hue hadoop

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

-master mode. To ensure configuration data consistency, Zookeeper is introduced in flume [1] to save configuration data. zookeeper can ensure consistency and high availability of configuration data. In addition, when configuration data changes, zookeeper can notify the flume master node. The flume master synchronizes data using the gossip protocol.For details, see:What isFlumeLog collection,FlumeFeatures What isFlumeLog collection,FlumeWhat is the principle,FlumeWhat problems do you encounter? 4

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

Hadoop family products, commonly used projects include Hadoop, Hive, Pig, HBase, Sqoop, Mahout, Zookeeper, Avro, Ambari, Chukwa, new additions including, YARN, Hcatalog, Oozie, 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

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

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

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

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,

deployment.The reminder here is not to re-export the same credentials to prevent the vouchers in the keytab that have been distributed from being invalidated.Balancer execution too long causes certification to expireAfter the security certification is deployed, we need to pre-certify the HDFS data for balance and then run into the issue of the authentication deadlines we said earlier.There are two ways to solve this problem: Add external timer task re-authentication, refresh credential

Word count is one of the simplest and most well-thought-capable programs, known as the MapReduce version of "Hello World", and the complete code for the program can be found in the Src/example directory of the Hadoop installation package. The main function of Word counting: count the number of occurrences of each word in a series of text files, as shown in. This blog will be through the analysis of WordCount source code to help you to ascertain the ba

1. What is a distributed file system? A file system stored across multiple computers in a management network is called a distributed file system. 2. Why do we need a distributed file system? The reason is simple. When the data set size exceeds the storage capacity of an independent physical computer, it is necessary to partition it and store it on several independent computers. 3. distributed systems are more complex than traditional file systems Because the Distributed File System arc