Feedback autonomic provisioning for guaranteeing performance in mapreduce systems
Companies have a fast growing amounts of data to process and store, a data explosion is
happening next to us. Currently one of the most common approaches to treat these vast data …
happening next to us. Currently one of the most common approaches to treat these vast data …
A control approach for performance of big data systems
We are at the dawn of a huge data explosion therefore companies have fast growing
amounts of data to process. For this purpose Google developed MapReduce, a parallel …
amounts of data to process. For this purpose Google developed MapReduce, a parallel …
Clotho: an elastic mapreduce workload/runtime co-design
W Shi, B Hong - Proceedings of the 12th International Workshop on …, 2013 - dl.acm.org
The resource management of a multi-tenant MapReduce cluster can be hard given
unpredictable user demands. Conventional resource management scheme would inevitably …
unpredictable user demands. Conventional resource management scheme would inevitably …
Improving data-analytics performance via autonomic control of concurrency and resource units
GJ Lee, JAB Fortes - ACM Transactions on Autonomous and Adaptive …, 2019 - dl.acm.org
Many big-data processing jobs use data-analytics frameworks such as Apache Hadoop
(currently also known as YARN). Such frameworks have tunable configuration parameters …
(currently also known as YARN). Such frameworks have tunable configuration parameters …
Aria: automatic resource inference and allocation for mapreduce environments
MapReduce and Hadoop represent an economically compelling alternative for efficient
large scale data processing and advanced analytics in the enterprise. A key challenge in …
large scale data processing and advanced analytics in the enterprise. A key challenge in …
Balanced resource allocations across multiple dynamic MapReduce clusters
Running multiple instances of the MapReduce framework concurrently in a multicluster
system or datacenter enables data, failure, and version isolation, which is attractive for many …
system or datacenter enables data, failure, and version isolation, which is attractive for many …
Using realistic simulation for performance analysis of mapreduce setups
Recently, there has been a huge growth in the amount of data processed by enterprises and
the scientific computing community. Two promising trends ensure that applications will be …
the scientific computing community. Two promising trends ensure that applications will be …
A game-theoretic approach for runtime capacity allocation in MapReduce
Nowadays many companies have available large amounts of raw, unstructured data. Among
Big Data enabling technologies, a central place is held by the MapReduce framework and …
Big Data enabling technologies, a central place is held by the MapReduce framework and …
An energy efficiency optimization and control model for hadoop clusters
H Wang, Y Cao - IEEE Access, 2019 - ieeexplore.ieee.org
The majority of large-scale data intensive applications designed by MapReduce model are
deployed and executed on a large-scale distributed Hadoop system. Running such …
deployed and executed on a large-scale distributed Hadoop system. Running such …
Dynamic split model of resource utilization in mapreduce
XW Wang, J Zhang, HM Liao, L Zha - … on Data intensive computing in the …, 2011 - dl.acm.org
MapReduce is gaining increasing popularity as a parallel programming model for large-
scale data processing. We find however some traditional MapReduce platforms have a poor …
scale data processing. We find however some traditional MapReduce platforms have a poor …