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Using a Tunable Knob for Reducing Makespan of MapReduce Jobs in a Hadoop Cluster
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/nav.3800010110openalex-snapshot
Optimal two‐ and three‐stage production schedules with setup times included
inferredcites →https://doi.org/10.1007/978-3-642-25821-3_10openalex-snapshot
Resource-Aware Adaptive Scheduling for MapReduce Clusters
inferredcites →https://doi.org/10.1109/cloud.2012.37openalex-snapshot
MROrchestrator: A Fine-Grained Resource Orchestration Framework for MapReduce Clusters
inferredcites →https://doi.org/10.1109/mascots.2012.12openalex-snapshot
Two Sides of a Coin: Optimizing the Schedule of MapReduce Jobs to Minimize Their Makespan and Improve Cluster Performance
inferredcites →https://doi.org/10.1109/noms.2010.5488494openalex-snapshot
Performance-driven task co-scheduling for MapReduce environments
inferredcites →https://doi.org/10.1145/2087522.2087528openalex-snapshot
Dynamic split model of resource utilization in MapReduce
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-981-10-0129-1_4openalex-snapshot
Apache Hadoop Yarn MapReduce Job Classification Based on CPU Utilization and Performance Evaluation on Multi-cluster Heterogeneous Environment
inferred← citeshttps://doi.org/10.1109/access.2021.3089907openalex-snapshot
Optimizing Internal Overlaps by Self-Adjusting Resource Allocation in Multi-Stage Computing Systems
inferred← citeshttps://doi.org/10.1109/cloud.2014.106openalex-snapshot
FRESH: Fair and Efficient Slot Configuration and Scheduling for Hadoop Clusters
inferred← citeshttps://doi.org/10.1109/cloud.2014.34openalex-snapshot
HaSTE: Hadoop YARN Scheduling Based on Task-Dependency and Resource-Demand
inferred← citeshttps://doi.org/10.1109/icsns.2015.7292373openalex-snapshot
Apache Hadoop Yarn Parameter configuration Challenges and Optimization
inferred← citeshttps://doi.org/10.1109/padsw.2018.8644997openalex-snapshot
An Overview on the Convergence of High Performance Computing and Big Data Processing
inferred← citeshttps://doi.org/10.1109/pccc.2015.7410279openalex-snapshot
OMO: Optimize MapReduce overlap with a good start (reduce) and a good finish (map)
inferred← citeshttps://doi.org/10.1109/tcc.2019.2894779openalex-snapshot
New Scheduling Algorithms for Improving Performance and Resource Utilization in Hadoop YARN Clusters
inferred← citeshttps://doi.org/10.1145/2801948.2801953openalex-snapshot
Dynamic reduce task adjustment for hadoop workloads
inferred← citeshttps://doi.org/10.17760/d20195695openalex-snapshot
Resource management in cluster computing platforms for large scale data processing
inferred← citeshttps://doi.org/10.2174/2666255816666230608165146openalex-snapshot
Performance Challenges and Solutions in Big Data Platform Hadoop
inferred← citeshttps://doi.org/10.26686/wgtn.17145944openalex-snapshot
Resource and Performance Modelling of Hadoop Clusters Using Machine Learning
inferred← citeshttps://doi.org/10.26686/wgtn.17145944.v1openalex-snapshot
Resource and Performance Modelling of Hadoop Clusters Using Machine Learning
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