The architecture of HDFS adopts the masterslave mode. an HDFS cluster consists of one Namenode and multiple Datanode. In an HDFS cluster, there is only one Namenode node. As the central server of the HDFS cluster, Namenode is mainly responsible for: 1. Managing the Namespace of the file system in the
What is 1.HDFS?The Hadoop Distributed File System (HDFS) is designed to be suitable for distributed file systems running on general-purpose hardware (commodity hardware). It has a lot in common with existing Distributed file systems.Basic Concepts in 2.HDFS(1) blocks (block)"Block" is a fixed-size storage unit, HDFS fi
User identityIn 1.0.4 This version of Hadoop, the client user identity is given through the host operating system. For Unix-like systems,
User name equals ' WhoAmI ';
The list of groups equals ' bash-c groups '.
In the future there will be additional ways to determine user identities (such as Kerberos, LDAP, etc.). It is unrealistic to expect to use the first approach mentioned above to prevent a user from impersonating another user. This user identification mechanism, combin
Enable backup of files on HDFs via snapshotAPI address please see http://archive.cloudera.com/cdh5/cdh/5/hadoop-2.5.0-cdh5.2.0/hadoop-project-dist/hadoop-hdfs/HdfsSnapshots.html==========================================================================================1. Allow snapshot creationFirst, execute the command below the folder where you want to make the backup, allowing the folder to create a snapsh
core of Hadoop is HDFs and MapReduce, and both are theoretical foundations, not specific, high-level applications, and Hadoop has a number of classic sub-projects, such as HBase, Hive, which are developed based on HDFs and MapReduce. To understand Hadoop, you have to know what HDFs and MapReduce are.
Hdfs
It is finally here: you can configure the Open Source log-aggregator, scribe, to log data directly into the hadoop distributed file system.
Compile Web 2.0 companies have to deploy a bunch of costly filers to capture weblogs being generated by their application. currently, there is no option other than a costly filer because the write-rate for this stream is huge. the hadoop-scribe integration allows this write-load to be distributed among a bunch of commodity machines, thus cing the total cost
This article uses the hadoop Source Code. For details about how to import the hadoop source code to eclipse, refer to the first phase.
I. background of HDFS
As the amount of data increases, the data cannot be stored within the jurisdiction of an operating system, so it is allocated to more disks managed by the operating system, but it is not convenient to manage and maintain, A distributed file management system is urgently needed to manage files on
Hadoop HDFS clusters are prone to unbalanced disk utilization between machines, such as adding new data nodes to clusters. When HDFS is unbalanced, many problems will occur, such as Mr.ProgramThe advantages of local computing cannot be well utilized, the network bandwidth usage between machines cannot be better, and the machine disk cannot be used. It can be seen that it is very important to ensure data bal
Sqoop
Flume
Hdfs
Sqoop is used to import data from a structured data source, such as an RDBMS
Flume for moving bulk stream data to HDFs
HDFs Distributed File system for storing data using the Hadoop ecosystem
The Sqoop has a connector architecture. The connector knows how to connect to the appropriate data source
Configuration file
m103 Replace with the HDFs service address.To use the Java client to access the file on the HDFs, have to say is the configuration file Hadoop-0.20.2/conf/core-site.xml, originally I was here to eat a big loss, so I am not even hdfs, file can not be created, read.
Configuration item: Hadoop.tmp.dir represents the directory locati
Continue the previous chapter to organize the HDFs related configuration items
Name
Value
Description
Dfs.default.chunk.view.size
32768
The content display size for each file in the HTTP access page of Namenode, usually without setting.
Dfs.datanode.du.reserved
1073741824
The amount of space reserved for each disk needs to be set up, mainly for non-HDFS
Tags: 3.0 end TCA Second Direct too tool OTA run1. Distributing HDFs Compressed Files (-cachearchive)Requirement: WordCount (only the specified word "The,and,had ..." is counted), but the file is stored in a compressed file on HDFs, there may be multiple files in the compressed file, distributed through-cachearchive;-cacheArchive hdfs://host:port/path/to/file.tar
A brief introduction to controlling the HDFs file system with JavaFirst, note the Namenode access rights, modify the Hdfs-site.xml file or modify the file directory permissionsThis time using modify Hdfs-site.xml for testing, add the following content in the configuration node Property > name >dfs.permissions.enabledname> value >falsevalue>
HDFs block of data
Disk data block is the smallest unit of data read/write for disk, typically 512 bytes,
There are also data blocks in the HDFs, and the default is 64MB. So the large files on the HDFs are divided into many chunk. Files that are small (less than 64MB) on HDFs will not occupy the entire block of space
Shell Command implementation:(1) Upload any text file to HDFs, if the specified file already exists in HDFs, the user specifies whether to append to the end of the original file or overwrite the original file;(2) Download the specified file from HDFS and automatically rename the downloaded file if the local file has the same name as the file to be downloaded;(3)
In-depth analysis of HDFSGuideHadoop Distributed File System (HDFS) is designed as a distributed file system suitable for running on a common hardware (commodity hardware. It has a lot in common with the existing distributed file system. But at the same time, it is quite different from other distributed file systems. HDFS is a highly fault tolerant system and is suitable for deployment on cheap machines.I.
From: http://www.csdn.net/article/2013-03-25/2814634-data-de-duplication-tactics-with-hdfs
Abstract:With the surge in data volume collected, de-duplication has undoubtedly become one of the challenges faced by many big data players. Deduplication has significant advantages in reducing storage and network bandwidth, and is helpful for scalability. In the storage architecture, common methods for deleting duplicate data include hash, binary comparison,
Original link:textfile use of local (or HDFs) files and Sparkcontext instances loaded in SparkThe default is to read the file from HDFs, or you can specify Sc.textfile ("path"). Precede the path with hdfs://to read the local file read Sc.textfile ("path") from the HDFs file system. Precede the path with file:// Reads f
How to use a PDI job to move a file into HDFS.PrerequisitesIn order to follow along with this how-to guide you'll need the following:
Hadoop
Pentaho Data Integration
Sample FilesThe sample data file needed is:
File Name
Content
Weblogs_rebuild.txt.zip
unparsed, raw weblog data
Step-by-
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