Abstract
Elastic Hadoop applications consisting of multiple virtual machines (VMs) are widely used to support big data analysis and processing. In this scenario, flash-based solid state drive (SSD) is usually deployed on hypervisors and used as the cache to improve the IO performance. However, existing SSD caching schemes are mostly VM-centric, which focus on the low-level IO performance metrics of individual VMs. They may not lead to the optimized performance of elastic Hadoop applications, i.e., the job completion time (JCT), as the importance of VMs inside the application are different even though they have the similar low-level IO patterns. Considering the IO dependency among VMs and figuring out the importance, which we regard as the application-centric metrics, may potentially better improve the performance. We present IO dependency based requirement model, to characterize the requirement of SSD cache for each VM inside the elastic Hadoop application, and then use it in a genetic algorithm (GA) based approach to calculate the nearly optimal weights of VMs for allocating the per-VM SSD cache space and the capacity of the I/O operations per second (IOPS). Furthermore, we present a tool AC-SSD based on the approach and introduce the closed-loop adaptation to react to continuously changing workloads. The evaluation shows that by using AC-SSD, the JCT is reduced by up to 39% for IO sensitive workloads, up to 29% for continuously changing workloads, and over 12.5% for different scale of data comparing to the shared cache.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Shvachko K, Hairong K, Radia S, et al. The hadoop distributed file system. In: Proceedings of the 26th Symposium on Mass Storage Systems and Technologies (MSST), Incline Village, 2010
Wei H F, De Biasi M, Huang Y, et al. Verifying pipelined-RAM consistency over read/write traces of data replicas. IEEE Trans Parallel Distrib Syst, 2016, 27: 1511–1523
Wei H F, Huang Y, Lu J. Probabilistically-atomic 2-atomicity: enabling almost strong consistency in distributed storage systems. IEEE Trans Comput, 2017, 66: 502–514
Kim J, Lee D, Noh S H. Towards slo complying SSDs through ops isolation. In: Proceedings of the 13th USENIX Conference on File and Storage Technologies (FAST), Santa Clara, 2015. 183–189
Lu L, Pillai T S, Arpaci-Dusseau A C, et al. WiscKey: separating keys from values in SSD-conscious storage. In: Proceedings of the 14th Usenix Conference on File and Storage Technologies (FAST), Santa Clara, 2016. 133–148
Hansen J G, Jul E. Lithium: virtual machine storage for the cloud. In: Proceedings of the 1st ACM Symposium on Cloud Computing (SoCC), Indianapolis, 2010. 15–26
Ye L, Lu G, Kumar S, et al. Energy-efficient storage in virtual machine environments. In: Proceedings of the 6th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE), Pittsburgh, 2010. 75–84
Arteaga D, Cabrera J, Xu J, et al. CloudCache: on-demand flash cache management for cloud computing. In: Proceedings of the 14th Usenix Conference on File and Storage Technologies (FAST), Berkeley, 2016. 355–369
Byan S, Lentini J, Madan A, et al. Mercury: host-side flash caching for the data center. In: Proceedings of the 28th Symposium on Mass Storage Systems and Technologies (MSST), San Diego, 2012
Koller R, Mashtizadeh A J, Rangaswami R. Centaur: host-side SSD caching for storage performance control. In: Proceedings of IEEE International Conference on Autonomic Computing (ICAC), Grenoble, 2015. 51–60
Oh Y, Lee E, Hyun C, et al. Enabling cost-effective flash based caching with an array of commodity SSDs. In: Proceedings of the 16th Annual Middleware Conference, Vancouver, 2015. 63–74
Tang Z, Wang W, Huang Y, et al. Application-centric SSD cache allocation for hadoop applications. In: Proceedings of the 9th Asia-Pacific Symposium on Internetware, Shanghai, 2017
Vavilapalli V K, Murthy A C, Douglas C, et al. Apache hadoop yarn: yet another resource negotiator. In: Proceedings of the 4th Annual Symposium on Cloud Computing (SoCC), Santa Clara, 2013
George L. HBase — The Definitive Guide: Random Access to Your Planet-Size Data. Sebastopol: O’Reilly Media, 2011
Agarwal G, Shah R, Walrand J, et al. An architectural blueprint for autonomic computing. IBM White Paper. 2013. http://users.cs.fiu.edu/~sadjadi/Teaching/Autonomic%20Grid%20Computing/CIS-6612-Summer-2006/AC-Blueprint-WhitePaper-V7.pdf
Barham P, Dragovic B, Fraser K, et al. Xen and the art of virtualization. In: Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP), New York, 2003. 164–177
Huang S S, Huang J, Dai J Q, et al. The HiBench benchmark suite: characterization of the mapreduce-based data analysis. In: Proceedings of the 26th International Conference on Data Engineering Workshops (ICDEW), Long Beach, 2010. 41–51
Tang Z, Wu H, Sun L, et al. Transaction-aware SSD cache allocation for the virtualization environment. In: Proceedings of the 12th International Symposium on Service-Oriented System Engineering Workshops (SOSEW), Bamberg, 2018. 174–179
Shamma M, Meyer D T, Wires J, et al. Capo: recapitulating storage for virtual desktops. In: Proceedings of the 9th USENIX Conference on File and Stroage Technologies (FAST), San Jose, 2011
Luo T, Ma S Y, Lee R B, et al. S-CAVE: effective SSD caching to improve virtual machine storage performance. In: Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques (PACT), Edinburgh, 2013. 103–112
Meng F, Zhou L, Ma X S, et al. vCacheShare: automated server flash cache space management in a virtualization environment. In: Proceedings of the 2014 USENIX Conference on USENIX Annual Technical Conference (USENIX ATC), Philadelphia, 2014. 133–144
Acknowledgements
This work was supported by National Key Research and Development Program of China (Grant No. 2016YFB1000103), National Natural Science Foundation of China (Grant No. 61572480), Tianjin Massive Data Processing Technology Laboratory, and Youth Innovation Promotion Association, Chinese Academy of Sciences (Grant No. 2015088).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Tang, Z., Wang, W., Sun, L. et al. IO dependent SSD cache allocation for elastic Hadoop applications. Sci. China Inf. Sci. 61, 050104 (2018). https://doi.org/10.1007/s11432-017-9401-y
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11432-017-9401-y