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Challenges for MapReduce in Big Data
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-4302-5762-2openalex-snapshot
Big Data Analytics Using Splunk
inferredcites →https://doi.org/10.1007/978-3-642-16248-0_88openalex-snapshot
The High-Activity Parallel Implementation of Data Preprocessing Based on MapReduce
inferredcites →https://doi.org/10.1007/s00778-013-0319-9openalex-snapshot
A survey of large-scale analytical query processing in MapReduce
inferredcites →https://doi.org/10.1016/j.future.2013.07.001openalex-snapshot
Achieving Accountable MapReduce in cloud computing
inferredcites →https://doi.org/10.1089/big.2012.1501openalex-snapshot
Mapreduce is Good Enough?If All You Have is a Hammer, Throw Away Everything That's Not a Nail!
inferredcites →https://doi.org/10.1089/big.2013.0010openalex-snapshot
Bring the Noise: Embracing Randomness Is the Key to Scaling Up Machine Learning Algorithms
inferredcites →https://doi.org/10.1109/bigdata.2013.6691798openalex-snapshot
Access control for big data using data content
inferredcites →https://doi.org/10.1109/bigdata.congress.2013.25openalex-snapshot
Countering the Concept-Drift Problem in Big Data Using iOVFDT
inferredcites →https://doi.org/10.1109/cloudcom.2011.17openalex-snapshot
Scalable and Low-Latency Data Processing with Stream MapReduce
inferredcites →https://doi.org/10.1109/icdmw.2010.172openalex-snapshot
S4: Distributed Stream Computing Platform
inferredcites →https://doi.org/10.1109/ldav.2011.6092321openalex-snapshot
Parallel visualization on large clusters using MapReduce
inferredcites →https://doi.org/10.1145/2331042.2331058openalex-snapshot
Interactive analysis of big data
inferredcites →https://doi.org/10.1145/2351316.2351317openalex-snapshot
Unexpected challenges in large scale machine learning
inferredcites →https://doi.org/10.1145/2503009openalex-snapshot
Distributed data management using MapReduce
inferredcites →https://doi.org/10.1145/2522968.2522979openalex-snapshot
The family of mapreduce and large-scale data processing systems
inferredcites →https://doi.org/10.1186/2192-113x-2-22openalex-snapshot
Data management in cloud environments: NoSQL and NewSQL data stores
inferredcites →https://doi.org/10.14778/1454159.1454204openalex-snapshot
Ad-hoc data processing in the cloud
inferredcites →https://doi.org/10.14778/2350229.2350259openalex-snapshot
Processing a trillion cells per mouse click
inferredcites →https://doi.org/10.14778/2367502.2367519openalex-snapshot
Interactive analytical processing in big data systems
inferredcites →https://doi.org/10.5555/1855711.1855731openalex-snapshot
Airavat: security and privacy for MapReduce
inferredcites →https://doi.org/10.5555/1924943.1924962openalex-snapshot
Reining in the outliers in map-reduce clusters using Mantri
inferredcites →https://doi.org/10.5860/choice.50-5095openalex-snapshot
Big data analytics: turning big data into big money
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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