Distributed Evaluation of XPath Axes Queries over Large XML Documents Stored in MapReduce Clusters

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F14%3A00224323" target="_blank" >RIV/68407700:21240/14:00224323 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21240/14:00221194

Výsledek na webu

<a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6974858" target="_blank" >http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6974858</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/DEXA.2014.59" target="_blank" >10.1109/DEXA.2014.59</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Distributed Evaluation of XPath Axes Queries over Large XML Documents Stored in MapReduce Clusters

Popis výsledku v původním jazyce

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 awide-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 s

Název v anglickém jazyce

Distributed Evaluation of XPath Axes Queries over Large XML Documents Stored in MapReduce Clusters

Popis výsledku anglicky

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 awide-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 s

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Database and Expert Systems Applications (DEXA), 2014 25th International Workshop on

ISBN

978-1-4799-5722-4

ISSN

1529-4188

e-ISSN

—

Počet stran výsledku

5

Strana od-do

253-257

Název nakladatele

IEEE Computer Soc.

Místo vydání

Los Alamitos, CA

Místo konání akce

Munich

Datum konání akce

1. 9. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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