2015Unpublished venueRequires access

Application Performance Analysis of Distributed File Systems under Cloud Computing Environment

Tiezhu Zhao, Zusheng Zhang, Xin Ao

Open publisher page 1 citations

Abstract

The processing efficiency of data-intensive application on Hadoop with the general-purpose distributed file system such as Lustre, as the backend file system, is not clear. This paper focuses on the similarities and differences between Lustre and HDFS (Hadoop Distributed File System). We propose a Hadoop-Lustre platform and evaluate the performance differences of Lustre and HDFS by using a set of data-intensive computing benchmarks. Experimental results indicate Lustre can reach parity with HDFS, or even better than HDFS if the much faster network interconnect is available. It is necessary to study non-HDFS distributed file system to make up the performance lack of HDFS in some MapReduce-based application scenarios.

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What this paper is about

The processing efficiency of data-intensive application on Hadoop with the general-purpose distributed file system such as Lustre, as the backend file system, is not clear. This paper focuses on the similarities and differences between Lustre and HDFS (Hadoop Distributed File System). We propose a Hadoop-Lustre platform and evaluate the performance differences of Lustre and HDFS by using a set of data-intensive computing benchmarks. Experimental results indicate Lustre can reach parity with HDFS, or even better than HDFS if the much faster network interconnect is available. It is necessary to study non-HDFS distributed file system to make up the performance lack of HDFS in some MapReduce-based application scenarios.

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Available abstract

The processing efficiency of data-intensive application on Hadoop with the general-purpose distributed file system such as Lustre, as the backend file system, is not clear. This paper focuses on the similarities and differences between Lustre and HDFS (Hadoop Distributed File System). We propose a Hadoop-Lustre platform and evaluate the performance differences of Lustre and HDFS by using a set of data-intensive computing benchmarks. Experimental results indicate Lustre can reach parity with HDFS, or even better than HDFS if the much faster network interconnect is available. It is necessary to study non-HDFS distributed file system to make up the performance lack of HDFS in some MapReduce-based application scenarios.

Key concepts: Lustre (file system), Distributed File System, Computer science, Operating system, Cloud computing, File system, Virtual file system, Database

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