Hue employs some Python modules which use native code and requires certain development libraries be installed on your system. To install from the tarball, you must have the following installed:

The full list is here: https://github.com/cloudera/hue#development-prerequisites

Configure $PREFIX with the path where you want to install Hue by running:

$ PREFIX=/usr/share make install
$ cd /usr/share/hue

You can install Hue anywhere on your system, and run Hue as a non-root user. The Shell application needs root privileges to launch various sub-processes as the logged in users. $USER should be the group of the user running Hue (same as its username).

It is a good practice to create a new user for Hue and either install Hue in that user’s home directory, or in a directory within /usr/share.

Q: I moved my Hue installation from one directory to another and now Hue no. longer functions correctly.

A: Due to the use of absolute paths by some Python packages, you must run a series of commands if you move your Hue installation. In the new location, run:

$ rm app.reg
$ rm -r build
$ make apps

Q: Why does "make install" compile other pieces of software? A: In order to ensure that Hue is stable on a variety of distributions and architectures, it installs a Python virtual environment which includes its dependencies. This ensures that the software can depend on specific versions of various Python libraries and you don’t have to be concerned about missing software components.

Install Hadoop -_~~_~~_~~~

Depending on which apps you need, you need to make sure that some Hadoop services are already setup (that way Hue can talk to them).

You need to enable WebHdfs or run an HttpFS server. To turn on WebHDFS, add this to your hdfs-site.xml and restart your HDFS cluster. Depending on your setup, your hdfs-site.xml might be in /etc/hadoop/conf.

<property>
  <name>dfs.webhdfs.enabled</name>
  <value>true</value>
</property>

You also need to add this to core-site.html.

<property>
  <name>hadoop.proxyuser.hue.hosts</name>
  <value>*</value>
</property>
<property>
  <name>hadoop.proxyuser.hue.groups</name>
  <value>*</value>
</property>

If you place your Hue Server outside the Hadoop cluster, you can run an HttpFS server to provide Hue access to HDFS. The HttpFS service requires only one port to be opened to the cluster.

Also add this in httpfs-site.xml which might be in /etc/hadoop-httpfs/conf.

<property>
  <name>httpfs.proxyuser.hue.hosts</name>
  <value>*</value>
</property>
<property>
  <name>httpfs.proxyuser.hue.groups</name>
  <value>*</value>
</property>

Hue is using only standard Hadoop APIs.

Hue communicates with the JobTracker via the Hue plugins, which is a jar file that you place in your MapReduce lib directory.

If you JobTracker and Hue are located on the same host, copy it over.

$ cd /usr/share/hue
$ cp desktop/libs/hadoop/java-lib/hue-plugins-*.jar /usr/lib/hadoop-0.20-mapreduce/lib

If you JobTracker runs on a different host, you need to scp the Hue plugins jar to the JobTracker host.

Then add this to your mapred-site.xml and restart your JobTracker. Depending on your setup, your mapred-site.xml might be in /etc/hadoop/conf.

<property>
  <name>jobtracker.thrift.address</name>
  <value>0.0.0.0:9290</value>
</property>
<property>
  <name>mapred.jobtracker.plugins</name>
  <value>org.apache.hadoop.thriftfs.ThriftJobTrackerPlugin</value>
  <description>Comma-separated list of jobtracker plug-ins to be activated.</description>
</property>

You can confirm that the plugins are running correctly by tailing the daemon logs:

$ tail --lines=500 /var/log/hadoop-0.20/hadoop*jobtracker*.log | grep ThriftPlugin
2009-09-28 16:30:44,337 INFO org.apache.hadoop.thriftfs.ThriftPluginServer: Starting Thrift server
2009-09-28 16:30:44,419 INFO org.apache.hadoop.thriftfs.ThriftPluginServer:
Thrift server listening on 0.0.0.0:9290

Hue submits MapReduce jobs to Oozie as the logged in user. You need to configure Oozie to accept the hue user to be a proxyuser. Specify this in your oozie-site.xml (even in a non-secure cluster), and restart Oozie:

<property>
    <name>oozie.service.ProxyUserService.proxyuser.hue.hosts</name>
    <value>*</value>
</property>
<property>
    <name>oozie.service.ProxyUserService.proxyuser.hue.groups</name>
    <value>*</value>
</property>

If you are setting $HADOOP_CLASSPATH in your hadoop-env.sh, be sure to set it in such a way that user-specified options are preserved. For example:

Correct:

# HADOOP_CLASSPATH=<your_additions>:$HADOOP_CLASSPATH

Incorrect:

# HADOOP_CLASSPATH=<your_additions>

This enables certain components of Hue to add to Hadoop’s classpath using the environment variable.

If your users are likely to be submitting jobs both using Hue and from the same machine via the command line interface, they will be doing so as the hue user if they’re using Hue and via their own user account on the command line. This leads to some contention on the directory specified by hadoop.tmp.dir, which defaults to /tmp/hadoop-${user.name}. Specifically, hadoop.tmp.dir is used to unpack jars in bin/hadoop jar. One work around to this is to set hadoop.tmp.dir to /tmp/hadoop-${user.name}-${hue.suffix} in the core-site.xml file:

<property>
  <name>hadoop.tmp.dir</name>
  <value>/tmp/hadoop-${user.name}${hue.suffix}</value>
</property>

Unfortunately, when the variable is unset, you’ll end up with directories named /tmp/hadoop-user_name-${hue.suffix} in /tmp. Despite that, Hue will still work.

	The Beeswax server writes into a local directory on the Hue machine that is specified by hadoop.tmp.dir to unpack its jars. That directory needs to be writable by the hue user, which is the default user who starts Beeswax Server, or else Beeswax server will not start. You may also make that directory world-writable.

Hue currently requires that the machines within your cluster can connect to each other freely over TCP. The machines outside your cluster must be able to open TCP port 8888 on the Hue Server (or the configured Hue web HTTP port) to interact with the system.

Hue uses CherryPy web server. You can use the following options to change the IP address and port that the web server listens on. The default setting is port 8888 on all configured IP addresses.

# Webserver listens on this address and port
http_host=0.0.0.0
http_port=8888

For security, you should also specify the secret key that is used for secure hashing in the session store. Enter a long series of random characters (30 to 60 characters is recommended).

secret_key=jFE93j;2[290-eiw.KEiwN2s3['d;/.q[eIW^y#e=+Iei*@Mn<qW5o

	If you don’t specify a secret key, your session cookies will not be secure. Hue will run but it will also display error messages telling you to set the secret key.

By default, the first user who logs in to Hue can choose any username and password and becomes an administrator automatically. This user can create other user and administrator accounts. User information is stored in the Django database in the Django backend.

The authentication system is pluggable. For more information, see the Hue SDK Documentation.

You can configure Hue to serve over HTTPS. To do so, you must install "pyOpenSSL" within Hue’s context and configure your keys.

To install pyOpenSSL, from the root of your Hue installation path, do the following steps:

	Self-signed Certificates and File Uploads
	To upload files using the Hue File Browser over HTTPS requires using a proper SSL Certificate. Self-signed certificates don’t work.

Hue only support one HDFS cluster currently. That cluster should be defined under the [[[default]]] sub-section.

Hue only support one MapReduce cluster currently. That cluster should be defined under the [[[default]]] sub-section. Note that JobBrowser only works with MR1.

Hue only support one Yarn cluster currently. That cluster should be defined under the [[[default]]] sub-section.

Filebrowser requires Hue to be running as the hue user.

A script called supervisor manages all Hue processes. The supervisor is a watchdog process — its only purpose is to spawn and monitor other processes. A standard Hue installation starts and monitors the following processes:

If you have installed other applications into your Hue instance, you may see other daemons running under the supervisor as well.

You can see the supervised processes running in the output of ps -f -u hue:

UID        PID  PPID  C STIME TTY          TIME CMD
hue       8685  8679  0 Aug05 ?        00:01:39 /usr/share/hue/build/env/bin/python /usr/share/hue/build/env/bin/desktop runcpserver

Note that the supervisor automatically restarts these processes if they fail for any reason. If the processes fail repeatedly within a short time, the supervisor itself shuts down.

In addition to logging INFO level messages to the logs directory, the Hue web server keeps a small buffer of log messages at all levels in memory. You can view these logs by visiting http://myserver:8888/logs. The DEBUG level messages shown can sometimes be helpful in troubleshooting issues.

The default SQLite database used by Hue is located in: ‘/usr/share/hue/desktop/desktop.db. You can inspect this database from the command line using the `sqlite3 program or typing `/usr/share/hue/build/env/bin/hue dbshell’. For example:

# sqlite3 /usr/share/hue/desktop/desktop.db
SQLite version 3.6.22
Enter ".help" for instructions
Enter SQL statements terminated with a ";"
sqlite> select username from auth_user;
admin
test
sample
sqlite>

It is strongly recommended that you avoid making any modifications to the database directly using SQLite, though this trick can be useful for management or troubleshooting.

If you use the default SQLite database, then copy the desktop.db file to another node for backup. It is recommended that you back it up on a regular schedule, and also that you back it up before any upgrade to a new version of Hue.

Although SQLite is the default database type, some advanced users may prefer to have Hue access an alternate database type. Note that if you elect to configure Hue to use an external database, upgrades may require more manual steps in the future.

The following instructions are for MySQL, though you can also configure Hue to work with other common databases such as PostgreSQL and Oracle.

	Tested Database Backends
	Note that Hue has only been tested with SQLite and MySQL database backends.

To configure Hue to store data in MySQL:

Your system is now configured and you can start the Hue server as normal.