DocumentCode :
3717179
Title :
Benchmarking key-value stores on high-performance storage and interconnects for web-scale workloads
Author :
Dipti Shankar;Xiaoyi Lu;Md. Wasi-ur-Rahman;Nusrat Islam;Dhabaleswar K. Panda
Author_Institution :
Department of Computer Science and Engineering, The Ohio State University
fYear :
2015
Firstpage :
539
Lastpage :
544
Abstract :
Leveraging a distributed key-value based caching layer has proven to be invaluable for scalable data-intensive web applications. With the emergence of high-performance storage (e.g. SSD) and interconnects (e.g. InfiniBand) on modern clusters, several efforts are being made to design high-performance key-value stores that can operate well with `RAM+SSD´ hybrid storage architecture. This has made it essential for us to design micro-benchmarks that are tailored to evaluate these upcoming, hybrid designs. In this paper, we study popular web-scale and cloud serving workloads, to identify different application-specific aspects, including commonly occurring data request distributions, update patterns, and environmental factors, that affect the performance of hybrid key-value stores. Based on these characterization studies, we propose a micro-benchmark suite that can be used to study high-performance, hybrid key-value stores on modern clusters, from the perspectives of both the application and the key-value store. We demonstrate its ease-of-use using database-integrated and stand-alone execution modes. Performance evaluations with different Memcached distributions, such as SSD-Assisted RDMA-Memcached, fatcache, and twemcache, over different networks/protocols, show that `SSD+RDMA´ can significantly enhance the performance of Memcached for various read-only and read-heavy workloads, that are representative of several common web-scale workloads.
Keywords :
"Benchmark testing","Databases","Servers","Internet","Environmental factors","Twitter"
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BigData.2015.7363797
Filename :
7363797
Link To Document :
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