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计算机系统应用:2011,20(11):80-85
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分布式系统Hadoop 平台的视频转码
杨帆1, 沈奇威2
(1.北京邮电大学 网络与交换技术国家重点实验室,北京 100876;2.东信北邮信息技术有限公司,北京 100191)
Distributed Video Transcoding on Hadoop
YANG Fan1, SHEN Qi-Wei2
(1.State Key Lab of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;2.EB Information Technology Co. Ltd., Beijing 100191, China)
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投稿时间:2011-03-20    修订日期:2011-04-24
中文摘要: 在研究了目前主流的视频转码方案基础上,提出了一种分布式转码系统。系统采用HDFS(HadoopDistributed File System)进行视频存储,利用MapReduce 思想和FFMPEG 进行分布式转码。详细讨论了视频分布式存储时的分段策略,以及分段大小对存取时间的影响。同时,定义了视频存储和转换的元数据格式。提出了基于MapReduce 编程框架的分布式转码方案,即Mapper 端进行转码和Reducer 端进行视频合并。实验数据显示了转码时间随视频分段大小和转码机器数量不同而变化的趋势。结
中文关键词: 视频转码  分布式内容处理  Hadoop  FFMPEG
Abstract:Based on study of current video transcoding solutions, we proposed a distributed transcoding system. Video resources are stored in HDFS(Hadoop Distributed File System) and transcoded by MapReduce program using FFMPEG. In this paper, video segmentation strategy on distributed storage and how they affect accessing time are discussed. We also defined metadata of video formats and transcoding parameters. The distributed transcoding framework is proposed on basis of MapReduce programming model. Segmented source videos are transcoding in map tasks and merged into target video in reduce task. Experimental results show that transcoding time is dependent on segmentation size and trascoding cluster size. Compared with single PC, the proposed distributed video transcoding system implemented on 8 PCs can decrease about 80% of the transcoding time.
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基金项目:国家杰出青年科学基金(60525110);国家973 计划(2007CB307100,2007CB307103);国家自然科学基金(61072057,60902051);中央高校基本科 研业务费专项资金(BUPT2009RC0505);国家科技重大专项(2011ZX03002-001-01,2011ZX03002-002-01)
引用文本:
杨帆,沈奇威.分布式系统Hadoop 平台的视频转码.计算机系统应用,2011,20(11):80-85
YANG Fan,SHEN Qi-Wei.Distributed Video Transcoding on Hadoop.COMPUTER SYSTEMS APPLICATIONS,2011,20(11):80-85

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