Welcome to the repository for Hue

Note

This is the development-oriented readme. If you want to write notes for end users, please put them in dist/README.

Hue is both a Web UI for Hadoop and a framework to create interactive Web applications. It features:

• FileBrowser for accessing HDFS
• Job Designer for creating MapReduce/Streaming/Java jobs
• Oozie App for submitting and scheduling workflows
• JobBrowser for viewing MapReduce jobs
• Beeswax application for executing Hive queries
• A Pig/HBase shell

On top of that, a SDK is available for creating new apps integrated with Hadoop.

More documentation is available at http://cloudera.github.com/hue/.

Getting Started

To build and get the core server running:

$ git clone http://github.com/cloudera/hue.git
$ cd hue
$ make apps
$ build/env/bin/hue runserver

If using the Beeswax application, start the daemon:

$ build/env/bin/hue beeswax_server

Now Hue should be running on http://localhost:8000.

The configuration in development mode is desktop/conf/pseudo-distributed.ini.

Note: to start all the servers in one command (but lose the automatic reloading after source modification):

$ build/env/bin/supervisor

To run the tests:

$ build/env/bin/hue test all
$ build/env/bin/hue test specific filebrowser
$ build/env/bin/hue test specific jobbrowser.tests:test_get_path

Development Prerequisites

You'll need these library development packages and tools installed on your system:

Ubuntu:

• ant
• gcc
• g++
• libkrb5-dev
• libmysqlclient-dev
• libssl-dev
• libsasl2-dev
• libsasl2-modules-gssapi-mit
• libsqlite3-dev
• libtidy-0.99-0 (for unit tests only)
• libxml2-dev
• libxslt-dev
• mvn (from maven2 package or tarball)
• openldap-dev / libldap2-dev
• python-dev
• python-simplejson
• python-setuptools

CentOS:

• ant
• asciidoc
• cyrus-sasl-devel
• cyrus-sasl-gssapi
• gcc
• gcc-c++
• krb5-devel
• libtidy (for unit tests only)
• libxml2-devel
• libxslt-devel
• mvn (from maven2 package or tarball)
• mysql
• mysql-devel
• openldap-devel
• python-devel
• python-simplejson
• sqlite-devel

MacOS (mac port):

• liblxml
• libxml2
• libxslt
• mysql5-devel
• simplejson (easy_install)
• sqlite3

File Layout

The Hue "framework" is in desktop. /core/ contains the Web components and desktop/libs/ the API for talking to Hadoop. The installable apps live in apps/. Please place third-party dependencies in the app's ext-py/ directory.

The typical directory structure for inside an application includes:

src/

for Python/Django code

models.py urls.py views.py forms.py settings.py

conf/

for configuration (.ini) files to be installed

static/

for static HTML/js resources and help doc

templates/

for data to be put through a template engine

locales/

for localizations in multiple languages

For the URLs within your application, you should make your own urls.py which will be automatically rooted at /yourappname/ in the global namespace. See apps/about/src/about/urls.py for an example.

Main Stack

• Python 2.4 - 2.7
• Django 1.2 https://docs.djangoproject.com/en/1.2/
• Mako
• jQuery
• Bootstrap

Using and Installing Thrift

Right now, we check in the generated thrift code. To generate the code, you'll need the thrift binary version 0.7.0. Please download from http://thrift.apache.org/.

The modules using Thrift have some helper scripts like regenerate_thrift.sh for regenerating the code from the interfaces.

Profiling Hue Apps

Hue has a profiling system built in, which can be used to analyze server-side performance of applications. To enable profiling:

$ build/env/bin/hue runprofileserver

Then, access the page that you want to profile. This will create files like /tmp/useradmin.users.000072ms.2011-02-21T13:03:39.745851.prof. The format for the file names is /tmp/<app_module>.<page_url>.<time_taken>.<timestamp>.prof.

Hue uses the hotshot profiling library for instrumentation. The documentation for this library is located at: http://docs.python.org/library/hotshot.html.

You can use kcachegrind to view the profiled data graphically:

$ hotshot2calltree /tmp/xyz.prof > /tmp/xyz.trace
$ kcachegrind /tmp/xyz.trace

More generally, you can programmatically inspect a trace:

#!/usr/bin/python
import hotshot.stats
import sys

stats = hotshot.stats.load(sys.argv[1])
stats.sort_stats('cumulative', 'calls')
stats.print_stats(100)

This script takes in a .prof file, and orders function calls by the cumulative time spent in that function, followed by the number of times the function was called, and then prints out the top 100 time-wasters. For information on the other stats available, take a look at this website: http://docs.python.org/library/profile.html#pstats.Stats

Internationalization

How to update all the messages and compile them:

$ make locales

How to update and compile the messages of one app:

$ cd apps/beeswax
$ make compile-locale

How to create a new locale for an app:

$ cd $APP_ROOT/src/$APP_NAME/locale
$ $HUE_ROOT/build/env/bin/pybabel init -D django -i en_US.pot -d . -l fr

License

Apache License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0