ceph hadoop

production environment Hadoop large cluster fully distributed mode installation 2013-3-7 Installation Environment Operating platform: Vmware2 Operating system: Oracle Enterprise Linux 5.6 Software version: Hadoop-0.22.0,jdk-6u18 Cluster Architecture: Node,master node (hotel01), slave node (hotel02,hotel03 ...) Host name IP System version

Build a Hadoop Client-that is, access Hadoop from hosts outside the Cluster Build a Hadoop Client-that is, access Hadoop from hosts outside the Cluster 1. Add host ing (the same as namenode ing ): Add the last line [Root @ localhost ~] # Su-root [Root @ localhost ~] # Vi/etc/hosts127.0.0.1 localhost. localdomain localh

Chapter 1 Meet HadoopData is large, the transfer speed is not improved much. it's a long time to read all data from one single disk-writing is even more slow. the obvious way to reduce the time is read from multiple disk once.The first problem to solve is hardware failure. The second problem is that most analysis task need to be able to combine the data in different hardware. Chapter 3 The Hadoop Distributed FilesystemFilesystem that manage storage h

Hadoop cannot be started properly (1) Failed to start after executing $ bin/hadoop start-all.sh. Exception 1 Exception in thread "Main" Java. Lang. illegalargumentexception: Invalid URI for namenode address (check fs. defaultfs): file: // has no authority. Localhost: At org. Apache. hadoop. HDFS. server. namenode. namenode. getaddress (namenode. Java: 214) Localh

ArticleDirectory Obtain Java Obtain hadoop Set Environment Variables Configure hadoop-env.sh Configure core-site.xml Configure hdfs-site.xml Configure mapred-site.xml Install HDFS Start hadoop Simple debugging Obtain Java Obtain hadoop Set Environment Variables Configure

First explain the configured environmentSystem: Ubuntu14.0.4Ide:eclipse 4.4.1Hadoop:hadoop 2.2.0For older versions of Hadoop, you can directly replicate the Hadoop installation directory/contrib/eclipse-plugin/hadoop-0.20.203.0-eclipse-plugin.jar to the Eclipse installation directory/plugins/ (and not personally verified). For HADOOP2, you need to build the jar f

Introduction HDFs is not good at storing small files, because each file at least one block, each block of metadata will occupy memory in the Namenode node, if there are such a large number of small files, they will eat the Namenode node's large amount of memory. Hadoop archives can effectively handle these issues, he can archive multiple files into a file, archived into a file can also be transparent access to each file, and can be used as a mapreduce

1 Creating Hadoop user groups and Hadoop users　　STEP1: Create a Hadoop user group:~$ sudo addgroup Hadoop　　STEP2: Create a Hadoop User:~$ sudo adduser-ingroup Hadoop hadoopEnter the password when prompted, this is the new

Hadoop In The Big Data era (1): hadoop Installation If you want to have a better understanding of hadoop, you must first understand how to start or stop the hadoop script. After all,Hadoop is a distributed storage and computing framework.But how to start and manage t

As a matter of fact, you can easily configure the distributed framework runtime environment by referring to the hadoop official documentation. However, you can write a little more here, and pay attention to some details, in fact, these details will be explored for a long time. Hadoop can run on a single machine, or you can configure a cluster to run on a single machine. To run on a single machine, you only

Preface After a while of hadoop deployment and management, write down this series of blog records. To avoid repetitive deployment, I have written the deployment steps as a script. You only need to execute the script according to this article, and the entire environment is basically deployed. The deployment script I put in the Open Source China git repository (http://git.oschina.net/snake1361222/hadoop_scripts ). All the deployment in this article is b

ObjectiveWhat is Hadoop?In the Encyclopedia: "Hadoop is a distributed system infrastructure developed by the Apache Foundation." Users can develop distributed programs without knowing the underlying details of the distribution. Take advantage of the power of the cluster to perform high-speed operations and storage. ”There may be some abstraction, and this problem can be re-viewed after learning the various

Hadoop consists of two parts: Distributed File System (HDFS) Distributed Computing framework mapreduce The Distributed File System (HDFS) is mainly used for the Distributed Storage of large-scale data, while mapreduce is built on the Distributed File System to perform distributed computing on the data stored in the distributed file system. Describes the functions of nodes in detail. Namenode: 1. There is only one namenode in the

Previously introduced me in Ubuntu under the combination of virtual machine Centos6.4 build hadoop2.7.2 cluster, in order to do mapreduce development, to use eclipse, and need the corresponding Hadoop plugin Hadoop-eclipse-plugin-2.7.2.jar, first of all, in the official Hadoop installation package before hadoop1.x with Eclipse Plug-ins, And now with the increase

I built a Hadoop2.6 cluster with 3 CentOS virtual machines. I would like to use idea to develop a mapreduce program on Windows7 and then commit to execute on a remote Hadoop cluster. After the unremitting Google finally fixI started using Hadoop's Eclipse plug-in to execute the job and succeeded, and later discovered that MapReduce was executed locally and was not committed to the cluster at all. I added 4 configuration files for

We all know that an address has a number of companies, this case will be two types of input files: address classes (addresses) and company class (companies) to do a one-to-many association query, get address name (for example: Beijing) and company name (for example: Beijing JD, Beijing Associated information for Red Star).Development environmentHardware environment: Centos 6.5 server 4 (one for master node, three for slave node)Software Environment: Java 1.7.0_45,

The main introduction to the Hadoop family of products, commonly used projects include Hadoop, Hive, Pig, HBase, Sqoop, Mahout, Zookeeper, Avro, Ambari, Chukwa, new additions include, YARN, Hcatalog, O Ozie, Cassandra, Hama, Whirr, Flume, Bigtop, Crunch, hue, etc.Since 2011, China has entered the era of big data surging, and the family software, represented by Hadoop