HDFS Architecture Guide 2.6.0This article is a translation of the text in the link belowHttp://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-hdfs/HdfsDesign.htmlBrief introductionHDFS is a distributed file system that can run on normal hardware. Compared with the existing distributed system, it has a lot of similarities. However, the difference is also very large.
Recently, a Hadoop cluster was installed, so the HA,CDH4 that configured HDFS supported the quorum-based storage and shared storage using NFS two HA scenarios, while CDH5 only supported the first scenario, the Qjm ha scenario.
About the installation deployment process for Hadoop clusters You can refer to the process of installing CDH Hadoop clusters using Yum or manually installing Hadoop clusters. Cluster Planning
I have installed a total of three no
Introduction
Prerequisites and Design Objectives
Hardware error
Streaming data access
Large data sets
A simple consistency model
"Mobile computing is more cost effective than moving data"
Portability between heterogeneous software and hardware platforms
Namenode and Datanode
File System namespace (namespace)
Data replication
Copy storage: One of the most starting steps
Copy Selection
Safe Mode
Persist
Important Navigation
Example 1: Accessing the HDFs file system using Java.net.URL
Example 2: Accessing the HDFs file system using filesystem
Example 3: Creating an HDFs Directory
Example 4: Removing the HDFs directory
Example 5: See if a file or directory exists
Example 6: Listing a file or
This paper mainly describes the principle of HDFs-architecture, replica mechanism, HDFS load balancing, rack awareness, robustness, file deletion and recovery mechanism
1: Detailed analysis of current HDFS architecture
HDFS Architecture
1, Namenode
2, Datanode
3, Sencondary Namenode
Data storage Details
Namenode dire
Catalogue
What is HDFs?
Advantages and disadvantages of HDFs
The framework of HDFs
HDFs Read and write process
HDFs command
HDFs parameters
1. What is HDFsThe
(1) Distributed File systemAs the amount of data is increasing and the scope of an operating system is not enough, it is allocated to more operating system-managed disks, but it is not easy to manage and maintain, so a system is urgently needed to manage files on multiple machines, which is distributed file management system. It is a file system that allows files to be shared across multiple hosts over a network, allowing multiple users on multiple machines to share files and storage space.And i
Hadoop Introduction: a distributed system infrastructure developed by the Apache Foundation. You can develop distributed programs without understanding the details of the distributed underlying layer. Make full use of the power of clusters for high-speed computing and storage. Hadoop implements a Distributed File System (HadoopDistributed File System), HDFS for short. HDFS features high fault tolerance and
The previous article has completed the installation of SQOOP2, this article describes sqoop2 to import data from Oracle HDFs has been imported from HDFs Oracle
The use of Sqoop is mainly divided into the following parts
Connect Server Search Connectors Create link Create job Execute job View job run information
Before using SQOOP2, you need to make the following modifications to the Hadoop configuration f
A Profile
Hadoop Distributed File system, referred to as HDFs. is part of the Apache Hadoop core project. Suitable for Distributed file systems running on common hardware. The so-called universal hardware is a relatively inexpensive machine. There are generally no special requirements. HDFS provides high-throughput data access and is ideal for applications on large-scale datasets. And
Namenode large amount of memory; Seek time exceeds read time;Concurrent write, File random modification: A file can only have one writer; only support appendIv. HDFs ArchitectureMaster Master(only one): can be used to manage HDFs namespaces, manage block mapping information, configure replica policies, handle client read and write requests NameNode : Fsimage and fsedits can be combined regularly, pushed
Common HDFS file operation commands and precautions
The HDFS file system provides a considerable number of shell operation commands, which greatly facilitates programmers and system administrators to view and modify files on HDFS. Furthermore, HDFS commands have the same name and format as Unix/Linux commands, and thus
Two classes, one HDFs file operation class, one is the WordCount word Count class, all from the Internet view. Code on:
Package mapreduce;
Import java.io.IOException;
Import java.util.ArrayList;
Import java.util.List;
Import org.apache.hadoop.conf.Configuration;
Import org.apache.hadoop.fs.BlockLocation;
Import Org.apache.hadoop.fs.FSDataInputStream;
Import Org.apache.hadoop.fs.FSDataOutputStream;
Import Org.apache.hadoop.fs.FileStatus;
Import Org.ap
Transferred from: http://www.nosqlnotes.net/archives/119
A lot of distributed file systems, including Gfs,hdfs, Taobao Open source tfs,tencent for album Storage for TFS (Tencent FS, for ease of differentiation, follow-up called QFS), and Facebook Haystack. Among them, tfs,qfs and haystack need to solve the problem as well as the architecture is very similar, these three file systems are called Blob FS (BLOB file system). This paper compares three typi
Turn from: http://www.nosqlnotes.net/archives/119
A lot of distributed file systems, including Gfs,hdfs, Taobao Open source tfs,tencent for the album Storage of TFS (Tencent FS, in order to facilitate the distinction between follow-up called QFS), and Facebook Haystack. Among them, tfs,qfs and haystack need to solve the problem and the architecture is similar, these three file systems are known as BLOB FS (BLOB file system). This paper compares three
Transferred from: http://www.cnblogs.com/tgzhu/p/5788634.htmlWhen configuring an HBase cluster to hook HDFs to another mirror disk, there are a number of confusing places to study again, combined with previous data; The three cornerstones of big Data's bottom-up technology originated in three papers by Google in 2006, GFS, Map-reduce, and Bigtable, in which GFS, Map-reduce technology directly supported the birth of the Apache Hadoop project, BigTable
Original link: http://blog.itpub.net/30089851/viewspace-2136429/1. Log in to the NN machine, go to the Namenode Configuration folder of the latest serial number, view the log4j configuration of the current NN[Email protected] ~]# cd/var/run/cloudera-scm-agent/process/[Email protected] process]# LS-LRT.....................Drwxr-x--x 3 HDFs HDFs 380 Mar 20:40 372-hdfs
The HDFs we mentioned earlier understands the features and architecture of HDFS. HDFs can store terabytes or even petabytes of data is a prerequisite, first of all the data to large file-based, followed by namenode memory is large enough. Some of the students who know about HDFs know that Namenode is an
HA-Federation-HDFS + Yarn cluster deployment mode
After an afternoon's attempt, I finally set up the cluster, and it didn't feel much necessary to complete the setup. So I should study it and lay the foundation for building the real environment.
The following is a cluster deployment of Ha-Federation-hdfs + Yarn.
First, let's talk about my Configuration:
The four nodes are started respectively:
1. bkjia117:
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