hadoop file formats and compression

There are two main advantages of file compression, one is to reduce the space for storing files, and the other is to speed up data transmission. In the context of Hadoop big data, these two points are especially important, so I'm going to look at the file compression of Hado

Mapmap read files in different formats This problem has always been, the previous reading method is to get the name of the file in the map, according to the name of different ways to read, such as the following wayFetch file name Inputsplit Inputsplit = Context.getinputsplit (); String FileName = ((filesplit) inputsplit). GetPath (). toString (), if (Filename.con

This section roughly summarizes the compression and decompression methods for various formats of compressed packages in linux. However, I have not used some of the methods. I hope you can help me with them. I will modify them at any time. Thank you!What are the compression formats in LINUX?. TarUnpack: tar xvf FileName

1.CompressionCodecFactory IntroductionWhen reading a compressed file, you may not know which compression algorithm is used to compress the file, then the decompression task cannot be completed. In Hadoop, compressioncodecfactory by using its Getcodec () method, you can map to a Compressioncodec class with its correspon

Learning about the Hadoop Compression decompression Architecture The Compressor decompression module of Hadoop is another major module in the Hadoop Common IO module. Although in real life, there are not so many scenarios where we use compression tools. Perhaps in our potent

template use File |Settings | File Templates. */ Public class Streamcompressor { public static void Main (string[] args) throws Exception { String codecclassname = args[0]; class Configuration conf = new configuration (); Compressioncodec codec = (COMPRESSIONCODEC) reflectionutils.newinstance (codecclass, conf); Compressionoutputstream out = Codec.createoutputstream (System.out);

In recent days to verify the next Lzo This compression mode, has the following feeling: Recently Lzo use problem, found Java.library.path setup problem, many online write is in hadoop-env.sh file add Java_library_path this attribute (about another increase Hadoop_classpath is valid , it is true that the jar package under the Lib directory is not automatically loa

............... ........................................ ........................................ ........................................ ........................................ ........................................ setrep: `/fish/1.txt ': No such file or directory [[email protected] bin] # hadoop fs -stat "% b% F% u:% g% o% y% n% r" /fish/1.txt Return value: Return 0 for success, 1 to

use: Hadoop fs-rmr uri [uri ...]The recursive version of Delete.Example: Hadoop Fs-rmr/user/hadoop/dir Hadoop FS-RMR Hdfs://host:port/user/hadoop/dir return value:Successful return 0, Failure returns-1.21:setrepHow to use:

| File Templates. */public class Maxtemperaturewithcompression {public static void main (string[] args) throws Exception {if ( args.length!=2) {System.out.println ("usage:maxtemperature Input is also a compressed file ~/hadoop/bin/hadoop com.sweetop.styhadoop.MaxTemperatureWithCompression input/data.gz

, then the entire input file will be treated as an input source of the data. The inability to separate means that a T's data is given to a map processing.2. What is the compression decompression speed? Typically, Hadoop operates on disk/io-intensive operations. The bottleneck of the operation is generally on disk IO, CPU This utilization is not high, the algorith

Data from the outside into the map, it is possible that the file is compressed, for the common compression do not care, the map inside is built-in support.When map execution is completed, output to reduce, this time need to go through a shuffer process, need to transfer, very consumption of network resources, in this case, the smaller the amount of data, the better.At this point we can compress the output o

Two benefits of file compression: reducing the disk space required to store files and accelerating data transmission over networks and disksIn storage, all algorithms weigh space/time, and all algorithms weigh cpu/transfer speed when processing The following is a list of common compression methods used in conjunction with Had