{"title":"Distributed Evaluation of XPath Axes Queries over Large XML Documents Stored in MapReduce Clusters","authors":"Adam Senk, M. Valenta, W. Benn","doi":"10.1109/DEXA.2014.59","DOIUrl":null,"url":null,"abstract":"The MR (MapReduce) framework, a programming model for parallel computation over data stored in a cluster of commodity computers, established itself as one of the leading solutions for Big Data processing. This framework is also being used like a query language in many database systems, because it can process data stored in various unstructured, semi-structured, and structured formats. Nevertheless, the MR framework can be used for XML data processing too, it does not allow to write queries in a declarative manner, like XPath or XQuery. To overcome this problem, we propose a system that enables to query XML data with XPath, but it evaluates the queries in parallel using the MR framework. First, we introduce a persistent storage that maps XML data into a wide-column store. The proposed mapping enables efficient and distributed data processing. Secondly, we describe a query processor translating an XPath language subset to MR jobs. Finally, we present tests and their results showing the scalability of our system.","PeriodicalId":291899,"journal":{"name":"2014 25th International Workshop on Database and Expert Systems Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 25th International Workshop on Database and Expert Systems Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2014.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The MR (MapReduce) framework, a programming model for parallel computation over data stored in a cluster of commodity computers, established itself as one of the leading solutions for Big Data processing. This framework is also being used like a query language in many database systems, because it can process data stored in various unstructured, semi-structured, and structured formats. Nevertheless, the MR framework can be used for XML data processing too, it does not allow to write queries in a declarative manner, like XPath or XQuery. To overcome this problem, we propose a system that enables to query XML data with XPath, but it evaluates the queries in parallel using the MR framework. First, we introduce a persistent storage that maps XML data into a wide-column store. The proposed mapping enables efficient and distributed data processing. Secondly, we describe a query processor translating an XPath language subset to MR jobs. Finally, we present tests and their results showing the scalability of our system.