Scarlett: coping with skewed content popularity in mapreduce clusters
By Ganesh Ananthanarayanan, Sameer Agarwal, Srikanth Kandula, Albert G. Greenberg, Ion Stoica, Duke Harlan, E. Harris. European Conference on Computer Systems, 2011
331 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/ae24289a0ed3152de528f863c96279382b14ae61
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Scott Shenker
- Sylvia Ratnasamy
- A. Sprintson
- Swanand Ravindra Kadhe
- Srikanth Kandula
- Randy Howard Katz
- Rodrigo Fonseca
- Eric Boutin
In Information Systems
- Scott Shenker
- Swanand Ravindra Kadhe
- A. Sprintson
- Rodrigo Fonseca
- Eric Boutin
- Sara Alspaugh
- Emina Soljanin
- Srikanth Kandula
Citations in the corpus
- Jockey: guaranteed job latency in data parallel clusters (2012, background): “Scarlett: Coping with Skewed Content Popularity in MapReduce Clusters.”
- Making Sense of Performance in Data Analytics Frameworks (2015, background): “Researchers have been able to identify and target a small number of underlying causes such as data skew [11] [26] [29] and popularity skew [7].”
- Analyzing the download time of availability codes (2015, methodology): “Fixed arrival regime is useful to understand the performance of Fork-Join model under highly skewed object popularities, which is known to be the typical case in practice [6].”
- Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads (2012, background): “There are some inaccuracies at trace start and termination, due to partial information for jobs straddling the trace boundaries.”