Towards automatic optimization of MapReduce programs
By Shivnath Babu. ACM Symposium on Cloud Computing, 2010
314 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/93e01a888a7c05f36ab6407abb2644c4c325c520
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
- Rolf Stadler
- Brendan Jennings
- Herodotos Herodotou
- Tat-seng Chua
- Yon Dohn Chung
- Bongki Moon
- Shivnath Babu
- Yonggang Wen
In Information Systems
- Rolf Stadler
- Brendan Jennings
- Herodotos Herodotou
- Tat-seng Chua
- Yon Dohn Chung
- Bongki Moon
- Shivnath Babu
- Yonggang Wen
Citations in the corpus
- Parallel data processing with MapReduce: a survey (2012, background): “Babu et al suggest an automatic tuning approach to finding optimal system parameters for given input data [5].”
- Profiling, what-if analysis, and cost-based optimization of MapReduce programs (2011, background): “Personal communication, our own experience [3, 15], and plenty of anecdotal evidence on the Web indicate that finding good configuration settings for MapReduce jobs is time consuming and requires extensive knowledge of system internals.”
- Toward Scalable Systems for Big Data Analytics: A Technology Tutorial (2014, background): “[272] proposed an automatic tuning approach to find optimal system parameters for the given input data.”
- Resource Management in Clouds: Survey and Research Challenges (2015, background): “Further, a general mechanism could be developed through which a Cloud Provider can pass information about current and expected resource availability to a Cloud User, which then uses the information to optimize its application, as has been demonstrated for MapReduce implementations [19, 103, 184, 235”