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Sloan Ahrens is a co-founder of Qbox and is currently a freelance data consultant. In this series of guest posts, Sloan will be demonstrating how to set up a large scale machine learning infrastructure using Apache Spark and Elasticsearch. This is part 2 of that series. Part 1: Building an Elasticsearch Index with Python on an Ubuntu is here.  -Mark Brandon In this post we're going to continue se
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I've been working with Apache Spark quite a bit lately in an effort to bring it into the fold as a viable tool for solving some of the data-intensive problems encountered in supercomputing. Â I've already added support for provisioning Spark clusters to a branch of the myHadoop framework I maintain so that Slurm, Torque, and SGE users can begin playing with it, and as a result of these efforts, I'v
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âLearning Sparkâèªæ¸ä¼#1 ã«åå ãã¾ããã ä»å㯠Apache Spark ã¤ã³ã¹ãã¼ã«ãã MLlib ã® Statistics, LinearRegressionWithSGD ã使ã£ã¦ã¿ãã¾ã§ã®ã¡ã¢ã§ãã Apache Spark ã¤ã³ã¹ãã¼ã« ç°å¢ã¯ OSX 10.10.2 ã§ãã $ curl -O https://www.apache.org/dyn/closer.cgi/spark/spark-1.2.1/spark-1.2.1-bin-hadoop2.4.tgz $ tar xzf spark-1.2.1-bin-hadoop2.4.tgz $ ln -s ~/path/to/your/spark-1.2.1-bin-hadoop2.4 /usr/local/share/spark $ PATH=/usr/local/share/spark/bin:$P
Spark 1.3.0ããªãªã¼ã¹ããããããã§ãã Spark Release 1.3.0 | Apache Spark ã§ãããããããSpark使ã£ããã¨ãªãã¦ãããããã¾ãããã¨ããããã¤ã³ã¹ãã¼ã«ãããã¯ãã¦ã¿ãããã¨æã£ã¦ãã£ãã¨ãã®ã¡ã¢ã â»ãããã試ãã¦åããã®ãã¾ã¨ãã¦ãã ããªã®ã§ãå¿ è¦ãªæé ã足ãã¦ãªãã£ãããé¢ä¿ãªãæé ãå ¥ã£ã¦ãããã§ããããã¾ãç解ã§ãã¦ã¾ãããã Hadoopãã¤ã³ã¹ãã¼ã«ãã åèï¼Apache Hadoop 2.6.0 - Hadoop MapReduce Next Generation 2.6.0 - Setting up a Single Node Cluster. ä½ã¯ã¨ããããã¾ãã¯Hadoopãã¤ã³ã¹ãã¼ã«ãã¦single-nodeã§åããã¾ãããã®è¨äºãæ¸ãæç¹ã§ã®ææ°ãã¼ã¸ã§ã³ã¯2.6.0ã§ããã ã¨ããããJavaãå ¥ãã¾ãã
IT Leaders ããã ï¼ ãã¯ããã¸ã¼ä¸è¦§ ï¼ ããã°ãã¼ã¿ ï¼ æ²³å潤ã®ITã¹ããªã¼ã ï¼ ãã¹ãHadoopã¨å¼ã°ãããApache Sparkãã«ãã¬ã¼ã¯ã®å ãï¼ç¬¬49å ããã°ãã¼ã¿ ããã°ãã¼ã¿è¨äºä¸è¦§ã¸ [æ²³å潤ã®ITã¹ããªã¼ã ] ãã¹ãHadoopã¨å¼ã°ãããApache Sparkãã«ãã¬ã¼ã¯ã®å ãï¼ç¬¬49å 2015å¹´7æ8æ¥(æ°´)æ²³å 潤ï¼IT Leadersç·¨éé¨ï¼ ãªã¹ã ããã°ãã¼ã¿ãæ±ãããã®åºç¤ç°å¢ã¨ãã¦çã£å ã«ååãæããã®ãããåããApache Hadoop/MapReduceããä¸æ¹ã§ãæ°å¹´åããå é²ä¼æ¥ï¼ã¨ã³ã¸ãã¢ã®éã§âãã¹ãHadoopâã¨å¼ã°ãã¦ããæè¡ãããã¾ããUCãã¼ã¯ã¬ã¼ã»AMPLabçºã®ãApache Sparkãã§ããå æãIBMããä»å¾10å¹´éã§æãéè¦ãªãªã¼ãã³ã½ã¼ã¹ããã¸ã§ã¯ããã¨ä½ç½®ã¥ãã¦Sparkã¸ã®æ³¨åã宣è¨ãã
We are "HOXO-M" anonymous data analysis and R user group in Japan!!! What is inconvenience of for loops in R? It is that results you get will be gone away. So we have created a package to store the results automatically. To do it, you only need to cast one line spell magic_for(). In this text, we tell you about how to use the magic. 1. Overview for() is one of the most popular functions in R. As y
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