Enhancing throughput of the Hadoop Distributed File System for interaction-intensive tasks

The Hadoop Distributed File System (HDFS) is designed to run on commodity hardware and can be used as a stand-alone general purpose distributed file system (Hdfs user guide, 2008). It provides the ability to access bulk data with high I/O throughput. As a result, this system is suitable for applicat...

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Vydané v:Journal of parallel and distributed computing Ročník 74; číslo 8; s. 2770 - 2779
Hlavní autori: Hua, Xiayu, Wu, Hao, Li, Zheng, Ren, Shangping
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Amsterdam Elsevier Inc 01.08.2014
Elsevier
Predmet:
Algorithms
Allocations
Applied sciences
Architecture
Cache
Commodities
Computer science; control theory; systems
Exact sciences and technology
Hardware
HDFS
Hierarchical structure
Interaction intensive task
Memory and file management (including protection and security)
Memory organisation. Data processing
Performance degradation
PSO
Software
Storage allocation algorithm
Tasks
Storage allocation algorithm
HDFS
Interaction intensive task
PSO
Cache
Hierarchical structure
Content access
Cache memory
File management
Storage system
Very large databases
Storage allocation
Particle swarm optimization
Massive parallelism
Transmission rate
Input output equipment
Hierarchical system
ISSN:0743-7315, 1096-0848
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Shrnutí:The Hadoop Distributed File System (HDFS) is designed to run on commodity hardware and can be used as a stand-alone general purpose distributed file system (Hdfs user guide, 2008). It provides the ability to access bulk data with high I/O throughput. As a result, this system is suitable for applications that have large I/O data sets. However, the performance of HDFS decreases dramatically when handling the operations of interaction-intensive files, i.e., files that have relatively small size but are frequently accessed. The paper analyzes the cause of throughput degradation issue when accessing interaction-intensive files and presents an enhanced HDFS architecture along with an associated storage allocation algorithm that overcomes the performance degradation problem. Experiments have shown that with the proposed architecture together with the associated storage allocation algorithm, the HDFS throughput for interaction-intensive files increases 300% on average with only a negligible performance decrease for large data set tasks. •Analyzed the performance degradation of HDFS caused by interaction-intensive tasks.•Designed a two-layer structure to improve the performance of handling I/O request.•Integrated caches to reduce the overhead of accessing interaction-intensive files.•Developed a PSO-based storage allocation algorithm to improve the I/O throughput.•Designed a set of experiments to evaluate the performance of the proposed methods.
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ISSN:0743-7315
1096-0848
DOI:10.1016/j.jpdc.2014.03.010