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- r1.0.4
- r1.2.1
r1.0.4
Hadoop Archives
什么是Hadoop archives? Hadoop archives是特殊的档案格式。一个Hadoop archive对应一个文件系统目录。 Hadoop archive的扩展名是*.har。Hadoop archive包含元数据（形式是_index和_masterindx）和数据（part-*）文件。_index文件包含了档案中的文件的文件名和位置信息。
如何创建archive?
用法: hadoop archive -archiveName name <src>* <dest>由-archiveName选项指定你要创建的archive的名字。比如foo.har。archive的名字的扩展名应该是*.har。输入是文件系统的路径名，路径名的格式和平时的表达方式一样。创建的archive会保存到目标目录下。注意创建archives是一个Map/Reduce job。你应该在map reduce集群上运行这个命令。下面是一个例子：
hadoop archive -archiveName foo.har /user/hadoop/dir1 /user/hadoop/dir2 /user/zoo/
在上面的例子中， /user/hadoop/dir1 和 /user/hadoop/dir2 会被归档到这个文件系统目录下 -- /user/zoo/foo.har。当创建archive时，源文件不会被更改或删除。
如何查看archives中的文件? archive作为文件系统层暴露给外界。所以所有的fs shell命令都能在archive上运行，但是要使用不同的URI。 另外，archive是不可改变的。所以重命名，删除和创建都会返回错误。Hadoop Archives 的URI是
har://scheme-hostname:port/archivepath/fileinarchive
如果没提供scheme-hostname，它会使用默认的文件系统。这种情况下URI是这种形式
har:///archivepath/fileinarchive
这是一个archive的例子。archive的输入是/dir。这个dir目录包含文件filea，fileb。 把/dir归档到/user/hadoop/foo.bar的命令是
hadoop archive -archiveName foo.har /dir /user/hadoop
获得创建的archive中的文件列表，使用命令
hadoop dfs -lsr har:///user/hadoop/foo.har
查看archive中的filea文件的命令-
hadoop dfs -cat har:///user/hadoop/foo.har/dir/filea
r1.2.1
Hadoop Archives Guide
Overview Hadoop archives are special format archives. A Hadoop archive maps to a file system directory. A Hadoop archive always has a .har extension. A Hadoop archive directory contains metadata (in the form of _index and _masterindex) and data (part-) files. The _index file contains the name of the files that are part of the archive and the location within the part files.
How to Create an Archive Usage: hadoop archive -archiveName name -p <parent> <src>* <dest>
-archiveName is the name of the archive you would like to create. An example would be foo.har. The name should have a *.har extension. The parent argument is to specify the relative path to which the files should be archived to. Example would be :
-p /foo/bar a/b/c e/f/g
Here /foo/bar is the parent path and a/b/c, e/f/g are relative paths to parent. Note that this is a Map/Reduce job that creates the archives. You would need a map reduce cluster to run this. For a detailed example the later sections.
If you just want to archive a single directory /foo/bar then you can just use
hadoop archive -archiveName zoo.har -p /foo/bar /outputdir
How to Look Up Files in Archives The archive exposes itself as a file system layer. So all the fs shell commands in the archives work but with a different URI. Also, note that archives are immutable. So, rename's, deletes and creates return an error. URI for Hadoop Archives is
har://scheme-hostname:port/archivepath/fileinarchive
If no scheme is provided it assumes the underlying filesystem. In that case the URI would look like
har:///archivepath/fileinarchive
Archives Examples Creating an Archive hadoop archive -archiveName foo.har -p /user/hadoop dir1 dir2 /user/zoo
The above example is creating an archive using /user/hadoop as the relative archive directory. The directories /user/hadoop/dir1 and /user/hadoop/dir2 will be archived in the following file system directory -- /user/zoo/foo.har. Archiving does not delete the input files. If you want to delete the input files after creating the archives (to reduce namespace), you will have to do it on your own.
Looking Up Files Looking up files in hadoop archives is as easy as doing an ls on the filesystem. After you have archived the directories /user/hadoop/dir1 and /user/hadoop/dir2 as in the example above, to see all the files in the archives you can just run:
hadoop dfs -lsr har:///user/zoo/foo.har/
To understand the significance of the -p argument, lets go through the above example again. If you just do an ls (not lsr) on the hadoop archive using
hadoop dfs -ls har:///user/zoo/foo.har
The output should be:
har:///user/zoo/foo.har/dir1 har:///user/zoo/foo.har/dir2 As you can recall the archives were created with the following command
hadoop archive -archiveName foo.har -p /user/hadoop dir1 dir2 /user/zoo
If we were to change the command to:
hadoop archive -archiveName foo.har -p /user/ hadoop/dir1 hadoop/dir2 /user/zoo
then a ls on the hadoop archive using
hadoop dfs -ls har:///user/zoo/foo.har
would give you
har:///user/zoo/foo.har/hadoop/dir1 har:///user/zoo/foo.har/hadoop/dir2 Notice that the archived files have been archived relative to /user/ rather than /user/hadoop.
Hadoop Archives and MapReduce Using Hadoop Archives in MapReduce is as easy as specifying a different input filesystem than the default file system. If you have a hadoop archive stored in HDFS in /user/zoo/foo.har then for using this archive for MapReduce input, all you need to specify the input directory as har:///user/zoo/foo.har. Since Hadoop Archives is exposed as a file system MapReduce will be able to use all the logical input files in Hadoop Archives as input.
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