Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/66790

TitleFast online analytical processing for Big Data warehousing
Author(s)Correia, José
Santos, Maribel Yasmina
Costa, Carlos A. P.
Andrade, Carina
KeywordsBig Data
Druid
Interactive queries
OLAP
Issue date2018
PublisherIEEE
Abstract(s)In an organizational context where data volume is continuously growing, Online Analytical Processing capabilities are necessary to ensure timely data processing for users that need interactive query processing to support the decision -making process. This paper benchmarks an innovative column -oriented distributed data store, Druid, evaluating its performance in interactive analytical workloads and verifying the impact that different data organizations strategies have in its performance. To achieve this goal, the well-known Star Schema Benchmark is used to verify the impact that the concepts of segments, query granularity and partitions or shards have in the space required to store the data and in the time needed to process it. The obtained results show that scenarios that use partitions usually achieve better processing times, even when that implies an increase in the needed storage space.
TypeConference paper
URIhttp://hdl.handle.net/1822/66790
ISBN9781538670972
DOI10.1109/IS.2018.8710583
Publisher versionhttps://ieeexplore.ieee.org/document/8710583
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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