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units1) data block size of Hadoop1.0:64M2) Hadoop2.0 database size: 128M2. In full distribution mode, at least two datanode nodes 3. Directory of Data Preservation: by Hadoop.tmp.dir parameter specifies secondary NameNode(second called node) 1. Main role: Merging logs2. Timing of consolidation: when HDFs issues checkpoints3. Log merge process: Problems with HDFs 1) Namenode si
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MapReduce LearningMAP ": The main node reads input data, divides it into small chunks that can be solved in the same way (here is a divide-and-conquer idea), and distributes these small chunks to different working nodes (Worder nodes), each working node (worder node) Loop to do the same thing, this is going to be a tree-row structure (many of the models in distributed computing are related to graph theory, PageRank is also), and each leaf node has to
completes, the JDK folder will be generated in the/opt/tools directory./jdk-6u34-linux-i586.binTo configure the JDK environment command:[Email protected]:/opt/tools# sudo gedit/etc/profileTo enter the profile file, change the file:Export java_home=/opt/tools/jdk1.6.0_34Export Jre_home= $JAVA _home/jreExport classpath= $JAVA _home/lib: $JRE _home/lib: $CLASSPATHExport path= $JAVA _home/bin: $JRE _home/bin: $PATHSave file, closeExecute the following command to make the configuration file effectiv
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Data deduplication: Data deduplication only occurs once, so the key in the reduce stage is used as the input, but there is no requirement for values-in, that is, the input key is directly used as the output key, and leave the value empty. The procedure is similar to wordcount: Tip: Input/Output path configuration. Import Java. io. ioexception; import Org. apache. hadoo
,iterableOutput_key.set (num++); Loop assignment as line numberContext.write (Output_key,key); Key for map incoming data}}public static void Main (string[] args) throws exception{Path outputpath=new path (Output_path);Configuration conf=new configuration ();Job job=job.getinstance (conf);Fileinputformat.setinputpaths (Job, Input_path);Fileoutputformat.setoutputpath (Job,outputpath);Job.setmapperclass (Mymapper.class);Job.setreducerclass (Myreduce.clas
classesJob. setmapperclass (wordcountmapper. Class );Job. setreducerclass (wordcountreducer. Class );// Set map outputJob. setmapoutputkeyclass (text. Class );Job. setoutputvalueclass (intwritable. Class );// Set reduce outputJob. setoutputkeyclass (text. Class );Job. setoutputvalueclass (intwritable. Class );// Set the input and output pathsFileinputformat. setinputpaths (job, new path (ARGs [0]);Fileoutputformat. setoutputpath (job, new path (ARGs [1]);// SubmitBoolean result = job. waitforco
The 1th chapter on Big DataThis chapter will explain why you need to learn big data, how to learn big data, how to quickly transform big data jobs, the contents of the actual combat cou
; direction 3: Big Data O M and cloud computing. If you are proficient in any direction, there will be no space in the "front (money)" way. What is the big data talent gap? Is Data Big Data
tip: see if you've counted the same time-consuming numbers many times. For example, suppose that the cost of a 1000-bag potato is expensive, but you don't need to calculate that cost 500 times before you store the cost of a 1000-bag potato in an array or other similar place, so you don't have to toss the same thing over and over. This technique, called memorization, is used in reports like yours to have a miraculous effect. Related recommendations: P
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