On 03/08/2015 08:49 PM, Eli Murray wrote:
Hi all, I'm a student journalist working on a project for our student paper which lists salaries and positions for every staff member at the university. We received the data from an FOI request but the university is refusing to give us primary keys for the data. The issue we've run into is that if there are two staff members with the same name (and there are) our current web app adds their salaries together and considers them one person. Now, luckily, we can create a composite key if we combine their name column with their salary column. Unfortunately, the format of the data we have makes it more difficult than that (of course!) because some employees can hold multiple paying positions. Here's some example data: Name, Position, Salary,Total Salary, ... Jane Doe, Dean, 100.000, 148.000, ... John Locke, Custodian, 30.000, 30.000, ... Jane Doe, Academic Adviser, 48.000, 148.000, ... Jane Doe, Trainer, 46.000, 46.000, ... Basically, what we'd like to do is create a serial primary key but instead of having it increment every row, it needs to check the name and total salary columns and only increment if that person doesn't already exist. If they do exist, it should just assign the previously created number to the column.
Well the above is not going to work, because the id would not be unique across rows and therefore could not be a primary key. If I am following what you want is a staff id that identifies a particular staff member across rows and is derived from the (Name, Total Salary) combination, is that correct? If so you could use a serial column to generate a surrogate primary key for each row without worrying about the names and total salary. Then it becomes an issue of generating the staff id for unique staff members. For that I would see John McKowns answer.
However, our team is small and between us we have
very little experience working with databases and we haven't found a way to accomplish this goal yet. In fact, we may be trying to solve this in the wrong way entirely. So, to put it succinctly, how would you approach this problem? What are our options? Do we need to write a script to clean the data into separate csv tables before we import it to postgres, or is this something we can do in postgres? We'd really appreciate any help you all may be able to offer. Best! Eli Murray
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