We’re going to have a look at HDFS by interacting with it from the command line. There are many other interfaces to HDFS, but the command line is one of the simplest and, to many developers, the most familiar. We are going to run HDFS on one machine, so first follow the instructions for setting up Hadoop in pseudo-distributed mode in Appendix A. Later you’ll see how to run on a cluster of machines to give us scalability and fault tolerance.
There are two properties that we set in the pseudo-distributed configuration that deserve further explanation. The first is fs.default.name, set to hdfs://localhost/, which is used to set a default filesystem for Hadoop. Filesystems are specified by a URI, and here we have used an hdfs URI to configure Hadoop to use HDFS by default. The HDFS daemons will use this property to determine the host and port for the HDFS namenode. We’ll be running it on localhost, on the default HDFS port, 8020. And HDFS clients will use this property to work out where the namenode is running so they can connect to it.
We set the second property, dfs.replication, to 1 so that HDFS doesn’t replicate filesystem blocks by the default factor of three. When running with a single datanode, HDFS can’t replicate blocks to three datanodes, so it would perpetually warn about blocks being under-replicated. This setting solves that problem.
Basic Filesystem Operations
The filesystem is ready to be used, and we can do all of the usual filesystem operations such as reading files, creating directories, moving files, deleting data, and listing directories. You can type hadoop fs -help to get detailed help on every command.
Start by copying a file from the local filesystem to HDFS:
This command invokes Hadoop’s filesystem shell command fs, which supports a number of subcommands in this case, we are running -copyFromLocal. The local file quangle.txt is copied to the file /user/tom/quangle.txt on the HDFS instance running on localhost. In fact, we could have omitted the scheme and host of the URI and picked up the default, hdfs://localhost, as specified in core-site.xml:
Let’s copy the file back to the local filesystem and check whether it’s the same:
The MD5 digests are the same, showing that the file survived its trip to HDFS and is back intact.
Finally, let’s look at an HDFS file listing. We create a directory first just to see how it is displayed in the listing:
The information returned is very similar to the Unix command ls -l, with a few minor differences. The first column shows the file mode. The second column is the replication factor of the file (something a traditional Unix filesystem does not have). Remember we set the default replication factor in the site-wide configuration to be 1, which is why we see the same value here. The entry in this column is empty for directories since the concept of replication does not apply to them directories are treated as metadata and stored by the namenode, not the datanodes. The third and fourth columns show the file owner and group. The fifth column is the size of the file in bytes, or zero for directories. The sixth and seventh columns are the last modified date and time. Finally, the eighth column is the absolute name of the file or directory.
File Permissions in HDFS
HDFS has a permissions model for files and directories that is much like POSIX. There are three types of permission: the read permission (r), the write permission (w), and the execute permission (x). The read permission is required to read files or list the contents of a irectory. The write permission is required to write a file, or for a directory, to create or delete files or directories in it. The execute permission is ignored for a file since you can’t execute a file on HDFS (unlike POSIX), and for a directory it is required to access its children. Each file and directory has an owner, a group, and a mode. The mode is made up of the permissions for the user who is the owner, the permissions for the users who are members of the group, and the permissions for users who are neither the owners nor members of the group. By default, a client’s identity is determined by the username and groups of the process it is running in. Because clients are remote, this makes it possible to become an arbitrary user, simply by creating an account of that name on the remote system. Thus, permissions should be used only in a cooperative community of users, as a mechanism for sharing filesystem resources and for avoiding accidental data loss, and not for securing resources in a hostile environment. (Note, however, that the latest versions of Hadoop support Kerberos authentication, which removes these restrictions, see “Security”.) Despite these limitations, it is worthwhile having permissions enabled(as it is by default; see the dfs.permissions property), to avoid accidental modification or deletion of substantial parts of the filesystem, either by users or by automated tools or programs. When permissions checking is enabled, the owner permissions are checked if the client’s username matches the owner, and the group permissions are checked if the client is a member of the group; otherwise, the other permissions are checked. There is a concept of a super-user, which is the identity of the namenode process. Permissions checks are not performed for the super-user.
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The Hadoop Distributed Filesystem
Developing A Mapreduce Application
How Mapreduce Works
Mapreduce Types And Formats
Setting Up A Hadoop Cluster
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