2011 · 298 citations · 19 references
Cluster ComputingEngineeringData Streaming ArchitectureMap-reduceData ScienceData IntegrationParallel ComputingData ManagementComputer ScienceData-intensive ComputingScalable ComputingNon-incremental SystemsEdge ComputingCloud ComputingParallel ProgrammingNew EntriesCode ComplexityMassive Data ProcessingBig Data
Many online data sets evolve over time as new entries are slowly added and existing entries are deleted or modified. Taking advantage of this, systems for incremental bulk data processing, such as Google's Percolator, can achieve efficient updates. To achieve this efficiency, however, these systems lose compatibility with the simple programming models offered by non-incremental systems, e.g., MapReduce, and more importantly, requires the programmer to implement application-specific dynamic algorithms, ultimately increasing algorithm and code complexity.
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Sanjay Ghemawat · Communications of the ACM · 2008 · 18.4K citations · Full text
Christopher Olston, Benjamin Reed, Utkarsh Srivastava et al. · 2008 · 1.7K citations
A low-bandwidth network file system
Athicha Muthitacharoen, Benjie Chen, David Mazières · 2001 · 782 citations
Hardware Security, Cluster Computing, Distributed File System +14
Yingyi Bu, Bill Howe, Magdalena Bałazińska et al. · Proceedings of the VLDB Endowment · 2010 · 685 citations
Cluster Computing, Engineering, Hadoop Mapreduce Framework +16