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Posts Tagged ‘Company: Facebook’

It’s Phab! That makes your life easier

Wednesday, August 13th, 2014 | Posted in Cloud computing

We have been using plenty of different tools for tracking bugs/product management/project management/to do lists/code review; such as ClearCase, ClearQuest, Bugzilla, Github, Asana, Pivotal Tracker, Google Drive etc. We found Phabricator as a “Too Good To Be True” software engineering web application platform originally developed at Facebook. It has code review, wiki, repository browsing,tickets and a lot more to make Phab more fabulous.

Phabricator is an open source collaboration of web applications which help software companies to build better software. It is a suite of applications. Following are the most important tools in phabricator :
Maniphest – Bug tracker/task management tracker
Diffusion- source code browser
Differential – code review tool that allows developers to easily submit reviews to one another via command line tool when they check in code using Git or Subversion
Phriction – wiki tool

How to setup and configure the code review and project management tool – Phabricator

Installation

Server – 4GB Digital ocean droplet
OS – Ubuntu 14.04

1. Install dependencies

apt-get install mysql-server apache2 dpkg-dev php5 php5-mysql php5-gd php5-dev php5-curl php-apc php5-cli php5-json

2. Get code

#cd /var/www/codereview

git clone https://github.com/phacility/libphutil.git

git clone https://github.com/phacility/arcanist.git

git clone https://github.com/phacility/arcanist.git

3. Configure virtual host entry

#add below lines

#######################################################################

DocumentRoot /var/www/codereview/webroot
RewriteEngine on
RewriteRule ^/rsrc/(.*) – [L,QSA]
RewriteRule ^/favicon.ico – [L,QSA]
RewriteRule ^(.*)$ /index.php?__path__=$1 [B,L,QSA]
Order allow,deny
allow from all
#######################################################################
4. Enable the virtual host entry for phabricator.

# a2ensite phabricator.conf
# service apache2 reload

5. Configure the MySQL database configuration for phabricator

– create database
# /var/www/codereview/phabricator/bin/config set mysql.user mysql_username
# /var/www/codereview/phabricator/bin/config get mysql.pass mysql_password
# /var/www/codereview/phabricator/bin/config get mysql.host mysql_host
# /var/www/codereview/phabricator/bin/config storage upgrade
-tweak mysql

Open /etc/mysql/my.cnf and add the following line under [mysqld] section:

sql-mode = STRICT_ALL_TABLES

#service mysql restart

Set the Base URI of Phabricator install

# /var/www/codereview/phabricator/bin/config set phabricator.base-uri

(eg: phabricator.your-domain.com)

Configure Outbound Email – External SMTP (Google Apps)

Set the following configuration keys using /var/www/codereview/phabricator/bin/config set value

– metamta.mail-adapter -> PhabricatorMailImplementationPHPMailerAdapter
– phpmailer.mailer -> smtp
– phpmailer.smtp-host -> smtp.gmail.com
– phpmailer.smtp-port -> 465
– phpmailer.smtp-user -> Your Google apps mail id
– phpmailer.smtp-password -> set to your password used for authentication
– phpmailer.smtp-protocol -> ssl

Start the phabricator daemons

You can start all the phabricator deamons using the script
# /var/www/codereview/phabricator/bin/phd start
To start daemons at the boot time, add this entry to the file /etc/rc.local

/var/www/codereview/phabricator/bin/phd start

Diffusion repository hosting with git

1. Install git

#apt-get install git

2. Create a local repository directory:

#mkdir -p /data/repo

3. Edit the repository.default-local-path key to the new local repository directory.

Go to the Config -> Repositories -> repository.default-local-path

4. Configure System user accounts

Phabricator uses as many as three user accounts. These are system user accounts on the machine Phabricator runs on, not Phabricator user accounts.

* daemon-user – The user the daemons run as

We will configure the root user to run the daemons

* www-user – The user the web server run as

We will use www-data to be the web user

* vcs-user – The user that users will connect over SSH as

We will configure git user to the vcs-user

To enable SSH access to repositories, edit /etc/sudoers file using visudo to contain:

#includedir /etc/sudoers.d
git ALL=(root) SETENV: NOPASSWD: /usr/bin/git-upload-pack, /usr/bin/git-receive-pack, /usr/bin/git

Since we are going to enable SSH access to the repository, ensure the following holds good.

– Open /etc/shadow and find the line for vcs-user, git.

The second field (which is the password field) must not be set to !!. This value will prevent login. If it is set to !!, edit it and set it to NP (“no password”) instead.

– Open /etc/passwd and find the line for the vcs-user, git.
The last field (which is the login shell) must be set to a real shell. If it is set to something like /bin/false, then sshd will not be able to execute commands. Instead, you should set it to a real shell, like /bin/sh.

– Use phd.user as our daemon user;
# /var/www/phab/phabricator/bin/config phd.user root
# /var/www/phab/phabricator/bin/config set diffusion.ssh-user git

5. Configuring SSH

We will move the normal sshd daemon to another port, say 222. We will use this port to get a normal login shell. We will run highly restrictive sshd on port 22 managed by Phabricator.

Move Normal SSHD

– make a backup of sshd_config before making any changes.

#cp /etc/ssh/sshd_config /etc/ssh/sshd_config.backup

– Update /etc/ssh/sshd_config, change the port to some othert port like 222.

Port 222

– Restart sshd and verify that you are able to connect to the new port

ssh -p 222 user@host

Configure and start Phabricator SSHD

We now configure and start a second SSHD instance which will run on port 22. This instance will use special locked down configuration that uses Phabricator to handle the authentication and command execution.

– Create a phabricator-ssh-hook.sh file

– Create a sshd_phabricator config file

– Start a copy of sshd using the new configuration

Create phabricator-ssh-hook.sh: Copy the template in phabricator/resources/sshd/ phabricator-ssh-hook.sh to somewhere like /usr/lib/phabricator-ssh-hook.sh and edit it to have the correct settings

##############################################################

#!/bin/sh

# NOTE: Replace this with the username that you expect users to connect with.
VCSUSER=”git”

# NOTE: Replace this with the path to your Phabricator directory.
ROOT=”/var/www/codereview/phabricator”

if [ “$1” != “$VCSUSER” ];
then
exit 1
fi

exec “$ROOT/bin/ssh-auth” $@
##############################################################

Make it owned by root and restrict editing;

#sudo chown root /usr/lib/phabricator-ssh-hook.sh
#chmod 755 /usr/lib/phabricator-ssh-hook.sh

Create sshd_config for Phabricator: Copy the template in /phabricator/sshd/sshd_config.phabricator.example to somewhere like /etc/ssh/sshd_config.phabricator

Start Phabricator SSHD

#sudo /usr/sbin/sshd -f /etc/ssh/sshd_config.phabricator

Note:-
Add this entry to the /etc/rc.local to start the daemon on startup.

If you did everything correctly, you should be able to run this;

#echo {} | ssh git@phabricator.your-company.com conduit conduit.ping

and get a response like this;

{“result”:”phab-server”,”error_code”:null,”error_info”:null}

You should now be able to access your instance over ssh on port 222 for normal login and administrative purposes. Phabricator SSHD runs on port 22 to handle authentication and command execution.

6. To create a git repository

Go to Diffusion -> New Repository -> Create a New Hosted Repository

Upgrade Phabricator

Since phabricator is under development, you should update frequently. To update phabricator:

– Stop the web server
– Run git pull in libphutil/, arcanist/, and phabricator.
– Run phabricator/bin/storage upgrade.
– Restart the web server.
Also you can use a script similar to this one to automate the process:
http://www.phabricator.com/rsrc/install/update_phabricator.sh

Mapreduce using Hadoop + pig/hive on AWS EC2 hadoop cluster

Tuesday, July 26th, 2011 | Posted in Amazon EC2, Amazon Web Services, Cloud computing

This article discuss about running mapreduce jobs using the apache tools called pig and hive.Before we can process the data we need to upload the files to be processed to HDFS/S3.  We recommend uploading to hdfs and keeping the important files in s3 for backup is a better practice. s3 is easily accessible from commandline using tools like s3cmd. HDFS is a failover cluster filesystem which provides enough protection to your data over instance failures.

Mapreduce

MapReduce is a programming model and an associated implementation for processing and generating large data sets. We can specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key.

The main steps hadoop takes to run a job are

  1. The client, which submits the MapReduce job.
  2. The jobtracker, which coordinates the job run. The jobtracker is a Java application whose main class is JobTracker.
  3. The tasktrackers, which run the tasks that the job has been split into. Tasktrackers are Java applications whose main class is TaskTracker.
  4. The distributed filesystem (normally HDFS), which is used for sharing job files between the other entities.

Hadoop Map/Reduce is very powerful, but

o   Requires a Java Programmer.

o   Harder to write and also time consuming.

o   Difficult to update frequently.

A solution is to Run jobs using pig(Piglatin)/hive(HiveQL).

Pig

• An engine for executing programs on top of Hadoop

• It provides a language, Pig Latin, to specify these programs

Pig has Two main parts:

– A high level language to express data analysis

– Compiler to generate mapreduce programs (which can run on top of Hadoop)

Pig Latin is the name of the language with which Pig scripts are written. Pig also provides an interactive shell for executing simple commands, called Grunt. Pig Latin is a high level language. Pig runs on top of Hadoop. It collect the data for processing from Hadoop HDFS filesystem and Submit the jobs to the Hadoop mapreduce system.

A sample mapreduce job (like a Hello World program) using pig is given below

It is assumed that you are on one of the machines which is a part of a hadoop cluster having NameNode/DataNode as well as JobTracker/TaskTracker setup.

We will be executing piglatin commands using grunt shell. Switch to hadoop user first .

Consider we have a file ‘users’ on our local filesystem which contain data to be processed.First we have to upload it to hdfs. Then

# pig -x mapreduce

this command will take you to grunt shell. Pig Latin statements are generally

organized in the following manner:

A LOAD statement reads data from the file system.Then we process the data.And writes output to the file system using STORE statement. A DUMP statement displays output to the screen.

grunt> Users = load ‘users’ as (name, age);

grunt> Fltrd = filter Users by age >= 18 and age <= 25;

grunt> Pages = load ‘pages’ as (user, url);

grunt> Jnd = join Fltrd by name, Pages by user;

grunt> Grpd = group Jnd by url;

grunt> Smmd = foreach Grpd generate group, COUNT(Jnd) as clicks;

grunt> Srtd = order Smmd by clicks desc;

grunt> Top5 = limit Srtd 5;

grunt> store Top5 into ‘top5sites’;

We can also view the progress of the job through the web interface http://<ipaddress of jobtracker machine>:50030.

Tools like PigPen (an eclipse plugin) are available  that helps us create pig-scripts, test them using the example generator and then submit them to a hadoop cluster.

There is another tool called oozie – Oozie is a server based Workflow Engine specialized in running workflow jobs with actions that run Hadoop Map/Reduce and Pig jobs.

Pig tasks can be modeled as a workflow in oozie. These are deployed to the Oozie server using a command line utility. Once deployed, the workflows can be started and manipulated as necessary using the same utility. Once the workflow is started Oozie will run through each flow.. The web console for Oozie server can be used to monitor the progress of various workflow jobs being managed by the server.

Hive

 

Pig, was causing some slowdowns at Facebook company as it needed training to bring business intelligence users up to speed. So the development team decided to write Hive which has an SQL like syntax.

Apache Hive is a data warehouse infrastructure built on top of Apache Hadoop. It provides tools for querying and analysis of large data sets stored in Hadoop files. Hive defines a simple SQL-like query language, called HiveQL, that enables users familiar with SQL to query the data. Also it allows custom mappers and reducers to perform more sophisticated analysis that may not be supported by the built-in capabilities of the language.

Some of the queries in HiveQL are given below, which is very similar to the SQL.

# show tables;

# describe <tablename>;

# SELECT * FROM <tablename> LIMIT 10;

#  CREATE TABLE table_name

#  ALTER TABLE table_name RENAME TO new_table_name

#  DROP TABLE table_name

NoSQL databases like Cassandra provide support for hadoop. Cassandra supports running Hadoop MapReduce jobs against the Cassandra cluster. With proper cluster configuration, MapReduce jobs can retrieve data from Cassandra and then output results either back into Cassandra, or into a file system.