本文關(guān)鍵詞：基于RDF的云制造資源數(shù)據(jù)存儲(chǔ)及檢索方法的研究與實(shí)現(xiàn)　出處：《北京交通大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： RDF HBase SPARQL 云制造

【摘要】：隨著語(yǔ)義網(wǎng)技術(shù)的不斷發(fā)展與成熟,資源描述框架RDF (Resource Description Framework)被應(yīng)用于越來(lái)越多的領(lǐng)域中,然而隨著全球全面進(jìn)入信息化,數(shù)據(jù)爆炸式的增長(zhǎng),大規(guī)模RDF數(shù)據(jù)的存儲(chǔ)及檢索成為行業(yè)數(shù)據(jù)整合和數(shù)據(jù)分析的關(guān)鍵技術(shù),如何提高RDF數(shù)據(jù)存儲(chǔ)的可擴(kuò)展性、數(shù)據(jù)檢索的高效性對(duì)于目前web服務(wù)管理、數(shù)據(jù)管理、云計(jì)算及行業(yè)數(shù)據(jù)共享及整合具有重要的現(xiàn)實(shí)意義。首先,本文對(duì)RDF數(shù)據(jù)的存儲(chǔ)方法進(jìn)行了比較,針對(duì)傳統(tǒng)的關(guān)系數(shù)據(jù)庫(kù)技術(shù)難以應(yīng)對(duì)海量數(shù)據(jù)存儲(chǔ)問(wèn)題,提出基于Hbase的RDF存儲(chǔ)方案,存儲(chǔ)方案中表的邏輯存儲(chǔ)結(jié)構(gòu)采用動(dòng)態(tài)列存儲(chǔ)數(shù)據(jù),使其可以在處理RDF可能出現(xiàn)的多值問(wèn)題時(shí)具有更高的效率。 然后,本文針對(duì)傳統(tǒng)基于關(guān)鍵字的查詢無(wú)法得到全面準(zhǔn)確信息的問(wèn)題,對(duì)RDF查詢語(yǔ)言——SPARQL與HBase之間的查詢接口進(jìn)行了研究與設(shè)計(jì)。提出了語(yǔ)義擴(kuò)展的查詢方法及核心算法。實(shí)現(xiàn)了基于語(yǔ)義與基于關(guān)鍵字相結(jié)合的查詢。 再次,針對(duì)傳統(tǒng)的數(shù)據(jù)集中式處理方式難以應(yīng)對(duì)快速信息檢索問(wèn)題,本文在查詢邏輯之上增加了索引機(jī)制以及并行查詢機(jī)制對(duì)查詢效率進(jìn)行了優(yōu)化。引入索引機(jī)制可以減少查詢時(shí)所要遍歷的節(jié)點(diǎn)數(shù),引入并行化查詢可以使一條查詢?cè)诟鞴?jié)點(diǎn)之間并行進(jìn)行查詢,從而提高查詢效率。 最后,本文通過(guò)對(duì)比試驗(yàn),對(duì)無(wú)索引與并行機(jī)制的查詢方案與有索引與并行機(jī)制的查詢方案進(jìn)行了對(duì)比；并對(duì)實(shí)驗(yàn)結(jié)果進(jìn)行分析,證明在數(shù)據(jù)量較大的情況下,有索引與并行機(jī)制的查詢方案要優(yōu)于無(wú)索引與并行機(jī)制的查詢方案。
[Abstract]:With the development of semantic web technologies and mature, resource description framework RDF (Resource Description Framework) has been applied in more and more areas, however, as the world entered the information, the explosive growth of data, massive RDF data storage and retrieval become the key technology industry data integration and data analysis, how to improve the RDF data storage scalability, efficient retrieval of data for the current web service management, data management, cloud computing and industry data sharing and integration has important practical significance. Firstly, the storage method of RDF data were compared to the traditional relational database technology to deal with the problem of massive data storage, RDF storage scheme based on Hbase, the logical storage structure storage scheme in the columns of the table data is stored by the dynamic, so that it can more value may appear in the RDF ask The problem is more efficient.
Then, according to the traditional keyword based queries can not be comprehensive and accurate information, the RDF query language, query interface between SPARQL and HBase is studied and designed. A query method of semantic extension and core algorithm. Based on the combination of semantic and keyword based query.
Again, according to the data of the traditional centralized processing technology to cope with rapid information retrieval, the query logic increases the indexing mechanism and parallel query mechanism to optimize the query efficiency. The number of nodes is introduced to reduce the indexing mechanism can traverse the query, introduce the parallel query can make a parallel query in the query between the nodes, and improve query efficiency.
Finally, through comparative test, query scheme on index and parallel mechanism and query scheme index and parallel mechanism are compared; and the experimental results are analyzed, in the case of large data, query scheme query scheme index and parallel mechanism is better than no index and parallel mechanism.

【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP333

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本文編號(hào)：1377183