hadoop mapreduce architecture

Configuring MapReduceconfiguration>configuration>Plus this.configuration> property > name>Mapreduce.framework.namename> value>Yarnvalue> Property >configuration>And then configure it inside the yarn-site.xml.configuration> -- property > name>Yarn.resourcemanager.hostnamename> value>Hadoop1value> Property > property > name>Yarn.nodemanager.aux-servicesname> value>Mapreduce_shufflevalue> Property > property > name>Yarn.n

, and end users extract the statement result file via the Hadoop client ( Hadoop itself is also a distributed file system with the usual file access capabilities.3. Clearing: Import the UnionPay file into HDFs, then the POSP transaction data previously imported from the relational database for MapReduce calculation (i.e. reconciliation operations), and then conne

(Firstpartitioner.class);//partition functionJob.setsortcomparatorclass (Keycomparator.class);//This course does not have custom sortcomparator, but instead uses Intpair's own sortJob.setgroupingcomparatorclass (Groupingcomparator.class);//Group functionJob.setmapoutputkeyclass (Intpair.class);Job.setmapoutputvalueclass (Intwritable.class);Job.setoutputkeyclass (Text.class);Job.setoutputvalueclass (Intwritable.class);Job.setinputformatclass (Textinputformat.class);Job.setoutputformatclass (Text

Tags: hadoop Business Logic In fact, it is very simple to input two files, one as the basic data (student information file) and the other is the score information file.Student Information File: stores student data, including student ID and Student name Score data: stores scores of students, including student IDs, subjects, and scores. We will use M/R to associate data based on student IDs. The final result is student name, subject, and score. Analog d

processing classesJob.setmapperclass (Datamapper.class); Job.setreducerclass (datareduce.class); //Setting the output key-value data typeJob.setoutputkeyclass (Text.class); Job.setoutputvalueclass (Text.class); //submit the job and wait for it to completeSystem.exit (Job.waitforcompletion (true) ? 0:1); } }Add one point: When a file is sliced, it starts a mapper process according to the default 64M data block principle.Example: For example, Data.log has 20M, will start a mapper process, Data

(args[1]));//Output path Job.setmapperclass (Scoremapper.class);//MapperJob.setreducerclass (Scorereducer.class);//Reducer Job.setmapoutputkeyclass (Text.class);//Mapper key Output typeJob.setmapoutputvalueclass (Scorewritable.class);//Mapper value Output type Job.setinputformatclass (Scoreinputformat.class);//Set Custom input formats Job.waitforcompletion (TRUE);return 0;} public static void Main (string[] args) throws Exception{string[] Args0 =// {"Hdfs://hadoopmaster:9000/score/score.txt","H

In the development of the Mr Program of Hadoop, it is often necessary to statistic some Map/reduce's running state information, which can be implemented by custom counter, which is done by the Code runtime check instead of the configuration information.1. Create a Counter enumeration class of your own.enum Process_counter { bad_records, bad_groups;}2, in need of statistics, such as map or reduce phase of the following operations.// added 1 // 1

longwritable for long. But there are some differences between text and string, which is a UTF-8 format of writable, and string in Java is a Unicode character. So the direct use of the value.tostring () method, the default character is UTF-8 encoded, so the original GBK encoded data using the text read into the direct use of the method will become garbled.The correct method is to convert the value of the input text type to a byte array (value.getbytes ()), using the string constructor string (by

= Mypath.getfilesystem (conf);if (Hdfs.isdirectory (MyPath)){Hdfs.delete (MyPath, true);}@SuppressWarnings ("deprecation")Job Job = new Job (conf, "gender");//Create a new taskJob.setjarbyclass (Gender.class);//Main classJob.setmapperclass (pcmapper.class);//mapperJob.setreducerclass (pcreducer.class);//reducerJob.setpartitionerclass (Myhashpartitioner.class);Job.setpartitionerclass (Pcpartitioner.class);//Set Partitioner classJob.setnumreducetasks (3);//reduce number set to 3Job.setmapoutputke

); } }}Datasort class PackageCom.cn.sort;Importorg.apache.hadoop.conf.Configuration;ImportOrg.apache.hadoop.fs.Path;Importorg.apache.hadoop.io.IntWritable;ImportOrg.apache.hadoop.mapreduce.Job;ImportOrg.apache.hadoop.mapreduce.lib.input.FileInputFormat;ImportOrg.apache.hadoop.mapreduce.lib.output.FileOutputFormat;ImportOrg.apache.hadoop.util.GenericOptionsParser;/*** Data Sorting *@authorRoot **/ Public classDatasort { Public Static voidMain (string[] args)throwsException {Configuration conf=

The 1.Text packet was wrongly guided.The import Com.sun.jersey.core.impl.provider.entity.XMLJAXBElementProvider.Text;Change to import Org.apache.hadoop.io.Text;.2. The local compilation environment and the Java version in the production environment do not match. It is possible that the JDK does not match or the JRE does not match. It doesn't matter if they match.3.map and reduce are overloaded with mapper and reducer classes respectively. Cannot be a method of your own definitionThe

Hadoop Reading Notes series article:http://blog.csdn.net/caicongyang/article/category/21668551.partition GroupingPartition is the specified grouping algorithm, and the number of tasks to set reduce by setnumreducetasks2. Code Kpiapp.avaPackage Cmd;import Java.io.datainput;import java.io.dataoutput;import java.io.ioexception;import Java.net.URI; Import Org.apache.hadoop.conf.configuration;import Org.apache.hadoop.conf.configured;import Org.apache.hadoo

file size does not exceed 1.1 times times the Shard size, it will be divided into a shard, avoid opening two map, one of the running data is too small, wasting resources.Summary, the Shard process is about, first traverse the target file, filter some non-conforming files, and then add to the list, and then follow the file name to slice the Shard (the size of the previous calculation of the size of the formula, the end of a file may be merged, in fact, often write network programs know), and the

Hadoop Reading Notes series article:http://blog.csdn.net/caicongyang/article/category/21668551. Description:The two columns of data given are sorted first in ascending order of the first column, and the second column in ascending order when the first column is the sameData format:3332312221112. Code Sortapp.javaPackage Sort;import Java.io.datainput;import java.io.dataoutput;import java.io.ioexception;import Java.net.URI; Import Org.apache.hadoop.conf.

Transferred from http://www.ptbird.cn/mapreduce-tempreture.html I. Description of requirements 1, data file description There are some data files stored in the HDFs in the form of text, as shown in the following example: In the middle of the date and time is a space, as a whole, indicating the detection of site monitoring time, followed by the detection of temperature, the middle through the tab \ t separated. 2, the demand calculation in 1949-1955 y

deserialization.Function call layer: locate the function to be called and execute the function. Hadoop RPC uses a java reflection mechanism and a dynamic proxy to call functions.Network Transmission Layer: message transmission between the Client and the Server. Hadoop RPC uses a TCP/IP-based Socket mechanism.Server Processing Framework: network I/O model. Describes how the client interacts with the server.

then introduces the MapReduce computing framework.HDFS ArchitectureHDFS is a highly fault-tolerant distributed file system that is suitable for deployment on inexpensive machines. HDFS provides high-throughput data access and is ideal for applications on large-scale datasets. The architecture of HDFS, in general, employs the Master/slave architecture, consisting

Hadoop Reading Notes series article:http://blog.csdn.net/caicongyang/article/category/21668551. Description:Finds the maximum value from the given file2. Code:Topapp.javaPackage Suanfa;import Java.io.ioexception;import Java.net.uri;import org.apache.hadoop.conf.configuration;import Org.apache.hadoop.fs.filesystem;import Org.apache.hadoop.fs.path;import Org.apache.hadoop.io.longwritable;import Org.apache.hadoop.io.nullwritable;import Org.apache.hadoop.

Step OneIf not, do not set up the HBase development environment blog, see my next blog.HBase Development Environment Building (Eclipse\myeclipse + Maven)　　Step one, need to add. As follows:In the project name, right-click,Then, write Pom.xml, here not much to repeat. SeeHBase Development Environment Building (Eclipse\myeclipse + Maven)When you are done, write the code, right.Step two some steps after the HBase development environment is built (export exported jar package or Ant mode)Here, do not

)); } } } }}Singletontablejoin class PackageCom.cn.singletonTableJoin;Importorg.apache.hadoop.conf.Configuration;ImportOrg.apache.hadoop.fs.Path;ImportOrg.apache.hadoop.io.Text;ImportOrg.apache.hadoop.mapreduce.Job;ImportOrg.apache.hadoop.mapreduce.lib.input.FileInputFormat;ImportOrg.apache.hadoop.mapreduce.lib.output.FileOutputFormat;ImportOrg.apache.hadoop.util.GenericOptionsParser;/*** Single-Table Association *@authorRoot **/ Public classSingletontablejoin { Public Stati