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Optimizing and Tuning MapReduce Jobs to Improve the Large-Scale Data Analysis Process
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/jpdc.1996.0092openalex-snapshot
Array Decompositions for Nonuniform Computational Environments
inferredcites →https://doi.org/10.1007/978-1-4302-1943-9_6openalex-snapshot
Tuning Your MapReduce Jobs
inferredcites →https://doi.org/10.1007/978-3-642-25821-3_9openalex-snapshot
Resource Provisioning Framework for MapReduce Jobs with Performance Goals
inferredcites →https://doi.org/10.1016/j.ipm.2010.12.003openalex-snapshot
MapReduce indexing strategies: Studying scalability and efficiency
inferredcites →https://doi.org/10.1023/b:dapd.0000028553.70337.e1openalex-snapshot
Main Memory-Based Algorithms for Efficient Parallel Aggregation for Temporal Databases
inferredcites →https://doi.org/10.1109/71.920590openalex-snapshot
A framework for integrating data alignment, distribution, and redistribution in distributed memory multiprocessors
inferredcites →https://doi.org/10.1109/ccis.2011.6045089openalex-snapshot
A comparative review of job scheduling for MapReduce
inferredcites →https://doi.org/10.1109/cit.2010.458openalex-snapshot
SAMR: A Self-adaptive MapReduce Scheduling Algorithm in Heterogeneous Environment
inferredcites →https://doi.org/10.1109/clustr.2009.5289171openalex-snapshot
HPMR: Prefetching and pre-shuffling in shared MapReduce computation environment
inferredcites →https://doi.org/10.1109/icpads.2009.88openalex-snapshot
Accelerating MapReduce with Distributed Memory Cache
inferredcites →https://doi.org/10.1109/tkde.2010.248openalex-snapshot
MAP-JOIN-REDUCE: Toward Scalable and Efficient Data Analysis on Large Clusters
inferredcites →https://doi.org/10.1109/tpds.2010.207openalex-snapshot
Data Replication in Data Intensive Scientific Applications with Performance Guarantee
inferredcites →https://doi.org/10.1109/tpds.2011.67openalex-snapshot
Toward Efficient and Simplified Distributed Data Intensive Computing
inferredcites →https://doi.org/10.1145/1559845.1559865openalex-snapshot
A comparison of approaches to large-scale data analysis
inferredcites →https://doi.org/10.1145/1739041.1739056openalex-snapshot
Optimizing joins in a map-reduce environment
inferredcites →https://doi.org/10.1145/1807167.1807273openalex-snapshot
A comparison of join algorithms for log processing in MaPreduce
inferredcites →https://doi.org/10.1145/2002945.2002947openalex-snapshot
Distributed tuning of machine learning algorithms using MapReduce Clusters
inferredcites →https://doi.org/10.1155/2005/962135openalex-snapshot
Interpreting the Data: Parallel Analysis with Sawzall
inferredcites →https://doi.org/10.1177/1094342006061887openalex-snapshot
Data Redistribution Algorithms for Heterogeneous Processor Rings
inferredcites →https://doi.org/10.1186/1471-2105-11-s12-s3openalex-snapshot
Hybrid cloud and cluster computing paradigms for life science applications
inferredcites →https://doi.org/10.21276/ijre.2018.5.5.4openalex-snapshot
MapReduce: Simplified Data Processing on Large Cluster
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Artificial Intelligence Usefulness Effect on Business Performance with Trust
inferred← citeshttps://doi.org/10.1007/978-981-16-8774-7_6openalex-snapshot
Accelerating Polynomial-Based Image Secret Sharing Using Hadoop
inferred← citeshttps://doi.org/10.1007/s10766-015-0395-0openalex-snapshot
MapReduce Parallel Programming Model: A State-of-the-Art Survey
inferred← citeshttps://doi.org/10.1016/b978-0-12-805394-2.00009-xopenalex-snapshot
System Optimization for Big Data Processing
inferred← citeshttps://doi.org/10.1109/access.2020.2984778openalex-snapshot
A Novel Configuration Tuning Method Based on Feature Selection for Hadoop MapReduce
inferred← citeshttps://doi.org/10.1109/hpcsim.2013.6641478openalex-snapshot
Improving performance of content-based image retrieval schemes using Hadoop MapReduce
inferred← citeshttps://doi.org/10.1109/hpcsim.2013.6641485openalex-snapshot
Applying Hadoop's MapReduce framework on clustering the GPS signals through cloud computing
inferred← citeshttps://doi.org/10.1109/iadcc.2014.6779400openalex-snapshot
Finding nearest facility location with open box query using Geohashing and MapReduce
inferred← citeshttps://doi.org/10.1109/iceiec.2018.8473562openalex-snapshot
An Novel Parameter Tuning Alogrithm for MapReduce Model
inferred← citeshttps://doi.org/10.1109/icsec.2014.6978204openalex-snapshot
Automatic extraction of topics on big data streams through scalable advanced analysis
inferred← citeshttps://doi.org/10.1109/ictke.2013.6756291openalex-snapshot
A parallel processing framework using MapReduce for content-based image retrieval
inferred← citeshttps://doi.org/10.1109/ictke.2014.7001539openalex-snapshot
Applying MVC data model on hadoop for delivering the business intelligence
inferred← citeshttps://doi.org/10.1109/jsyst.2020.3022286openalex-snapshot
Noninvasive MapReduce Performance Tuning Using Multiple Tuning Methods on Hadoop
inferred← citeshttps://doi.org/10.1109/ms.2020.3044598openalex-snapshot
An Open Source Project for Tuning and Analyzing MapReduce Performance in Hadoop and Spark
inferred← citeshttps://doi.org/10.1109/sii.2014.7028092openalex-snapshot
Big data topic modeling with mahout for managing business analysis services
inferred← citeshttps://doi.org/10.17762/itii.v2i2.14openalex-snapshot
Towards an Ontology-Based Semantic Approach to Tuning Parameters to Improve Hadoop Application Performance
inferred← citeshttps://doi.org/10.48550/arxiv.1912.12456openalex-snapshot
An Open-Source Project for MapReduce Performance Self-Tuning
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