DataTask
DataTask extends Rake’s dependency-based programming language to databases. This gem provides the data task, analogous to Rake’s built-in file task but extended to work with pluggable backends beyond the local filesystem.
Adapters are included for Sqlite3, PostgreSQL, and Greenplum.
Installation
Add this line to your application’s Gemfile:
gem 'data_task'
And then execute:
$ bundle
Or install it yourself as:
$ gem install data_task
Usage
To write your first data task, connect to your database by instantiating an adapter:
postgres = Rake::DataTask::Postgres.new(
'host' => 'localhost',
'port' => 5432,
'database' => 'example',
'username' => 'postgres'
)
Then use this adapter instance as the target for a data task:
desc "Load a data file into PostgreSQL for analysis."
data postgres['raw'] => 'raw.txt' do
# Add loading logic here
end
Rake will run this task if and only if (a) the table ‘raw’ is does not exist yet, or (b) the table ‘raw’ exists but has a timestamp earlier than the file ‘raw.txt’. Since database tables now have timestamps associated with them, they can serve as targets or as dependencies in data tasks.
Here’s a runnable example Rakefile:
``` require ‘rake’ require ‘data_task’
connect to the database
postgres = Rake::DataTask::Postgres.new( ‘host’ => ‘localhost’, ‘port’ => 5432, ‘database’ => ‘example’, ‘username’ => ‘postgres’ )
mark raw.txt as a potential dependency
file ‘raw.txt’
define a loader for the postgres table ‘raw’, dependent on raw.txt
desc “Load a data file into PostgreSQL for analysis.” data postgres[‘raw’] => ‘raw.txt’ do postgres.create_table ‘raw’, nil, ‘(var1 text)’ postgres.execute “copy raw.txt to raw” end ```
To run it:
- paste the example into a file named ‘Rakefile’,
- make sure the PostgreSQL configuration matches your server,
- open a terminal and run the commands below:
$ echo "v1" > raw.txt
$ rake 'raw'
The contents of raw.txt should be in your table ‘raw’ on PostgreSQL. Running the rake command a second time will result in no operations as long as raw.txt hasn’t changed. With big data files, this can be a big time-saver.
Contributing
- Fork it ( https://github.com/shahin/data_task/fork )
- Create your feature branch (
git checkout -b my-new-feature) - Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-feature) - Create a new Pull Request