gspreadsheet_fdw

Multicorn-based PostgreSQL foreign data wrapper for Google Spreadsheets

Makes your Google Spreadsheets appear as foreign tables in your PostgreSQL database.

Installation

You need a recent PostgreSQL install (9.1+) and you need to have installed the excellent Multicorn FDW-in-python framework into PostgreSQL.

You need the Google Data binding for python:

pip install gdata

Then just clone and install as usual:

git clone git://github.com/lincolnturner/gspreadsheet_fdw.git
cd gspreadsheet_fdw
python setup.py install

Example

See file test.sql.

Start psql and if you haven't used multicorn yet, enable it with:

CREATE EXTENSION multicorn;

Then create the gspreadsheet 'server' with:

CREATE SERVER multicorn_gspreadsheet FOREIGN DATA WRAPPER multicorn
options (
  wrapper 'gspreadsheet_fdw.GspreadsheetFdw' );

Make a Google Spreadsheet

Head over to Google Drive and make a Google Spreadsheet which conforms to the rules of a list-based feed. In essence:

• Put column names in the first row: untitled columns will not be read
• A blank row terminates the table (data below won't be read)
• Put it in the first (and only) worksheet

Get the Google API 'key' (for want of a better term), which is a 44-character string matching regexp [A-Za-z0-9_]{44}. It lives between the /spreadsheets/d/ and possible trailing /edit/blah in the URL of your Google Spreadsheet.

Create the foreign table

You can then use 'normal' DDL to create a foreign table with column names that match those in your spreadsheet. The gdata API seems to automatically downcase and remove spaces from the column headers, which is very handy. But probably best not relied on. Give your columns simple lowercase names.

CREATE FOREIGN TABLE staff_gspreadsheet (
  givenname character varying,
  surname   character varying,
  phone     character varying,
  office    character varying
) server multicorn_gspreadsheet options(
  email '[email protected]',
  password 'yourB!g$ecreT',
  key '1hoYrcViweamARnxdU1IW-Ivd8hjKHKPzkGSLbKHLeno'
);

Try querying it

You should be able to try this example, the key corresponds to a small public test table. You will of course need to change the email parameter to your Google account and the password to your Google password.

Then you should be able to execute queries against your new foreign table:

SELECT * FROM staff_gspreadsheet;

Should produce:

   givenname    | surname  | phone | office 
----------------+----------+-------+--------
 Isidior        | Rabi     | 49823 | 26.102
 Chandrasekhara | Raman    | 43803 | 26.108
 Norman         | Ramsey   | 41082 | 26.103
 Eugene         | Wigner   | 40921 | 26.114
 Ettore         | Majorana | 40010 | 26.117
(5 rows)

Qualifiers

Qualifiers are in essence SQL WHERE clauses which are sent down to the foreign data wrapper to reduce the traffic on the network. For example, executing

SELECT * FROM staff_gspreadsheet WHERE surname='Ramsey';

is translated into a Google list-feed 'query' which returns only that row. At present, anything more sophisticated than this gets mistranslated (largely due to type-casting issues, i.e. everything is a VARCHAR right now).

First thing to do in type-aware-qualifiers branch is to selectively quote only character and text values and not quote numerical values.

Removing the quals code altogether makes things work better, as without quals processing the whole foreign table is always returned but postgres then does the right thing and applies the WHERE clause once it gets its hands on the data. To be fixed soon.

Further info

Materialized views

Google Drive is always available, except when it isn't. Materialized views are a wonderful thing and highly recommended for caching your online data in PostgreSQL.

Limitations

Very minimal functionality implemented so far.

• Read-only
• All data read as PostgreSQL type character varying
• Simple queries only (=, >, < might work up to type-casting issues)

To do

• Insert, update and delete
• Sensible type awareness, at least numeric versus text
• Handle quals properly, i.e find out what pg emits and what gdata understand (Example: name LIKE 'Blog%' emits name~~'Blog%' which gdata API doesn't understand)
• Some sort of sane authentication that doesn't involve Google passwords in the data catalog!