oozie hadoop

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

drought index product, different products such as the surface reflectivity, surface temperature, and rainfall need to be used ), select the multi-Reduce mode. The Map stage is responsible for organizing input data, and the Reduce stage is responsible for implementing the core algorithms of the index product. The specific computing process is as follows: 2) product production algorithms with high complexity For the production algorithms of highly complex remote sensing products, a MapReduce

first, the use of Sqoop data extraction1. Sqoop IntroductionSqoop is a tool for efficiently transferring large volumes of data between Hadoop and structured data storage, such as relational databases. It was successfully hatched in March 2012 and is now the top project of Apache. Sqoop has SQOOP1 and Sqoop2 two generations, and the final stable version of SQOOP1 is 1.4.6,SQOOP2 the last version is 1.99.6. It is important to note that 1.99.6 is not com

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 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 　　　

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 ++ 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?#

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

, 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

1 Hadoop configurationcaveats: Turn off all firewalls server ip system master centos 6.0 X64 slave1 10.0.0.11 Centos 6.0 X64 slave2 10.0.0.12 centos 6.0 X64 Hadoop version: hadoop-0.20.2.tar.gz1.1 in master: (Operations

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

Overview Sqoop is a top-level Apache project used to transmit data in hadoop and relational databases. Through sqoop, we can easily import data from a relational database to HDFS, or export data from HDFS to a relational database.Sqoop architecture: the sqoop architecture is very simple. It integrates hive, hbase, and oozie to transmit data through map-reduce tasks, so as to provide concurrency features and

the RM with several HA-related options and switches the Active/standby mode. The HA command takes the RM service ID set by the Yarn.resourcemanager.ha.rm-ids property as the parameter.$ yarn rmadmin-getservicestate rm1 Active $ yarn rmadmin-getservicestate RM2 StandbyIf automatic recovery is enabled, then you can switch commands without having to manually.$ yarn Rmadmin-transitiontostandby rm1 Automatic failover is enabled for [email protected] refusing to manually manage HA State, since it cou

-generated Method StubFile docdirectory=NewFile (Docdirectorypath); if(!docdirectory.isdirectory ()) {System.out. println ("Provide an absolute path of a directory that contains the documents to be added to the sequence file"); return; } /** Sequencefile.writer sequencefilewriter = * Sequencefile.createwriter (FS, Conf, new Path (Sequencefil Epath), * text.class, Byteswritable.class); */org.apache.hadoop.io.SequenceFile.Writer.Option FilePath=sequencefile.writer. File (NewPath (Se

insideLet's modify the hostTwo comments out of the front.6. Configure the Yum source6.1 Copying filesDelete the repo file that comes with the system in the/ETC/YUM.REPOS.D directory firstWill: Create a new file: Cloudera-manager.repoTouch Cloudera-manager.repoThe contents of the file are:BaseURL back is the folder inside your var/www/html.baseurl=http://Correct the second time you do itThird Amendment[Cloudera-manager]Name=cloudera ManagerBaseURL = Http://192.168.42.99/cdh/cm5.3/packageGpgcheck

.el6.noarch.rpm/download/# Createrepo.When installing Createrepo here is unsuccessful, we put the front in Yum.repo. Delete something to restoreUseyum-y Installcreaterepo Installation TestFailedAnd then we're on the DVD. It says three copies of the installed files to the virtual machine.Install deltarpm-3.5-0.5.20090913git.el6.x86_64.rpm FirstError:Download the appropriate rpmhttp://pkgs.org/centos-7/centos-x86_64/zlib-1.2.7-13.el7.i686.rpm/download/Http://pkgs.org/centos-7/centos-x86_64/glibc-2

I was fortunate enough to take the MOOC college Hadoop experience class at the academy. This is the little Elephant College hadoop2. X Overview Notes for chapter eighthThe main introduction is HBase, a distributed database application case.Case Overview:1) Time series database (OPENTSDB) Use HBase to store time series data, every moment is resolved, the database is open source 2) hbase Crawler Scheduler Library Vertical Search Crawler Mass crawler (wh

Hadoop is a project under Apache. It consists of HDFS, mapreduce, hbase, hive, Zookeeper, and other Members. HDFS and mapreduce are two of the most basic and important members. HDFS is an open-source version of Google gfs. It is a highly fault-tolerant distributed file system that provides high-throughput data access and is suitable for storing massive (Pb-level) data) (usually more than 64 MB), the principle is as follows: The Master/Slave struct

;padding:0px;border:0px;background-image: none; "/> 1. The principles have been described in the diagram, not another large paragraph of text explained, 2. In the above two diagrams, except for the "actual business object class", all belong to the structure or frame part; 3. If you use OO thinking to review the above two charts, you will be complaining about the bad design, here just to describe the work of the distributed system as simple as possible, you can use the policy mode to ada

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