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MapReduce scheduling algorithms in Hadoop: a systematic study
Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses
Hadoop Distributed File System (HDFS) for storing data and uses MapReduce to process …
Hadoop Distributed File System (HDFS) for storing data and uses MapReduce to process …
A survey on automatic parameter tuning for big data processing systems
Big data processing systems (eg, Hadoop, Spark, Storm) contain a vast number of
configuration parameters controlling parallelism, I/O behavior, memory settings, and …
configuration parameters controlling parallelism, I/O behavior, memory settings, and …
{AGILE}: Elastic distributed resource scaling for {Infrastructure-as-a-Service}
Dynamically adjusting the number of virtual machines (VMs) assigned to a cloud application
to keep up with load changes and interference from other uses typically requires detailed …
to keep up with load changes and interference from other uses typically requires detailed …
IoTDeM: An IoT Big Data-oriented MapReduce performance prediction extended model in multiple edge clouds
Abstract Uploading all IoT Big Data to a centralized cloud for data analytics is infeasible
because of the excessive latency and bandwidth limitation of the Internet. A promising …
because of the excessive latency and bandwidth limitation of the Internet. A promising …
ishuffle: Improving hadoop performance with shuffle-on-write
Hadoop is a popular implementation of the MapReduce framework for running data-
intensive jobs on clusters of commodity servers. Shuffle, the all-to-all input data fetching …
intensive jobs on clusters of commodity servers. Shuffle, the all-to-all input data fetching …
Hadoop performance modeling for job estimation and resource provisioning
MapReduce has become a major computing model for data intensive applications. Hadoop,
an open source implementation of MapReduce, has been adopted by an increasingly …
an open source implementation of MapReduce, has been adopted by an increasingly …
Improving performance of heterogeneous mapreduce clusters with adaptive task tuning
Datacenter-scale clusters are evolving toward heterogeneous hardware architectures due to
continuous server replacement. Meanwhile, datacenters are commonly shared by many …
continuous server replacement. Meanwhile, datacenters are commonly shared by many …
Optimizing analytic data flows for multiple execution engines
Next generation business intelligence involves data flows that span different execution
engines, contain complex functionality like data/text analytics, machine learning operations …
engines, contain complex functionality like data/text analytics, machine learning operations …
Heterogeneity and interference-aware virtual machine provisioning for predictable performance in the cloud
Infrastructure-as-a-service (IaaS) cloud providers offer tenants elastic computing resources
in the form of virtual machine (VM) instances to run their jobs. Recently, providing …
in the form of virtual machine (VM) instances to run their jobs. Recently, providing …
Cost-effective resource provisioning for mapreduce in a cloud
This paper presents a new MapReduce cloud service model, Cura, for provisioning cost-
effective MapReduce services in a cloud. In contrast to existing MapReduce cloud services …
effective MapReduce services in a cloud. In contrast to existing MapReduce cloud services …