感想や聞いてきた内容のシェアはhadoopコードリーディング第10回で行いますが、自分用のメモというか探せた資料を掲載しておきます オープニングビデオ Day1 Keynotes 時間 Hall 1 A1 B1 A2 A3 C1 C3 10:30-11:10 Apache Hadoop MapReduce - What Next? Hadoop Summit 2012 Hadoop Distributed File System Reliability and Durability at Facebook Searching conversations with hadoop 11:25-12:05 Hdfs high availability Improving h base availability and repair Large-Scale Machine Learning at
香川県高松市にて開催されたALSIP2011(Second Workshop on Algorithms for Large-Scale Information Processing in Knowledge Discovery)に参加してきた。 簡潔データ構造で有名なRajeev Raman先生、NIIの定兼先生、PFIの岡野原さんが招待講演をして下さるということで以前から注目していた。 招待講演に加えて興味深い10本の発表がありとても楽しめた。私の勉強不足もあって初めて知ることが非常に多く勉強になった。簡単に内容をメモしておく(理解不足のため間違ったことを書いていたらすみません)。 今回の会議で最も興味深かったのがgrammer-based compressionというもので、これは例えばX=ababという文字列があったときにX1=a,X2=b,X3=X1X2,X=X3X3という感じで
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Hadoop is an open-source software framework for distributed storage and processing of large datasets across clusters of computers. It was inspired by Google's MapReduce and GFS papers. Hadoop allows for the distributed processing of large data sets across clusters of commodity hardware. It is designed to scale up from single servers to thousands of machines, each offering local computation and sto
This document discusses Hadoop and its use on Amazon Web Services. It describes how Hadoop can be used to process large amounts of data in parallel across clusters of computers. Specifically, it outlines how to run Hadoop jobs on an Elastic Compute Cloud (EC2) cluster configured with Hadoop and store data in Amazon Simple Storage Service (S3). The document also provides examples of using Hadoop St
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