CFP: BEYONDMR’15 2nd Workshop on Algorithms and Systems for MapReduce and Beyond

Paolo Missier pmissier at
Mon Nov 3 08:34:43 CST 2014

* Call for papers *

2nd Workshop on Algorithms and Systems for MapReduce and Beyond, March 27, 2015.

Held in conjunction with EDBT/ICDT 2015
Brussels, Belgium, March 23-27, 2015

The second BeyondMR workshop aims to explore algorithms, computational models, architectures, languages and interfaces for systems that need large-scale parallelization and systems designed to support efficient parallelization and fault tolerance. These include specialized programming and data-management systems based on MapReduce and extensions, graph processing systems, data-intensive workflow and dataflow systems.

We invite submissions on topics such as

Frameworks for Large-Scale Analytical Processing: 
- Models, architectures and languages for data processing pipelines, data-intensive workflows, DAGs of operations/MapReduce jobs, dataflows, and data-mashups. 
- Extensions of MapReduce with more fundamental functions other than Map and Reduce and more complex dataflow connections between function inputs and outputs. 
- Expressing and parallelising iterations, incremental iterations, and programs consisting of large DAGs of operations. 
- Approaches to achiving fault tolerance and to recovering from failures.

Algorithms for Large-Scale Data Processing:
- Methods and techniques for designing efficient algorithms for MapReduce and similar systems.
- Experiments and experience with new algorithms in these settings. 

Cost Models and Optimization Techniques: 
- Formal definition of models that evaluate the efficiency of algorithms in large-scale parallel processing systems taking into account the requirements of such systems in different applications.
- Testing and benchmarking of MapReduce extensions and data-intensive workflows.

Resource Management for Many-Task Computing: 
- Scheduling of tasks and load-balancing techniques.
- Methods to tackle data skewness.
- Study of cases where automatic data distribution in MapReduce and similar systems does not provide sufficient data balancing.
- Design of algorithms that avoid skewness.
- Extensions of MapReduce that automatically tackle data skewness.

Papers submission deadline: Dec 11th, 2014
Authors notification:  Jan 7th, 2014
Deadline for camera-ready copy: Jan 20, 2014
Workshop: March 27, 2015

We invite full research or experience papers (up to 10 pages), or short papers (up to 4 pages) describing research in progress, formatted using the ACM double-column style (

The workshop proceedings will be published with EDBT/ICDT by the Center for European Union Research (CEUR).

Foto Afrati 	(National Technical University of Athens, Greece)
Jan Hidders 	(TU Delft, The Netherlands)
Frank McSherry	(Microsoft Research, formerly)
Paolo Missier 	(Newcastle University, UK)
Jacek Sroka 	(University of Warsaw, Poland)
Jeffrey Ullman	(Stanford University)

Program Committee (in progress)

Umut Acar				(CMU)
Khalid Belhajjame	(University Paris-Dauphine)
Sarah Cohen-Boulakia	(Universite Paris-Sud)
Asterios Katsifosdimos	(TU Berlin)
Cristoph Koch		(EPFL)
Dionysus Logothetis	(Telefonica Research)
Marta Mattoso		(Federal University of Rio de Janeiro)
Frank McSherry (Chair)	(Microsoft Research, formerly)
Derek Murray		(Microsoft Research, formerly)
Jelena Pjesivac-Grbovic	(Google)
Christopher Re		(Stanford)
Krzystof Rzadca		(University of Warsaw)
Piotr Sankowski		(University of Warsaw)
Mark Santcroos		(Rutgers)
Sergei Vassilvitskii	(Google)
Jianwu Wang 		(UCSD)
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