Abstract
As MapReduce becomes more and more popular in data processing applications, the demand for Hadoop clusters grows. However, Hadoop is incompatible with existing cluster batch job queuing systems and requires a dedicated cluster under its full control. Hadoop also lacks support for user access control, accounting, fine-grain performance monitoring and legacy batch job processing facilities comparable to existing cluster job queuing systems, making dedicated Hadoop clusters less amenable for administrators and normal users alike with hybrid computing needs involving both MapReduce and legacy applications. As a result, getting a properly suited and sized Hadoop cluster has not been easy in organizations with existing clusters. This paper presents CloudBATCH, a prototype solution to this problem enabling Hadoop to function as a traditional batch job queuing system with enhanced functionality for cluster resource management. With CloudBATCH, a complete shift to Hadoop for managing an entire cluster to cater for hybrid computing needs becomes feasible.
| Original language | English |
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| Title of host publication | Proceedings - 2nd IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2010 |
| Pages | 368-375 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2010 |
| Externally published | Yes |
| Event | IEEE International Conference on Cloud Computing Technology and Science 2010 - Indianapolis, United States of America Duration: 30 Nov 2010 → 3 Dec 2010 Conference number: 2nd |
Conference
| Conference | IEEE International Conference on Cloud Computing Technology and Science 2010 |
|---|---|
| Abbreviated title | CloudCom 2010 |
| Country/Territory | United States of America |
| City | Indianapolis |
| Period | 30/11/10 → 3/12/10 |