shù)據(jù),數(shù)據(jù)量和用戶數(shù)的劇增,給這些系統(tǒng)帶來了很大的壓力。如何有效減少用戶訪問延時(shí),提高系統(tǒng)服務(wù)質(zhì)量是一個(gè)迫切需要解決的難題,Web緩存技術(shù)可以極大的提高系統(tǒng)的響應(yīng)速度,然而傳統(tǒng)的緩存策略只是著眼于單個(gè)用戶的訪問習(xí)慣,沒有從全盤考慮緩存性能,或者需要加載所有數(shù)據(jù)才能判斷哪些數(shù)據(jù)是需要緩存的,對于海量數(shù)據(jù)來說,加載所有數(shù)據(jù)是不可能的,因此,本文針對海量數(shù)據(jù)的緩存策略和如何設(shè)計(jì)緩存系統(tǒng),做了以下幾個(gè)方面的工作： (1)針對海量數(shù)據(jù)如何剔除那些冗余的數(shù)據(jù),只提取對系統(tǒng)有用的核心數(shù)據(jù)進(jìn)行緩存,提出了基于規(guī)則引擎的數(shù)據(jù)精簡模式(REBDR, Rules Engine-Based Data Reduction design pattern),采用規(guī)則引擎作為數(shù)據(jù)預(yù)處理的核心,而不是傳統(tǒng)上的將數(shù)據(jù)預(yù)處理邏輯固化在代碼中,從而讓數(shù)據(jù)預(yù)處理邏輯和應(yīng)用代碼之間獲得了很好的分離。數(shù)據(jù)精簡的規(guī)則可靈活定制,能夠適應(yīng)不同行業(yè)的業(yè)務(wù)需求,并且可以快速響應(yīng)業(yè)務(wù)需求的變動,該模式具有通用性。 (2)對于海量數(shù)據(jù),經(jīng)過數(shù)據(jù)精簡后,也往往無法全部加載到緩存中,因此我們提出了基于裝載因子的數(shù)據(jù)緩存策略,該算法無需加載所有數(shù)據(jù)到內(nèi)存中,根據(jù)數(shù)據(jù)的裝載因子即能做出是否緩存的策略,通過仿真測試,該緩存策略相比傳統(tǒng)的緩存策略,命中率更高,在系統(tǒng)的吞吐量獲得成倍增長的同時(shí)大幅降低了系統(tǒng)的響應(yīng)時(shí)延。 (3)設(shè)計(jì)實(shí)現(xiàn)了“電子銀行風(fēng)險(xiǎn)監(jiān)控系統(tǒng)”,通過應(yīng)用REBDR模式和基于裝載因子的數(shù)據(jù)緩存策略,解決了系統(tǒng)最關(guān)鍵的性能問題,該系統(tǒng)擁有很高的靈活性,為國內(nèi)銀行開展電子銀行實(shí)時(shí)風(fēng)險(xiǎn)監(jiān)控打下了堅(jiān)實(shí)的基礎(chǔ),目前,國內(nèi)未見有其它滿足銀行海量交易實(shí)時(shí)監(jiān)控性能要求的產(chǎn)品。
[Abstract]:With the rapid development of Internet, large financial information systems such as securities, banks and other financial information systems have accumulated huge amounts of user data, and the amount of data and the number of users have increased dramatically, which has brought great pressure to these systems. How to effectively reduce the delay of user access and improve the quality of service is an urgent problem. Web caching technology can greatly improve the response speed of the system. However, the traditional caching strategy only focuses on the access habits of individual users. It is not possible to load all the data for a large amount of data without considering the overall cache performance, or to load all the data to determine which data needs to be cached. This paper focuses on the cache strategy of mass data and how to design the cache system. (1) aiming at how to remove the redundant data from the massive data, we only extract the core data useful for the system to cache. The rule engine is used as the core of data preprocessing in rule engine based data reduction design pattern), (RDR), rather than the traditional logic of data preprocessing in code. So that the data preprocessing logic and the application code to get a good separation. The rules of data reduction can be flexibly customized, can adapt to the business needs of different industries, and can quickly respond to changes in business requirements. (2) for mass data, after data streamlining, the model is universal. Therefore, we propose a data caching strategy based on load factor. This algorithm does not need to load all data into memory, according to the loading factor of data, we can make the policy of whether to cache or not. The simulation results show that the cache strategy has a higher hit rate than the traditional cache strategy. At the same time, the throughput of the system increases exponentially and the response delay of the system is greatly reduced. (3) the "Electronic Banking risk Monitoring system" is designed and implemented, through the application of REBDR mode and data cache strategy based on loading factor. It has solved the most critical performance problem of the system, and the system has high flexibility, which has laid a solid foundation for domestic banks to carry out real-time risk monitoring of electronic banking. There are no other domestic products that meet the real-time monitoring performance requirements of banks' massive transactions.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP333

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 廖守億,戴金海;基于Agent的建模與仿真設(shè)計(jì)模式及軟件框架[J];系統(tǒng)仿真學(xué)報(bào);2005年04期

，

本文編號：2098466