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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xianqiang Bao Ling Liu Nong Xiao Yang Zhou Qi Zhang |
| Copyright Year | 2015 |
| Description | Author affiliation: Distrib. Data Intensive Syst. Lab., Georgia Inst. of Technol., Atlanta, GA, USA (Ling Liu; Yang Zhou; Qi Zhang) || State Key Lab. of High Performance Comput., Nat. Univ. of Defense Technol., Hunan, China (Xianqiang Bao; Nong Xiao) |
| Abstract | NoSQL systems have become the vital components to deliver big data services in the Cloud. However, existing NoSQL systems rely on experienced administrators to configure and tune the wide range of configurable parameters in order to achieve high performance. In this paper, we present a policy-driven configuration management system for NoSQL systems, called PCM. PCM can identify workload sensitive configuration parameters and capture the tuned parameters for different workloads as configuration policies. PCM also can be used to analyze the range of configuration parameters that may impact on the runtime performance of NoSQL systems in terms of read and write workloads. The configuration optimization recommended by PCM can enable NoSQL systems such as HBase to run much more efficiently than the default settings for both individual worker node and entire cluster in the Cloud. Our experimental results show that HBase under the PCM configuration outperforms the default configuration and some simple configurations on a range of workloads with offering significantly higher throughput. |
| Starting Page | 245 |
| Ending Page | 252 |
| File Size | 298040 |
| Page Count | 8 |
| File Format | |
| ISSN | 21596190 |
| e-ISBN | 9781467372879 |
| DOI | 10.1109/CLOUD.2015.41 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-27 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Phase change materials Loading Throughput Compaction Tuning Optimization Monitoring |
| Content Type | Text |
| Resource Type | Article |
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