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

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Minimization of Data Transfers during MapReduce Computations in Distributed Wide-Column Stores
Original language description
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.
Czech name
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Czech description
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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