hdfs commands

Original address: http://zh.hortonworks.com/hadoop-tutorial/using-commandline-manage-files-hdfs/In this tutorial we'll walk through some of the basic HDFS commands you'll need to manage files on HDFS. To the tutorial you'll need a working HDP cluster. The easiest to has a Hadoop cluster is to download the Hortonworks S

for the buffer pool, which limits the total size of data that can be cached by commands in the buffer pool. Normally, the buffer pool limit is equal to or greater than the total remaining HDFS cache in the cluster. The buffer pool also tracks a lot of statistics to help cluster users determine what to cache. You can also set the maximum expiration time for the buffer pool. This will limit the maximum expir

A simple introduction to the basic operation of the Hadoop HDFs APIHadoop provides us with a very handy shell command for HDFs (similar to commands for Linux file operations). Hadoop also provides us with HDFSAPI so that our developers can do something about Hfds. such as: Copy file (from local to HDFs, from

Summary: Hadoop HDFS file operations are often done in two ways, command-line mode and JAVAAPI mode. This article describes how to work with HDFs files in both ways. Keywords: HDFs file command-line Java API HDFs is a distributed file system designed for the distributed processing of massive data in the framework of Ma

called MyApp under the Hadoop installation directory to hold our own Hadoop applications, and execute the following commands in the Linux terminal:cd /usr/local/hadoopmkdir myappThen, on the left side of the idea work interface, File > Project Structure, as shown below, then make the appropriate selection:Then select the class to exportThen choose to delete the other dependent classes, leaving only their own code toSelect Build on the menu bar and ch

HDFs system architecture Diagram level analysis Hadoop Distributed File System (HDFS): Distributed File systems * Distributed applications mainly from the schema: Master node Namenode (one) from the node: Datenode (multiple) *HDFS Service Components: Namenode,datanode,secondarynamenode *HDFS storage: Files stored on

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

Spark program Note: This is not the final solution, so you need to find out why If the file is important, you need to fix it.View file status one by one and restoreTake this file as an example:/user/admin/data/cdn//20170508/ngaahcs-access.log.3k3.201705081700.1494234003128.gz To perform a repair command: HDFs Debug Recoverlease-path HDFs Debug Recoverlease-path/user/admin/data/cdn//20170508/ngaahcs-acces

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

rare to remember that this is also done in the GFS paper ). If namenode needs to send some scheduling or control commands to datanode, it must be returned to datanode as the response of heartbeat after datanode sends heartbeat to namenode.Datanode is very busy. It not only needs to regularly send heartbeat to namenode, but also often comes with a lot of control messages to be processed. At the same time, datanode must receive requests for reading and

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

://www.blogjava.net/hongjunli/archive/2007/08/15/137054.html troubleshoot viewing. class filesA typical Hadoop workflow generates data files (such as log files) elsewhere, and then copies them into HDFs, which is then processed by mapreduce, usually without directly reading an HDFs file, which is read by the MapReduce framework. and resolves it to a separate record (key/value pair), unless you specify the i

Transferred from: http://blog.csdn.net/michaelwubo/article/details/50879832First, using the Hadoop URL to read dataPackage Hadoop;import Java.io.inputstream;import Java.net.url;import Org.apache.hadoop.fs.fsurlstreamhandlerfactory;import Org.apache.hadoop.io.ioutils;public class URLCat { static { url.seturlstreamhandlerfactory (new Fsurlstreamhandlerfactory ()); } public static void Readhdfs (String url) throws Exception { inputstream in = null; try {in =

You can use bin/Hadoop fs-ls to Read File Attribute Information on HDFS. You can also use HDFS APIs to read data. As follows: Import java.net. URI;Import org. apache. hadoop. conf. Configuration;Import org. apache. hadoop. fs. FileSystem;Import org. apache. hadoop. fs. Path;Import org. apache. hadoop. fs. FileStatus;Public class FileInfo{Public static void main (String [] args) throws Exception{If (args. le

CheckpointFileSystem {Public static void main (String [] args) throws IOException {Configuration conf = new Configuration ();Job job = Job. getInstance (conf, "DeCodec ");// Methods required for running the packageJob. setJarByClass (CheckpointFileSystem. class );LocalFileSystem localFileSystem = ChecksumFileSystem. getLocal (conf );System. out. println (LocalFileSystem. getChecksumFile (new Path ("/liguodong/data ")));}} [Root @ master liguodong] # yarn jar checksum. jar/Liguodong/. data. crc

is connected. After the client completes writing, it will call the close () method through DistributedFilesystem. This method has a magical effect, it stores all the remaining bags in the data queue in the waiting for confirmation queue and waits for confirmation. The namenode records the datanode of all copies. After reading the theoretical knowledge, I 'd like to share it with you in a simple vernacular. Principle Analysis of HDFS File Reading in H