Cloudera Impala：Apache Hadoopã§å®Ÿç¾ã™ã‚‹ã€çœŸã®ãƒªã‚¢ãƒ«ã‚¿ã‚¤ãƒ クエリ | Cloudera Japan
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グーグルãŒMapReduce特許をå–得。Hadoopã¸ã®å½±éŸ¿ã¯ï¼Ÿ
大è¦æ¨¡ãªãƒ‡ãƒ¼ã‚¿ã‚’分散処ç†ã™ã‚‹ãŸã‚ã®ãƒ•ãƒ¬ãƒ¼ãƒ ワークã§ã‚ã‚‹MapReduce。グーグルãŒæ¤œç´¢ã‚¨ãƒ³ã‚¸ãƒ³ã®åŸºç›¤æŠ€è¡“ã¨ã—ã¦é–‹ç™ºã—ã€2004å¹´ã«è«–文「MapReduce: Simplified Data Processing on Large Clustersã€ã‚’発表ã—ãŸã“ã¨ã§ã‚ˆã知られるよã†ã«ãªã‚Šã¾ã—ãŸã€‚ ãã®ã‚°ãƒ¼ã‚°ãƒ«ãŒMapReduceã®ç‰¹è¨±ã‚’å–å¾—ã—ãŸã“ã¨ãŒã€ãƒ–ãƒã‚°ã€ŒWataru's Blogã€ã®ã‚¨ãƒ³ãƒˆãƒªã€Œ GoogleãŒMapReduce特許をå–得。Googleã¯ç”¨é€”ã«ã¤ã„ã¦ã‚³ãƒ¡ãƒ³ãƒˆã›ãšã€ã§ä¼ãˆã‚‰ã‚Œã¦ã„ã¾ã™ã€‚ グーグルã®ç‰¹è¨±å–å¾—ã¯æ¥ç•Œã«ã©ã®ã‚ˆã†ãªå½±éŸ¿ã‚’与ãˆã‚‹ã®ã‹ã€‚ã“ã®ã‚¨ãƒ³ãƒˆãƒªã‚’起点ã«ã€ç¾æ™‚点ã§ã®æƒ…å ±ã‚„å ±é“ã‚’ã¾ã¨ã‚ã¾ã—ãŸã€‚ 特許å–å¾—ã¯é˜²è¡›ç›®çš„ã ã¨ã®è¦³æ¸¬ 米国特許商標åºï¼ˆUSPTO）ã®Webサイトã§ã¯ã€è©²å½“ã™ã‚‹ã‚°ãƒ¼ã‚°ãƒ«ã®ç‰¹è¨±ã€ŒSystem and method for efficient large
United States Patent: 7650331
Barroso, L.A., et al., "Web Search for a Planet: The Google Cluster Architecture," IEEE Micro, 23(2):22-28, Apr. 2003. cited by other . Ghemawat, S., et al., "The Google File System," 19th Symposium on Operating Systems Principles, pp. 29-43, Lake George, New York, 2003. cited by other . Rabin, M.O., "Efficient Dispersal of Information for Security, Load Balancing and Fault Tolerance," Journal of
MapReduceã®Java実装Apache Hadoopを使ã£ã¦ã¿ãŸ (1/3) - @IT
MapReduceã®Java実装Apache Hadoopを使ã£ã¦ã¿ãŸï¼šã„ã¾å†æ³¨ç›®ã®åˆ†æ•£å‡¦ç†æŠ€è¡“（後編）（1/3 ページ） 最近注目を浴ã³ã¦ã„る分散処ç†æŠ€è¡“「MapReduceã€ã®åˆ©ç‚¹ã‚’サンプルã‹ã‚‰ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ レベルã§ç†è§£ã—ã€æ˜”ã‹ã‚‰ã‚ã‚‹Java関連ã®åˆ†æ•£å‡¦ç†æŠ€è¡“を見直ã™ç‰¹é›†ä¼ç”»ï¼ˆç·¨é›†éƒ¨ï¼‰ Apache Hadoopプãƒã‚¸ã‚§ã‚¯ãƒˆã¨ã¯ä½•ã‹ï¼Ÿ 本特集ã§ã¯ã€ã„ã¾å†æ³¨ç›®ã®åˆ†æ•£å‡¦ç†æŠ€è¡“ã«ã¤ã„ã¦ã„ã‚ã„ã‚ã¨ç´¹ä»‹ã—ã¦ãã¾ã—ãŸã€‚å‰ç·¨ã®ã€ŒGoogleã®MapReduceアルゴリズムをJavaã§ç†è§£ã™ã‚‹ã€ã§ã¯ã€åˆ†æ•£å‡¦ç†æŠ€è¡“ã§æœ€è¿‘注目を浴ã³ã¦ã„ã‚‹ã‚‚ã®ã¨ã—ã¦ã€ã‚°ãƒ¼ã‚°ãƒ«ã®MapReduceアルゴリズムを紹介ã—ã€ä¸ç·¨ã®ã€Œã‚¤ãƒã‚¤ãƒãªåˆ†æ•£å‡¦ç†æŠ€è¡“ã¨ã‚¤ãƒžãƒ‰ã‚ã®Webサービスã€ã§ã¯ã€MapReduceã«è‡³ã‚‹ã¾ã§ã®ã•ã¾ã–ã¾ãªåˆ†æ•£å‡¦ç†æŠ€è¡“ã‚„Webサービスã«ã¤ã„ã¦ç´¹ä»‹ã—ã¾ã—ãŸã€‚ ãã®MapReduceアルゴリズムをJavaã§å®Ÿè£…ã—ãŸã‚‚
Google Research Publication: MapReduce: Simplified Data Processing on Large Clusters
MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with t
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