Minimization of Data Transfers during MapReduce Computations in Distributed Wide-Column Stores

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F16%3A00302505" target="_blank" >RIV/68407700:21240/16:00302505 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007/978-3-319-44039-2_18" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-44039-2_18</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-44039-2_18" target="_blank" >10.1007/978-3-319-44039-2_18</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Minimization of Data Transfers during MapReduce Computations in Distributed Wide-Column Stores

Popis výsledku v původním jazyce

In this contribution, we present our original approach to distributed wide-column store database tuning based on data locality optimization. The main goal of the optimization is the reduction of communication overhead in distributed environment during Map-Reduce query evaluation. The optimization is realized by the minimisation of the total number of key-value pairs emitted from mappers. To achieve the goal, we combine several Map-Reduce optimization methods, adapt them to wide-column store model and utilize them to overcome architectural limitation. To prove our idea, we implemented the proposed solution in HBase system that represents this class of DBMS. We present our data, measurements, and tests. The evaluated results support our idea that this method can significantly decrease data transfers in the distributed system.

Název v anglickém jazyce

Minimization of Data Transfers during MapReduce Computations in Distributed Wide-Column Stores

Popis výsledku anglicky

In this contribution, we present our original approach to distributed wide-column store database tuning based on data locality optimization. The main goal of the optimization is the reduction of communication overhead in distributed environment during Map-Reduce query evaluation. The optimization is realized by the minimisation of the total number of key-value pairs emitted from mappers. To achieve the goal, we combine several Map-Reduce optimization methods, adapt them to wide-column store model and utilize them to overcome architectural limitation. To prove our idea, we implemented the proposed solution in HBase system that represents this class of DBMS. We present our data, measurements, and tests. The evaluated results support our idea that this method can significantly decrease data transfers in the distributed system.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

New Trends in Databases and Information Systems

ISBN

978-3-319-44065-1

ISSN

1865-0929

e-ISSN

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Počet stran výsledku

14

Strana od-do

261-274

Název nakladatele

Springer

Místo vydání

Wien

Místo konání akce

Praha

Datum konání akce

28. 8. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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