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
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
Hadoop FS: Use the widest range of surfaces to manipulate any file system.Hadoop DFS and HDFs DFS: can only operate on HDFs file system-related (including operations with local FS), which is already deprecated, typically using the latter.The following reference is from StackOverflowFollowing is the three commands which appears same but has minute differences
Hadoop fs {args}
The debug run in Eclipse and "run on Hadoop" are only run on a single machine by default, because in order to let the program distributed running in the cluster also undergoes the process of uploading the class file, distributing it to each node, etc.A simple "run on Hadoop" just launches the local Hadoop class library to run your program,No job information is vi
The previous installation process to be supplemented, after the installation complete Hadoop installation, began to execute the relevant commands, let Hadoop run up Use the command to start all services: [Email protected]:/usr/local/gz/hadoop-2.4. 1$./sbin/start-all. SHOf course there will be a lot of startup files under directory
}
Kerberos principal name for the secondary NameNode.
Maybe you will directly use dfs. secondary. namenode. kerberos. the name principal gets the value, and the obtained value is hdfs/_ HOST $ {local. realm}, but obviously this is not the value we need, because there is $ {local. realm}, which actually represents another set value,
Ubuntu System (I use the version number is 140.4)The Ubuntu system is a desktop-based Linux operating system, and Ubuntu is built on the Debian distribution and GNOME desktop environments. The goal of Ubuntu is to provide an up-to-date, yet fairly stable, operating system that is primarily built with free software for the general user, free of charge and with community and professional support.As a Hadoop big data development test environment, it is r
Meet hadoop
1.1 data! (Data)
Most of the data is locked up in the largest Web properties (like search engines), or scientific or financial institutions, isn' t it? Does the advent of "big data," as it is beingCalled, affect smaller organizations or individuals?
As ordinary people do not benefit from the vast amount of data, data is stored in the network or stored by a large number of research institutions, so big data mining is also applied.
From a pe
1. Preface
Hadoop RPC is mainly implemented through the dynamic proxy and reflection (reflect) of Java,Source codeUnder org. Apache. hadoop. IPC, there are the following main classes:
Client: the client of the RPC service
RPC: implements a simple RPC model.
Server: abstract class of the server
Rpc. SERVER: specific server class
Versionedprotocol: All classes that use the RPC service mu
I perform the following steps:1. dynamically increase datanode nodes and Tasktracker nodesin host226 as an exampleExecute on host226:Specify host NameVi/etc/hostnameSpecify host name-to-IP-address mappingsVi/etc/hosts(the hosts are the Datanode and TRAC)Adding users and GroupsAddGroup HadoopAddUser--ingroup Hadoop HadoopChange temporary directory permissionschmod 777/tmpExecute on HOST2:VI conf/slavesIncrease host226Ssh-copy-id-i. ssh/id_rsa.pub [Emai
Hello everyone, I am Stefan, starting today to bring you a detailed Hadoop learning tutorial, you can follow my tutorial step by step into the development of cloud computing, OK, nonsense, we started the first: Hadoop environment.
The beginning of everything is difficult, this is not a blow. Many people in the initial environment to build up the problem, and everyone's platform and there are differences, it
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
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The most comprehensive history of hadoop, hadoop
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