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 a FileBrowser for accessing HDFS, JobSub and JobBrowser applications for submitting and viewing MapReduce jobs, a Beeswax application for executing Hive queries. 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 "core" stuff is in ``desktop/core/``, whereas 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 code models.py urls.py views.py forms.py settings.py for Django code conf/ for configuration (``.ini``) files to be installed static/ for static HTML and js resources templates/ for data to be put through a template engine docs/ for helpful notes 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 0.7 * jQuery 1.7 * Bootstrap 2 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/....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