Weaving Relations for Cache Performance
Proceedings of the 27th International Conference on Very Large Data Bases
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
"One Size Fits All": An Idea Whose Time Has Come and Gone
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Interpreting the data: Parallel analysis with Sawzall
Scientific Programming - Dynamic Grids and Worldwide Computing
Map-reduce-merge: simplified relational data processing on large clusters
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Dryad: distributed data-parallel programs from sequential building blocks
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Evaluating MapReduce for Multi-core and Multiprocessor Systems
HPCA '07 Proceedings of the 2007 IEEE 13th International Symposium on High Performance Computer Architecture
Technical perspective: the data center is the computer
Communications of the ACM - 50th anniversary issue: 1958 - 2008
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Bigtable: A Distributed Storage System for Structured Data
ACM Transactions on Computer Systems (TOCS)
Pig latin: a not-so-foreign language for data processing
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Clustera: an integrated computation and data management system
Proceedings of the VLDB Endowment
Mars: a MapReduce framework on graphics processors
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
SCOPE: easy and efficient parallel processing of massive data sets
Proceedings of the VLDB Endowment
Ad-hoc data processing in the cloud
Proceedings of the VLDB Endowment
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
MapReduce for Data Intensive Scientific Analyses
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
Bioinformatics
Rethinking cost and performance of database systems
ACM SIGMOD Record
A comparison of approaches to large-scale data analysis
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Distributed data-parallel computing using a high-level programming language
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
MapReduce and parallel DBMSs: friends or foes?
Communications of the ACM - Amir Pnueli: Ahead of His Time
MapReduce: a flexible data processing tool
Communications of the ACM - Amir Pnueli: Ahead of His Time
Nephele: efficient parallel data processing in the cloud
Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
Proceedings of the VLDB Endowment
Building a high-level dataflow system on top of Map-Reduce: the Pig experience
Proceedings of the VLDB Endowment
Hive: a warehousing solution over a map-reduce framework
Proceedings of the VLDB Endowment
HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads
Proceedings of the VLDB Endowment
Optimizing joins in a map-reduce environment
Proceedings of the 13th International Conference on Extending Database Technology
ACM SIGOPS Operating Systems Review
On the energy (in)efficiency of Hadoop clusters
ACM SIGOPS Operating Systems Review
Nephele/PACTs: a programming model and execution framework for web-scale analytical processing
Proceedings of the 1st ACM symposium on Cloud computing
Towards automatic optimization of MapReduce programs
Proceedings of the 1st ACM symposium on Cloud computing
Pregel: a system for large-scale graph processing
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Efficient parallel set-similarity joins using MapReduce
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
ParaTimer: a progress indicator for MapReduce DAGs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Integrating hadoop and parallel DBMs
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A comparison of join algorithms for log processing in MaPreduce
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Ricardo: integrating R and Hadoop
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
A Map-Reduce System with an Alternate API for Multi-core Environments
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
An Analysis of Traces from a Production MapReduce Cluster
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
MapReduce for the cell broadband engine architecture
IBM Journal of Research and Development
To compress or not to compress - compute vs. IO tradeoffs for mapreduce energy efficiency
Proceedings of the first ACM SIGCOMM workshop on Green networking
Twister: a runtime for iterative MapReduce
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
Data-Intensive Text Processing with MapReduce
Data-Intensive Text Processing with MapReduce
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Improving MapReduce performance in heterogeneous environments
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Relational versus non-relational database systems for data warehousing
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
Energy management for MapReduce clusters
Proceedings of the VLDB Endowment
HaLoop: efficient iterative data processing on large clusters
Proceedings of the VLDB Endowment
Dremel: interactive analysis of web-scale datasets
Proceedings of the VLDB Endowment
The performance of MapReduce: an in-depth study
Proceedings of the VLDB Endowment
MRShare: sharing across multiple queries in MapReduce
Proceedings of the VLDB Endowment
Hadoop++: making a yellow elephant run like a cheetah (without it even noticing)
Proceedings of the VLDB Endowment
Cheetah: a high performance, custom data warehouse on top of MapReduce
Proceedings of the VLDB Endowment
Hadoop: The Definitive Guide
Automatic optimization for MapReduce programs
Proceedings of the VLDB Endowment
Column-oriented storage techniques for MapReduce
Proceedings of the VLDB Endowment
Processing theta-joins using MapReduce
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Llama: leveraging columnar storage for scalable join processing in the MapReduce framework
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
A platform for scalable one-pass analytics using MapReduce
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
RCFile: A fast and space-efficient data placement structure in MapReduce-based warehouse systems
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
MAP-JOIN-REDUCE: Toward Scalable and Efficient Data Analysis on Large Clusters
IEEE Transactions on Knowledge and Data Engineering
Compression-aware I/O performance analysis for big data clustering
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
High-performance online spatial and temporal aggregations on multi-core CPUs and many-core GPUs
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
HadoopXML: a suite for parallel processing of massive XML data with multiple twig pattern queries
Proceedings of the 21st ACM international conference on Information and knowledge management
A framework for readapting and running bioinformatics applications in the cloud
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Join processing using Bloom filter in MapReduce
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Making use of the big data: next generation of algorithm trading
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Speeding up large-scale point-in-polygon test based spatial join on GPUs
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
Journal of Computer and System Sciences
Evaluating MapReduce for profiling application traffic
Proceedings of the first edition workshop on High performance and programmable networking
High performance risk aggregation: addressing the data processing challenge the hadoop mapreduce way
Proceedings of the 4th ACM workshop on Scientific cloud computing
On distributed computation rate optimization for deploying cloud computing programming frameworks
ACM SIGMETRICS Performance Evaluation Review
Toward intersection filter-based optimization for joins in MapReduce
Proceedings of the 2nd International Workshop on Cloud Intelligence
Speeding-up codon analysis on the cloud with local MapReduce aggregation
Information Sciences: an International Journal
Parallel labeling of massive XML data with MapReduce
The Journal of Supercomputing
| Hi-index | 0.00 |
A prominent parallel data processing tool MapReduce is gaining significant momentum from both industry and academia as the volume of data to analyze grows rapidly. While MapReduce is used in many areas where massive data analysis is required, there are still debates on its performance, efficiency per node, and simple abstraction. This survey intends to assist the database and open source communities in understanding various technical aspects of the MapReduce framework. In this survey, we characterize the MapReduce framework and discuss its inherent pros and cons. We then introduce its optimization strategies reported in the recent literature. We also discuss the open issues and challenges raised on parallel data analysis with MapReduce.