Publication | Closed Access
Data-intensive text processing with MapReduce
450
Citations
134
References
2009
Year
Unknown Venue
Cluster ComputingEngineeringMap-reduceText MiningInformation RetrievalData ScienceHadoop ProgramsData-intensive PlatformData IntegrationParallel ComputingData ManagementHadoop ClustersData-intensive Text ProcessingKnowledge DiscoveryComputer ScienceData-intensive ComputingCloud ComputingParallel ProgrammingMassive Data ProcessingBig Data
This half-day tutorial introduces participants to data-intensive text processing with the MapReduce programming model [1], using the open-source Hadoop implementation. The focus will be on scalability and the tradeoffs associated with distributed processing of large datasets. Content will include general discussions about algorithm design, presentation of illustrative algorithms, case studies in HLT applications, as well as practical advice in writing Hadoop programs and running Hadoop clusters.
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