mapreduce algorithm in hadoop

Hadoop MapReduce:MapReduce reads the data from disk every time it executes, and then puts the data on the disk after the calculation is complete.Spark Map Reduce:RDD is everything for dev:Basic Concepts:Graph RDD:Spark Runtime:ScheduleDepency Type:Scheduler Optimizations:Event Flow:Submit Job:New Job Instance:Job in Detail:Executor.launchtask:Standalone:Work Flow:Standalone Detail:Driver Application to Clustor:Worker Exception:Executor Exception:Maste

that corresponds to the IP of your system configurationConfigure Mapred-site.xmlSo the configuration is complete.Open the virtual machine, turn on the yarn service, enter JPS to see if there are two parts of ResourceManager NodeManager. There is a successful configuration.Running WordCount algorithm under virtual machineEnter the wordcount algorithm in hadoop-->

;import Org.apache.hadoop.conf.configuration;import Org.apache.hadoop.filecache.distributedcache;import Org.apache.hadoop.fs.filesystem;import Org.apache.hadoop.fs.path;import Org.apache.hadoop.io.longwritable;import Org.apache.hadoop.io.text;import Org.apache.hadoop.io.writable;import Org.apache.hadoop.mapreduce.job;import Org.apache.hadoop.mapreduce.Mapper; Import Org.apache.hadoop.mapreduce.reducer;import Org.apache.hadoop.mapreduce.lib.input.fileinputformat;import Org.apache.hadoop.mapreduce

mapreduce Common Data Mining algorithm set collection 1. Map/reduce way to realize matrix multiplication Http://www.norstad.org/matrix-multiply/index.html 2. Map/reduce way to realize PageRank algorithm http://blog.ring.idv.tw/comment.ser?i=369 Http://code.google.com/p/map-reduce-assignment/source/browse/trunk/src/pagerank/?r=6 3. Map/reduce Way to realize TF/

Description: Reference mahout FP algorithm related source code.The algorithm project is able to download the confidence level in the FP Association rules: (Just a standalone version of the implementation, and no MapReduce code)Using the FP association rule algorithm to calculate confidence is based on the following ide

Description: Refer to mahout FP algorithm related source code.Algorithmic engineering can be downloaded with the confidence level of the FP Association rules: (Just a standalone version of the implementation, and no MapReduce code)Using the FP association rule algorithm to calculate confidence is based on the following ideas:1. First use the original FP Tree Asso

is this. 1. Map Stage Each row of the map operation, the 1/k,k of the current page's probability value for all outgoing links is the number of links to the current page, such as the first line of output 2. Reduce phase The reduce operation collects the same value as the page ID, accumulates and calculates by weight, pj=a* (p1+p2+ ... PM) + (1-a) *1/n, where M is the number of pages J that points to page J, n all pages. The idea is so simple, but in practice, how to know the current line of the

Hadoop Ecosystem technology Introduction to speed of light (shortest path algorithm Mr Implementation, Mr Two ordering, PageRank, social friend referral algorithm)Share the network disk download--https://pan.baidu.com/s/1i5mzhip password: vv4xThis course will have a better explanation from the basic environment building to the deeper knowledge learning. Help lear

/ 2.2 Test phase Load the data from the training phase into memory, calculate the probability of the document in each category, and find the category with the greatest probability. Three, Mr Analysis Test data: Sogou Lab Http://www.sogou.com/labs/resources.html?v=1 The first step here is to turn all the documents into the desired text format, where one line represents a piece of news. Training set: 75,000 news; test set: 5,000 news

data that defines a particular format. Here is the data I used to test, how to store it(Note: For custom simulation data, when the PR initial value of the selection, all the pages are "equal", will not say that their own pages and Google's popular web page there is a lot of difference, but according to a certain rule after a certain calculation of PR is not the same, such as many other pages may be linked to Google, Its PR will naturally be higher than yours. So the initial value of the selecti

, select the nearest point from the source point,To update other points in the next iteration. If the result_ array is empty, exit the iteration.Description: The point nearest to the source point is divided into two stages, first in the reduce phase to find the most recent, and finally in the local nearest result set to find the most recent point in the global. Copyright NOTICE: This article for Bo Master original article, without Bo Master permission not reproduced.

users and the number of movies and the number of users who rated the film valnumratings=ratings.count () valnumusers=ratings.map (_._2.user). Distinct (). Count () valnummovies=ratings.map (_._2.product). Distinct (). Count () println ("got" +numRatings+ "ratingsfrom" + numusers+ "users" +numMovies+ "movies") //the sample scoring table with a key value divided into 3 parts, respectively, for training (60%, and adding user ratings), check (20%),and test (20%) //This data is applied multip

Case SIX: Map direct output aloneNever used this map to output the mode alone, even if the output of some simple I will pass the reduce output, but found that the map output is a bit different from what I expected, I always thought that the shuffle process will be at the end of the map, reduce the beginning of the There will be a merger, but shuffle only do the division, sorting, and then directly listed out, this is a rise posture, before the merger of understanding, the return is a bit of a pr

compression of common data compression algorithmsThere are two main advantages of file compression, one is to reduce the space for storing files, and the other is to speed up data transmission. In the context of Hadoop big data, these two points are especially important, so I'm going to look at the file compression in Hadoop. There are many compression formats supported in

, rainfall, etc.), you should select the multi-reduce mode. The map phase is responsible for collating the input data, and the reduce phase is responsible for implementing the core algorithm of the index product. Specific calculation processes such as:2) Product production algorithm with high complexityfor the high complexity of remote sensing product production algorit