Profiling, what-if analysis, and cost-based optimization of MapReduce programs

By Herodotos Herodotou, Shivnath Babu. Proceedings of the VLDB Endowment, 2011

414 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/0b5105bbe6635b55d8a0677071b44e4000f2f6d4

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

1. Ameet Talwalkar
2. M. Franklin
3. Evan R. Sparks
4. Michael I. Jordan
5. Tim Kraska
6. Di Xie
7. Ning Ding
8. Y. C. Hu

In Information Systems

1. M. Franklin
2. Ameet Talwalkar
3. Michael I. Jordan
4. Tim Kraska
5. Di Xie
6. Ning Ding
7. Y. C. Hu
8. Ramana Rao Kompella

Citations in the corpus

• Automating model search for large scale machine learning (2015, background): “[23] explore performance modeling for MapReduce jobs on Hadoop clusters in great depth, but their model requires extensive profiling in order to accurately estimate job completion time.”
• The only constant is change: incorporating time-varying network reservations in data centers (2012, methodology): “PROTEUS shares the same pro.ling methodology with Elasti­sizer [22], StarFish [23] and CBO [21] which focus on choos­ing the type and number of VMs for MapReduce jobs to balance cost/performance objectives.”