hadoop copy directory from hdfs to hdfs

HDFS HDFSIt is a distributed file system with high fault tolerance and is suitable for deployment on cheap machines. It has the following features: 1) suitable for storing very large files 2) suitable for stream data reading, that is, suitable for "write only once, read multiple times" data processing mode 3) suitable for deployment on cheap machines However, HDFS is not suitable for the following scenarios

Problem Description:Hadoop in the virtual machine under the Linux systemLocal files are uploaded to the specified directory on the Hadoop platform by writing code locally through eclipseThe code is as follows:@Test Public voidUpload ()throwsIOException {Configuration conf=NewConfiguration (); Conf.set ("Fs.defaultfs", "Hdfs://lujie01:9000/"); FileSystem FS=filesystem.get (conf); Path Path=NewPath ("

, success!About emptying the size of the space, after emptying the logs, or using 15G, there should be other places to continue to empty, welcome advice![Email protected] hadoop]# df-ahfilesystem Size used Avail use% mounted on/dev/sda2 18G 15G 2.1G 88%/proc 0 0 0 - /procsysfs 0 0 0 - /sysdevpts 0 0 0 - /dev/ptstmpfs 9

action instance object for a specific file system, based on the configuration informationFS = Filesystem.get (New URI ("Hdfs://hadoopmaster:9000/"), conf, "Hadoop");}/*** Upload files to compare the underlying wording** @throws Exception*/@Testpublic void Upload () throws Exception {Configuration conf = new configuration ();Conf.set ("Fs.defaultfs", "hdfs://hado

text file to reduce storage space, but also need to support split, and compatible with the previous application (that is, the application does not need to modify) situation. 5.comparison of the characteristics of 4 compression formats compression Format Split native Compression ratio Speed whether Hadoop comes with Linux Commands if the original application has to be modified after you cha

Hadoop was inspired by Google, and was originally designed to address the high and slow cost of data processing in traditional databases. Hadoop two core projects are HDFS(Hadoop Distributed File System) and MapReduce. HDFs is used to store data, which is different from

HDFs:The condition configuration is the same as above1. The client initiates a read request to Namenode (hereinafter referred to as NN)2. NN returns a partial or full block list of a file to the client, and for each BLOCK,NN returns the address of the backup node for that block3. The client selects the nearest DN to read the block, closes the connection to the current DN after reading the data from the block, and looks for the next best DN storage block4. If no files have been read until after

accessapplications that require low-latency access to data in the millisecond range are not suitable for HDFS. HDFs is optimized for high data throughput, which may be at the expense of latency. Currently, HBase is a better choice for low-latency accessa large number of small filesThe namenode node stores the file system's metadata, so the limit on the number of files is determined by the amount of memory

*@throwsurisyntaxexception*/ Public StaticFileSystem Getfilesystembyuser (String puser)throwsException, interruptedexception, urisyntaxexception{String Fileuri= "/home/test/test.txt" ; Configuration conf=NewConfiguration (); Conf.set ("Fs.defaultfs", "hdfs://192.168.1.109:8020"); FileSystem FileSystem= Filesystem.get (NewURI (Fileuri), Conf, puser); returnFileSystem; } }2. Main classThis class is primarily used for file read and write and