hadoop cluster setup

Wang Jialin's in-depth case-driven practice of cloud computing distributed Big Data hadoop in July 6-7 in Shanghai Wang Jialin Lecture 4HadoopGraphic and text training course: Build a true practiceHadoopDistributed Cluster EnvironmentHadoopThe specific solution steps are as follows: Step 1: QueryHadoopTo see the cause of the error; Step 2: Stop the cluster;

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 @ localho

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 ...)

Datanode nodemanager server: 192.168.1.100 192.168.1.101 192.168.1.102 Zookeeper server cluster (for namenode high-availability automatic failover): 192.168.1.100 192.168.1.101 Jobhistory server (used to record mapreduce logs): 192.168.1.1 NFS for namenode HA: 192.168.1.100 Environment deployment 1. Add the YUM repository to CDH4 1. the best way is to put the cdh4 package in the self-built yum warehouse. For how to build a self-built yum warehou

Apache Ambari is a Web-based tool that supports the supply, management, and monitoring of Apache Hadoop clusters. Ambari currently supports most Hadoop components, including HDFS, MapReduce, Hive, Pig, Hbase, Zookeper, Sqoop, and Hcatalog.Apache Ambari supports centralized management of HDFS, MapReduce, Hive, Pig, Hbase, Zookeper, Sqoop, and Hcatalog. It is also one of the five top-level

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 m

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

settings for nodes in VirturalboxThe command for viewing the IP address of a node in Linux is the ifconfig inet address shown ( Note that CentoS installed on the virtual machine does not automatically connect to the network and needs to be connected to the Internet in the upper right corner to see the IP address):Linux View IP commandConfigure the machine nameStart by completing the preparation on the Master node and shutting down Hadoop ( /usr/local

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 no

A few days ago, I summarized the hadoop distributed cluster installation process. Building a hadoop cluster is only a difficult step in learning hadoop. More knowledge is needed later, I don't know if I can stick to it or how many difficulties will be encountered in the futu

Although I have installed a Cloudera CDH cluster (see http://www.cnblogs.com/pojishou/p/6267616.html for a tutorial), I ate too much memory and the given component version is not optional. If only to study the technology, and is a single machine, the memory is small, or it is recommended to install Apache native cluster to play, production is naturally cloudera cluster