2012 · 109 citations · 7 references
ComputingComputer ScienceCluster ComputingDatabasesDistributed SystemsDatabase ManagementDimensional ModelingDistributed ComputingDistributed Data ProcessingDistributed Database ArchitectureDistributed DatabasesMulti-dimensional DatabasesMultidimensional ModelsScalable Data ManagementScalable Database Design
A crucial element of large web companies is their ability to collect and analyze massive amounts of data. Tuple store databases are a key enabling technology employed by many of these companies (e.g., Google Big Table and Amazon Dynamo). Tuple stores are highly scalable and run on commodity clusters, but lack interfaces to support efficient development of mathematically based analytics. D4M (Dynamic Distributed Dimensional Data Model) has been developed to provide a mathematically rich interface to tuple stores (and structured query language “SQL” databases). D4M allows linear algebra to be readily applied to databases. Using D4M, it is possible to create composable analytics with significantly less effort than using traditional approaches. This work describes the D4M technology and its application and performance.
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The Hadoop Distributed File System
Konstantin V. Shvachko, Hairong Kuang, Sanjay Radia et al. · 2010 · 4.8K citations
Fay W. Chang, Sanjay Ghemawat, Wilson C. Hsieh et al. · ACM Transactions on Computer Systems · 2008 · 3.4K citations
Jeremy Kepner, Stan Ahalt · Journal of Parallel and Distributed Computing · 2004 · 60 citations · Full text