Abstract
MapReduce is a commonly used framework for executing data-intensive tasks on distributed server clusters. We present Coded MapReduce, a new framework that enables and exploits a particular form of coding to significantly reduce the inter-server communication load of MapReduce. In particular, Coded MapReduce exploits the repetitive mapping of data blocks at different servers to create coded multicasting opportunities in the shuffling phase, cutting down the total communication load by a multiplicative factor that grows linearly with the number of servers in the cluster. We also analyze the tradeoff between the computation load and the communication load of the Coded MapReduce.
Original language | English (US) |
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Title of host publication | 2015 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 964-971 |
Number of pages | 8 |
ISBN (Electronic) | 9781509018239 |
DOIs | |
State | Published - Apr 4 2016 |
Externally published | Yes |
Event | 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015 - Monticello, United States Duration: Sep 29 2015 → Oct 2 2015 |
Publication series
Name | 2015 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015 |
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Other
Other | 53rd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2015 |
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Country/Territory | United States |
City | Monticello |
Period | 9/29/15 → 10/2/15 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.