hadoop fundamentals

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Hadoop 2.5.2 Source Code compilation

The compilation process is very long, the mistakes are endless, need patience and patience!! 1. Preparation of the environment and software Operating system: Centos6.4 64-bit JDK:JDK-7U80-LINUX-X64.RPM, do not use 1.8 Maven:apache-maven-3.3.3-bin.tar.gz protobuf:protobuf-2.5.0.tar.gz Note: Google's products, preferably in advance Baidu prepared this document Hadoop src:hadoop-2.5

Hadoop exception and handling Summary-01 (pony-original), hadoop-01

Hadoop exception and handling Summary-01 (pony-original), hadoop-01 Test environment: Local: MyEclipse Cluster: Vmware 11 + 6 Centos 6.5 Hadoop version: 2.4.0 (configured as automatic HA) Test Background: After four normal tests of the MapReduce Program (hereinafter referred to as MapReduce), a new MR program is executed, and the console information of MyEclipse

Hadoop learning 2: hadoop Learning

Hadoop learning 2: hadoop LearningAfter building a pseudo-distributed system:Introduction to pseudo distributed installation: http://www.powerxing.com/install-hadoop/ Exercise 1 compile a Java program to implement the followingFunction: 1. In HDFSUpload files 2. From HDFSDownload filesTo local 3.Show file directory 4.Move files 5.Create folder 6.Remove folder    

Hadoop "Unable to load Native-hadoop library for your platform" error on CentOS

everything is OK on the Namenode node, and there is no prompt for this information, but the following message appears on Datanode:15/01/14 16:42:09 WARN util. nativecodeloader:unable to load Native-hadoop library for your platform ... using Builtin-java classes where applicableafter checking the original is Datanode sub-node /home/hadoop/hadoop2.2/lib directory does not have native folder, and Namenode abov

Hadoop ++: Improves the local performance of hadoop

Hadoop ++ is a non-invasive Optimization of hadoop map reduce. It improves query and connection performance by customizing functions such as split in hadoop framework. The project is hosted by Professor Jens dittrich at the University of Saarland, Germany. The project homepage is http://infosys.uni-saarland.de/hadoop?#

Introduction to the capacity scheduler of hadoop 0.23 (hadoop mapreduce next generation-capacity schedity)

Original article: http://hadoop.apache.org/common/docs/r0.23.0/hadoop-yarn/hadoop-yarn-site/CapacityScheduler.html This document describes capacityscheduler, a pluggable hadoop scheduler that allows multiple users to securely share a large cluster, their applications can obtain the required resources within the capacity limit. Overview Capacityscheduler is design

Hadoop Learning II: Hadoop infrastructure and shell operations

, file random modification a file can have only one writer, only support append.Data form of 3.HDFSThe file is cut into a fixed-size block, the default block size is 64MB, the size of the block can be configured, if the file size is less than 64MB, it is stored separately into a block. A file storage method is divided into blocks by size, stored on different nodes, with three replicas per block by default.HDFs Data Write Process:  HDFs Data Read process:  4.MapReduce: Google's MapReduce open sou

Install and deploy Apache Hadoop 2.6.0

Install and deploy Apache Hadoop 2.6.0 Note: For this document, refer to the official documentation for the original article. 1. hardware environment There are three machines in total, all of which use the linux system. Java uses jdk1.6.0. The configuration is as follows:Hadoop1.example.com: 172.20.115.1 (NameNode)Hadoop2.example.com: 172.20.1152 (DataNode)Hadoop3.example.com: 172.115.20.3 (DataNode)Hadoop4.example.com: 172.20.115.4Correct resolution

Deploy Hadoop cluster service in CentOS

Deploy Hadoop cluster service in CentOSGuideHadoop is a Distributed System infrastructure developed by the Apache Foundation. Hadoop implements a Distributed File System (HDFS. HDFS features high fault tolerance and is designed to be deployed on low-cost hardware. It also provides high throughput to access application data, suitable for applications with large datasets. HDFS relaxed the requirements of POSI

The fundamentals of MapReduce

failure, Hadoop new version 0.23 resolves this issue. Part III: Job schedulingFIFOThe default scheduler in Hadoop, which first selects the jobs to be executed according to the priority of the job and then the time of arrivalFair SchedulerThe method of assigning resources to a task, which is intended to allow the submitted job to get the same amount of cluster shared resources over time, allowing the user t

High-availability Hadoop platform-Hadoop Scheduling for Oozie Workflow

High-availability Hadoop platform-Hadoop Scheduling for Oozie Workflow1. Overview In the "high-availability Hadoop platform-Oozie Workflow" article, I will share with you how to integrate a single plug-in such as Oozie. Today, we will show you how to use Oozie to create related workflows for running and Hadoop. You mu

Several Hadoop daemon and Hadoop daemon

Several Hadoop daemon and Hadoop daemon After Hadoop is installed, several processes will appear when jps is used. Master has: Namenode SecondaryNameNode JobTracker Slaves has Tasktracker Datanode 1.NameNode It is the master server in Hadoop, managing the file system namespace and accessing the files stored in the

Hadoop officially learns---Hadoop

resourcesMaster-Slave structureMaster node, there can be 2: ResourceManagerFrom the node, there are a number of: NodeManagerResourceManager is responsible for:Allocation and scheduling of cluster resourcesFor applications such as MapReduce, Storm, and Spark, the Applicationmaster interface must be implemented to be managed by RMNodeManager is responsible for:Management of single node resourcesVII: The architecture of MapReduceBatch computing model with disk IO dependentMaster-Slave structureMas

Hadoop----My understanding of Hadoop

Big data: Massive dataStructured data: Data that can be stored in a two-dimensional tableunstructured data: Data cannot be represented using two-dimensional logic of the data. such as word,ppt, picture Semi-structured data: a self-describing, structured and unstructured data that stores the structure with the data itself: XML, JSON, HTMLGoole paper: mapreduce:simplified Date processing on Large Clusters Map: Small data that maps big data to multiple nodes that are segmented

Hadoop Combat---Problems and workarounds for Hadoop development

First on the correct run display:Error 1: The variable is intwritable and is receiving longwritable, such as:Reason, write more parameters reporter, such as:Error 2: The array is out of bounds, such as:Cause: The Combine class is set up, such as:Error 3:nullpointerexception exception, such as:Cause: The static variable is null and can be assigned, such as:Error 4: Entering map, but unable to enter reduce, and direct map data output, and no error promptCause: The new and older version of

"Hadoop" 1, Hadoop Mountain chapter of Virtual machine under Ubuntu installation jdk1.7

1 access to Apache Hadoop websitehttp://hadoop.apache.org/2.2. Click image to downloadWe download the 2.6.0 third in the stable version of stableLinux Download , here is an error, we download should be the bottom of the second, which I did not pay attention to download the above 17m .3. Install a Linux in the virtual machineFor details see other4. Installing the Hadoop environment in Linux1. Installing the

Learn about the fundamentals of Java

JavaIs the 1995 Sun Company launched a high-level programming language, is the Internet-oriented language, the language of choice for Web applications (Android bottom, Big Data Hadoop framework written in Java, Spark in Scala, Scala written in Java), (compared to other languages) easy to learn , safe and reliable, fully object-oriented, cross-platform (operating system, completely ignore the operating system, after writing any operating system can be

Linux Fundamentals 1

descriptionSynopsis: Usage notes, including available optionsDESCRIPTION: A detailed description of the command function, which may include the meaning of each optionOptions: Explaining the meaning of each optionFiles: Related configuration file for this commandBUGS:EXAMPLES: Use CasesSee ALSO: Another referenceFlip Screen:Turn back one screen: spaceTurn One screen forward: bLine backward: EnterForward line: KFind:/keyword: BackwardsN Key: NextN Key: Previous? KEYWORD: ForwardN Key: NextN Key:

Hadoop Learning Hadoop Case Study

command to upload data to HDFs, if the log server data is large, the pressure is higher, using NFS to upload data on another server, if the log server is very large, data volume, using flume for data processing;2.2 Write a MapReduce program to clean the data in HDFs;2.3 Using hive to statistics the data after cleaning;2.4 The statistic data is exported to MySQL via Sqoop;2.5 If you need to view detailed data, you can show through HBase;3 Detailed Overview3.1 Uploading data from Linux to HDFs us

Hadoop big data basic training course: the only full HD version of the first season, hadoop Training Course

Hadoop big data basic training course: the only full HD version of the first season, hadoop Training CourseHadoop big data basic training course unique HD full version first seasonThe full version of 30 lessons was born Link: http://pan.baidu.com/share/link? Consumer id = 3751953208 uk = 3611155194 Password free shared edition http://pan.baidu.com/share/link? Consumer id = 1384103203 uk = 3611155194

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