hdfs

About HDFSThe Hadoop Distributed file system, referred to as HDFs, is a distributed filesystem. HDFs is highly fault-tolerant and can be deployed on low-cost hardware, and HDFS provides high-throughput access to application data, which is suitable for applications with large data sets. It has the following characteristics:1) suitable for storing very large files2

configuring CDH and Managing servicesTuning of HDFs before closing DatanodeRole requirements: Configurator, Cluster Administrator, full Administratorwhen a datanode is closed, Namenode ensures that each block in each Datanode is still available based on the replication factor (the replication factor) across the cluster. This process involves the block duplication of small batches between datanode. In this case, a datanode has thousands of blocks, and

Original link: http://blog.csdn.net/ashic/article/details/47068183Official Document Link: http://hadoop.apache.org/docs/r2.7.1/hadoop-project-dist/hadoop-hdfs/HdfsSnapshots.htmlOverviewThe HDFs snapshot is a read-only, point-in-time file system copy. You can take a snapshot of a subdirectory in the file system or the entire file system. Snapshots are often used as data backups to prevent user errors and dis

Hdfs-hadoop File SystemSection One: The file structure of HDFsLearning HDFs first needs to understand the file structure of HDFs, and how it updates and saves the data, to understand HDFs first to know that HDFs is mainly composed of three parts: Namenode,datanode,secondaryn

of each application client need to be collected in real time and sent to the distributed file system, for subsequent data mining and analysis. The data is collected to HDFS and a file is generated on a regular basis every day (the file prefix is the date, and the suffix is the serial number starting from 0). When the file size exceeds the specified size, A new file is automatically generated. The file prefix is the current date, And the suffix is the

Architecture The image shows that HDFS mainly contains the following functional components:Namenode: stores the metadata of a document and the directory structure of the entire file system.Datanode: stores document block information, and there is redundant backup between document blocks.The document block concept is mentioned here. Like the local file system, HDFS is also block-based storage, but the block

[Flume] uses Flume to pass the Web log to HDFs example:Create the directory where log is stored on HDFs:$ HDFs dfs-mkdir-p/test001/weblogsflumeSpecify the log input directory:$ sudo mkdir-p/flume/weblogsmiddleSettings allow log to be accessed by any user:$ sudo chmod a+w-r/flume$To set the configuration file contents:$ cat/mytraining/exercises/flume/spooldir.conf

[TOC] Hadoop HDFS Java APIMainly Java operation HDFs Some of the common code, the following direct code:Package Com.uplooking.bigdata.hdfs;import Org.apache.hadoop.conf.configuration;import org.apache.hadoop.fs.*; Import Org.apache.hadoop.fs.permission.fspermission;import Org.apache.hadoop.io.ioutils;import org.junit.After; Import Org.junit.before;import org.junit.test;import Java.io.bufferedreader;im

,logfile,logdailyfile,logrollingfile,logmail,logdb,all log4j.rootlogger=all,systemout # Output to console log4j.appender.systemout= org.apache.log4j.ConsoleAppender log4j.appender.systemout.layout= Org.apache.log4j.PatternLayout log4j.appender.systemout.layout.conversionpattern= [%-5p][%-22d{yyyy/mm/dd HH : mm:sss}][%l]%n%m%n log4j.appender.systemout.threshold= INFO log4j.appender.systemout.immediateflush= TRUE Finally, copy and paste five profiles of Hadoop into the src\main\resources d

Name Value Description DFS. Default. Chunk. View. Size 32768 The size of each file displayed on the HTTP access page of namenode usually does not need to be set. DFS. datanode. Du. Reserved 1073741824 The size of the space reserved by each disk, which must be set to be used mainly for non-HDFS files. The default value is not reserved, and the value is 0 bytes. DFS. Name. dir /Opt/data1/

first, the purpose of the experiment1. There is only one namenode for the existing Hadoop cluster, and a namenode is now being added.2. Two namenode constitute the HDFs Federation.3. Do not restart the existing cluster without affecting data access.second, the experimental environment4 CentOS Release 6.4 Virtual machines with IP address192.168.56.101 Master192.168.56.102 slave1192.168.56.103 Slave2192.168.56.104 KettleOne of the kettle is a new "clean

From:http://www.2cto.com/database/201303/198460.htmlHadoop HDFs Common CommandsHadoop common commands:Hadoop FSView all commands supported by Hadoop HDFsHadoop fs–lslisting directory and file informationHadoop FS–LSRLoop lists directories, subdirectories, and file informationHadoop fs–put Test.txt/user/sunlightcsCopy the test.txt of the local file system to the/user/sunlightcs directory of the HDFs file sys

PackageCn.itcast.bigdata.hdfs;ImportJava.net.URI;ImportJava.util.Iterator;ImportJava.util.Map.Entry;Importorg.apache.hadoop.conf.Configuration;ImportOrg.apache.hadoop.fs.FileStatus;ImportOrg.apache.hadoop.fs.FileSystem;ImportOrg.apache.hadoop.fs.LocatedFileStatus;ImportOrg.apache.hadoop.fs.Path;ImportOrg.apache.hadoop.fs.RemoteIterator;ImportOrg.junit.Before;Importorg.junit.Test;/*** * Client to operate HDFS, there is a user identity * By default, the

/jni/libswt-*3740.so ~/.swt/lib/linux/x86_64 and restart it.Eclipse under the Usr/lib/eclipsehttp://www.blogjava.net/hongjunli/archive/2007/08/15/137054.html troubleshoot viewing. class filesA typical Hadoop workflow generates data files (such as log files) elsewhere, and then copies them into HDFs, which is then processed by mapreduce, usually without directly reading an HDFs file, which is read by the Map

1. Directory Quota [xiaoqiu@s150/home/xiaoqiu/hadoop_tmp]$ Hadoop FS-LSR/ lsr:DEPRECATED:Please use ' ls-r ' instead. Drwxr-xr-x -Xiaoqiu supergroup 0 2017-12-29 15:50/user drwxr-xr-x -Xiaoqiu supergroup 0 2017-12-29 15:50/user/xiaoqiu drwxr-xr-x -xiaoqiu supergroup 0 2017-12-29 15:50/user/xiaoqiu/data drwxr-xr-x -xiaoqiu supergroup 0 2017-12-29 15:44/usr drwxr-xr-x -Xiaoqiu supergroup 0 2017-12-29 15:44/usr/xiaoqiu drwxr-xr-x -xiaoqiu sup

Preparatory work: 1, install the Hadoop; 2. Create a Helloworld.jar package, this article creates a jar package under the Linux shell: Writing Helloworld.java filespublic class HelloWorld{public static void Main (String []args) throws Exception{System.out.println ("Hello World");} } Javac Helloworld.java is compiled and gets Helloworld.classIn the catalogue CV MANIFEST.MF file:manifest-version:1.0CREATED-BY:JDK1.6.0_45 (Sun Microsystems Inc.)Main-class:helloworld Run command: Jar CVFM Hellowor

Design objectives: -(Hardware failure is normal, not accidental) automatic rapid detection to deal with hardware errors -Streaming Access data (data batch processing) -Transfer calculation is more cost-effective than moving the data itself (reducing data transfer) -Simple data consistency model (one write, multiple read file access model) -Heterogeneous Platform portability HDFS Architecture Adopt Master-slaver Mode: Namenode Central Server (Master)

Hadoop provides us with an API to access HDFs using C language , which is briefly described below:Environment:ubuntu14.04 hadoop1.0.1 jdk1.7.0_51AccessHDFsfunction is primarily defined in theHdfs.hfile, the file is located in thehadoop-1.0.1/src/c++/libhdfs/folder, and the corresponding library file is located in the hadoop-1.0.1/c++/linux-amd64-64/lib/directory.libhdfs.so, in addition to accessHDFsalso need to rely onJDKthe relatedAPI, the header f

Xshell run into the graphical interface in xmanager 1 sh spoon. SHCreate a new job1. write data into HDFs 1) kettle writes data to HDFs in LinuxDouble-click hadoop copy FilesRun this jobView data:1) kettle Write Data to HDFs in WindowsHDFs writes data to the power server in WindowsLog:2016/07/28 16:21:14-version CHECKER-OK2016/07/28 16:21:57-Data integrat

In HDFS, administrators can set certain names and space quotas for each directory. The name quota and space quota can be set separately, but from the management and implementation aspects, these two quotas are close to parallel. Namequota is a hard limit on the quantity of all files and directory names in this directory. When the quota is exceeded In HDFS, administrators can set certain names and space quot