本文選題：交通流數據 + HBase　； 參考：《北方工業(yè)大學》2017年碩士論文

【摘要】：隨著城市智能交通的快速發(fā)展、打車軟件和共享單車的盛行,交通數據呈現出指數式增長。對交通數據進行合理的分析可以預測出人們的出行習慣和熱門交通路線,為城市交通的管理提供幫助,也為相關互聯網公司創(chuàng)造營收提供支持。HBase數據庫對大規(guī)模數據的存儲具有先天優(yōu)勢,在交通領域的應用非常廣泛。但是HBase只能在行鍵上構建索引,無法直接構建高效的多維索引和非行鍵索引,在交通數據的時空查詢上性能較差,并且無法實現快速的非行鍵查詢。針對這些問題,需要為HBase構建相應的輔助索引。本文結合實時交通流數據的特點,經過大量的調研工作,對HBase時空索引和二級索引兩種輔助索引技術進行了研究和設計,實現了一個基于HBase輔助索引的查詢系統(tǒng)。主要研究內容如下:一、針對交通數據的時空三維特征,提升HBase對交通數據的時空查詢性能,本文通過Geohash降維的思想研究和設計了三種基于HBase的時空索引,并對其優(yōu)缺點和適用的場景作了分析。二、針對HBase非行鍵查詢性能低下的問題,提高HBase對交通數據查詢支持的靈活度,本文通過倒排索引的思想研究和設計了兩種HBase二級索引,并作了相關分析。三、實現了一個基于HBase輔助索引的查詢系統(tǒng)。該系統(tǒng)實現了本文設計的兩種輔助索引中各自最優(yōu)的方案,還實現了 SQL解析、索引構建、索引匹配、索引管理等功能,簡化了用戶對HBase數據庫的查詢操作。四、最后通過實驗驗證了本文提出的索引方案能有效提升實時交通流數據的查詢性能,并且驗證了索引管理的有效性。
[Abstract]:With the rapid development of urban intelligent transportation and the prevalence of ride-hailing software and shared bicycles, traffic data show exponential growth. Reasonable analysis of traffic data can predict people's travel habits and popular transportation routes, and provide help for urban traffic management. HBase also provides revenue support for related Internet companies. HBase database has an inherent advantage in large-scale data storage and is widely used in transportation. But HBASE can only build index on row key, can not directly build multi-dimensional index and non-line key index directly, and can not realize fast non-line key query because of its poor performance in spatio-temporal query of traffic data. To solve these problems, it is necessary to build corresponding auxiliary indexes for HBASE. According to the characteristics of real-time traffic flow data and through a lot of research work, this paper studies and designs two kinds of auxiliary index technology: HBase space-time index and second-level index, and realizes a query system based on HBAS-based auxiliary index. The main research contents are as follows: firstly, aiming at the spatial and temporal features of traffic data and improving the spatio-temporal query performance of HBase to traffic data, this paper studies and designs three space-time indexes based on HBase through the idea of reducing dimension of Geohash. Its advantages and disadvantages and applicable scenarios are analyzed. Secondly, in order to improve the flexibility of HBASE in traffic data query, two kinds of HBASE secondary indexes are designed and analyzed through the idea of inverted index, aiming at the low performance of HBASE non-line key query and improving the flexibility of HBASE to traffic data query. Thirdly, a query system based on HBASE aided index is implemented. The system realizes the optimal schemes of the two auxiliary indexes designed in this paper, and also realizes the functions of SQL parsing, index construction, index matching, index management and so on, which simplifies the query operation of the user to HBase database. Finally, the experimental results show that the proposed indexing scheme can effectively improve the query performance of real-time traffic flow data, and verify the effectiveness of index management.
【學位授予單位】：北方工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U495;TP311.13

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本文編號：2010651