Re: automated 'discovery' of a table : potential primary key, columns functional dependencies ...

On 11/22/19 2:05 PM, Rémi Cura wrote:
> Hello dear List,
> I'm currently wondering about how to streamline the normalization of a 
> new table.
> 
> I often have to import messy CSV files into the database, and making 
> clean normalized version of these takes me a lot of time (think dozens 
> of columns and millions of rows).

To me messy means the information to do the below is not available. 
Personally I think you best bet is to get the data into tables and then 
use visualization tools to help you determine the below. My guess is 
there will be a lot of data cleaning going on before you can get to a 
well ordered table layout.

> 
> I wrote some code to automatically import a CSV file and infer the type 
> of each column.
> Now I'd like to quickly get an idea of
>   - what would be the most likely primary key
>   - what are the functional dependencies between the columns
> 
> The goal is **not** to automate the modelling process,
> but rather to automate the tedious phase of information collection
> that is necessary for the DBA to make a good model.
> 
> If this goes well, I'd like to automate further tedious stuff (like 
> splitting a table into several ones with appropriate foreign keys / 
> constraints)
> 
> I'd be glad to have some feedback / pointers to tools in plpgsql or even 
> plpython.
> 
> Thank you very much
> Remi
> 
> 


-- 
Adrian Klaver
[email protected]