The Hadoop version of this blog is Hadoop 0.20.2.Installing Hadoop-0.20.2-eclipse-plugin.jar
To download the Hadoop-0.20.2-eclipse-plugin.jar file and add it to the Eclipse plug-in library, add a method that is simple: Locate the plugins directory under the Eclipse installation directory, copy directly to this
Once Hadoop is installed, you will often be prompted with a warning:
WARN util. nativecodeloader:unable to load Native-hadoop library for your platform ...
Using Builtin-java classes where applicableSearched a lot of articles, all say is related to the system bit number, I use CentOS 6.5 64-bit operating system.
The first two days in the Docker image to find a step to solve the problem, the pro tried
VMware has installed Multiple RedHatLinux operating systems, excerpted a lot of online materials, and installed them in order? 1. Create groupaddbigdatauseradd-gbigdatahadooppasswdhadoop? 2. Create JDKvietcprofile? ExportJAVA_HOMEusrlibjava-1.7.0_07exportCLASSPATH.
VMware has installed Multiple RedHat Linux operating systems, excerpted a lot of online materials, and installed them in order? 1. Create groupadd bigdata useradd-g bigdata hadoop passwd
Detailed procedures for starting the HDFS process using start-dfs.sh
The scripts involved are:
Under Bin:
hadoop-config.sh
start-dfs.sh
hadoop-daemons.sh
slaves.sh
hadoop-daemon.sh
Hadoop
Conf under:
hadoop-env.sh
Where both
Preface
The most interesting thing about hadoop is hadoop Job Scheduling. Before introducing how to set up hadoop, it is necessary to have a deep understanding of hadoop job scheduling. We may not be able to use hadoop, but if we understand the Distributed Scheduling Princip
Hadoop distributed platform optimization, hadoop
Hadoop performance tuning is not only its own tuning, but also the underlying hardware and operating system. Next we will introduce them one by one:
1. underlying hardware
Hadoop adopts the master/slave architecture. The master (resourcemanager or namenode) needs to mai
OneEclipse Import Hadoop Source projectBasic steps:1) Create a new Java project "hadoop-1.2.1" in Eclipse2) Copy the Core,hdfs,mapred,tools,example four directory under the directory src of the Hadoop compression package to the SRC directory of the new project above3) Right click to select Build path, modify Java Build path "source", delete src, add src/core,src/
In Hadoop, data processing is resolved through the MapReduce job. Jobs consist of basic configuration information, such as the path of input files and output folders, which perform a series of tasks by the MapReduce layer of Hadoop. These tasks are responsible for first performing the map and reduce functions to convert the input data to the output results.
To illustrate how MapReduce works, consider a simp
Hadoop pseudo-distribution installation steps, hadoop Installation Steps2. steps for installing hadoop pseudo-distribution: 1.1 set the static IP address icon in the upper-right corner of the centos desktop, right-click to modify and restart the NIC, and run the Command service network restart for verification: ifconfig 1.2 modify the host name
Hadoop is a distributed storage and computing platform for Big dataArchitecture of HDFs: Master-Slave architectureThe primary node has only one namenode, and there can be many datanode from the node.Namenode is responsible for:(1) Receiving User action request(2) Maintaining the directory structure of the file system(3) Managing the relationship between the file and block, and the connection between block and DatanodeDatanode is responsible for:(1) St
Hadoop has a distributed system called HDFS , all known as Hadoop distributed Filesystem.HDFs has a block concept, and the default is that the file on 64mb,hdfs is divided into chunks of block size, as separate storage units. The advantage of using blocks is: 1. A file size can be larger than the capacity of any disk in the cluster network, and all blocks of the file do not need to be stored on the same dis
P3-P4:The problem is simple: the capacity of hard disk is increasing, 1TB has become the mainstream, however, data transmission speed has risen from the 1990 4.4mb/s only to the current 100mb/sReading a 1TB hard drive data takes at least 2.5 hours. Writing the data consumes more time. The workaround is to read from multiple hard drives, imagine that if there are currently 100 disks, each disk stores 1% data, then the parallel reads only need 2minutes to read all the data.At the same time, parall
The following error is reported:Workaround:1. Increase Debugging informationAdd the following information in the hadoop_home/etc/hadoop/hadoop-env.sh file2. Perform another operation to see what errors are reportedThe above information shows that 2.14 GLIBC library is requiredWorkaround:1. View the libc version of the system (LL/LIB64/LIBC.SO.6)Display version is 2.12The first solution, using the 2.12 versi
A virtual machine was started on Shanda cloud. The default user is root. An error occurred while running hadoop:
[Error description]
Root @ snda:/data/soft/hadoop-0.20.203.0 # bin/hadoop FS-put conf Input11/08/03 09:58:33 warn HDFS. dfsclient: datastreamer exception: Org. apache. hadoop. IPC. remoteException: Java. io.
Hadoop provides mapreduce with an API that allows you to write map and reduce functions in languages other than Java: hadoop streaming uses standard streamams) as an interface for data transmission between hadoop and applications. Therefore, you can write the map and reduce functions in any language, as long as it can read data from the standard input stream (std
Apache Hadoop and the Hadoop EcosystemHadoop is a distributed system infrastructure developed by the Apache Foundation .The user is able to understand the distributed underlying details. Develop distributed programs. Take advantage of the power of the cluster for fast operations and storage.Hadoop implements a distributed filesystem (Hadoop distributedFile system
Whether you are adding machines and removing machines in a Hadoop cluster, there is no downtime and the entire service is uninterrupted.
Before this operation, the cluster of Hadoop is as follows:
The machine condition for HDFs is as follows:
The machine condition of Mr is as follows:
Adding Machines
In the master machine of the cluster, modify the $hadoop_home/conf/slaves file to add the hostname of the n
Hadoop (13), hadoop
1. mahout introduction:
Mahout is a powerful data mining tool and a collection of distributed machine learning algorithms, including the implementation, classification, and clustering of distributed collaborative filtering called Taste. The biggest advantage of Mahout is its hadoop-based implementation, which converts many previous algorithms
application submission context information to the ASM2, ASM to Scheduler request a container for AM to run, send launchcontainer information to its nm, start container3. Am is registered with ASM when the NM is started4. Job client obtains AM information from ASM and communicates directly with it5. Am calculates splits and constructs resource requests for all maps6, am to do some outputcommitter preparation work7, am to Scheduler request resources (a group of container) and then together with N
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