Flux

Flux is a system to programmaticaly author, schedule and monitor data pipelines.

Use the Flux library to define workflows as directed acyclic graphs (DAGs) of data related tasks. Command line utilities make it easy to run parts of workflows interactively, and commiting pipelines into production is all it takes for the master scheduler to run the pipelines with the schedule and dependencies specified.

The Flux UI make it easy to visualize pipelines running in production, monitor progress and pinpoint and troubleshoot issues when needed.

Screenshots

Tree View

Graph View

Gantt Chart

Principles

• Dynamic: Flux has intrinsec support for dynamic pipeline generation: you can write pipelines, as well as writing code that defines pipeline.
• Interactivity: the libraries are intuitive so that writting / testing and monitoring pipelines from a shell (or an iPython Notebook) should just flow
• Extensible: easily define your own operators, executors and extend the library so that it fits the level of abstraction that suits your environment
• Elegant: make your commands dynamic with the power of the Jinja templating engine

Concepts

Operators

Operators allows to generate a certain type of task on the graph. There are 3 main type of operators:

• Sensor: Waits for events to happen, it could be a file appearing in HDFS, the existance of a Hive partition or for an arbitrary MySQL query to return a row.
• Remote Execution: Trigger an operation in a remote system, this could be a HQL statement in Hive, a Pig script, a map reduce job, a stored procedure in Oracle or a Bash script to run.
• Data transfers: Move data from a system to another. Push data from Hive to MySQL, from a local file to HDFS, from Postgres to Oracle, or anything of that nature.

Tasks

A task represent the instantiation of an operator and becomes a node in the directed acyclic graph (DAG). The instantiation defines specific values when calling the abstract operator. A task could be waiting for a specific partition in Hive, or triggerring a specific DML statement in Oracle.

Task instances

A task instance represents a task run, for a specific point in time. While the task defines a start datetime and a schedule (say every hour or every day), a task instance represents a specific run of a task. A task instance will have a status of either "started", "retrying", "failed" or "success"

Installation

Debian packages

sudo apt-get install virtualenv python-dev
sudo apt-get install libmysqlclient-dev mysql-server
sudo apt-get g++

Required environment variable, add this to your .bashrc

export FLUX_HOME=~/Flux

Create a python virtualenv

virtualenv env # creates the environment
source init.sh # activates the environment

Use pip to install the python packages required by Flux

pip install -r requirements.txt

Setup the metdata database

Here are steps to get started using MySQL as a backend for the metadata database, though any backend supported by SqlAlquemy should work just fine.

$ mysql -u root -p 
mysql> CREATE DATABASE flux;
CREATE USER 'flux'@'localhost' IDENTIFIED BY 'flux';
GRANT ALL PRIVILEGES ON flux.* TO 'flux'@'localhost';

Start the web server

./flux webserver
# Now browse to http://localhost:8080