Title
On Efficient Hierarchical Storage for Big Data Processing
Abstract
A promising trend in storage management for big data frameworks, such as Hadoop and Spark, is the emergence of heterogeneous and hybrid storage systems that employ different types of storage devices, e.g. SSDs, RAMDisks, etc., alongside traditional HDDs. However, scheduling data accesses or requests to an appropriate storage device is non-trivial and depends on several factors such as data locality, device performance, and application compute and storage resources utilization. To this end, we present DUX, an application-attuned dynamic data management system for data processing frameworks, which aims to improve overall application I/O throughput by efficiently using SSDs only for workloads that are expected to benefit from them rather than the extant approach of storing a fraction of the overall workloads in SSDs. The novelty of DUX lies in profiling application performance on SSDs and HDDs, analyzing the resulting I/O behavior, and considering the available SSDs at runtime to dynamically place data in an appropriate storage tier. Evaluation of DUX with trace-driven simulations using synthetic Facebook workloads shows that even when using 5.5× fewer SSDs compared to a SSD-only solution, DUX incurs only a small (5%) performance overhead, and thus offers an affordable and efficient storage tier management.
Year
DOI
Venue
2016
10.1109/CCGrid.2016.61
2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)
Keywords
Field
DocType
MapReduce,data-intensive computing,heterogeneous storage,performance prediction,tiered storage
Spark (mathematics),Data-intensive computing,Scheduling (computing),Computer science,Computer data storage,Profiling (computer programming),Real-time computing,Dynamic data,Throughput,Big data,Operating system,Distributed computing
Conference
ISSN
ISBN
Citations 
2376-4414
978-1-5090-2454-4
8
PageRank 
References 
Authors
0.47
20
5
Name
Order
Citations
PageRank
K. R. Krish1654.17
Bharti Wadhwa280.47
M. Safdar Iqbal3934.76
M. Mustafa Rafique415715.49
Ali R Butt521017.36