Just a collection of tips to make working with Postgres (and other SQL-like databases) easier

# Measurement Unit

Take this case for an example, you have a product table and you want to store product information like its size and weight by adding these columns to describe such properties: width, length, height and weight.

id name width length height weight
1 ipad 10 20 0.1 0.5
2 macbook 20 30 0.5 2

So what’s the problem with the above table? We are assuming that the size props (width, height and length) are measured in cm and the weight is measured in kg. Usually, we could put this logic in application layer to make sure we convert everything to cm and kg before inserting into the database. However, it could lead to even more problems

• What will happen if a new dev join the team? How can you make sure that person will know when to convert and when not?
• What will happen if a dev using pound join the team?
• What will happen if a dev accidentally assume the value in weight is in mg?
• Sometimes, you could do a double conversion, making thing worse.
• You need to remember adding comment to every place in your code, just to remind people which measurement unit that function is using.
• Which data type to choose? Integer, of course, is not a good choice. However, working with real, double, decimal or numeric is always harder compare to int. They could cause some problems with parsing and datatype for languages/libraries like Nodejs.

Solving this issue is actually quite straight forward, you will need to

• Make it explicit: Append the measurement unit suffix to the prop name, for example widthMm, widthCm, weightKg, weightMg,…
• Use the smallest possible unit to avoid the issue with decimal number, simply use integer for everything and do the conversion if necessary on application layer. In the above example, you should stick with widthMm, lengthMm, heightMm and weightMg.

# Down Migration

Normally, Database migration tools offer 2 modes of migration: Up and Down. The Up migrations are usually the normal and happy path. The Down ones are usually used to undo the changes of the Up migrations if there are anything wrong. However, over time, your Down migrations will become rediculously unpredictable

• How often do you test the Down migrations? Usually the answer is Never. How confident are you with the Down migrations? You may fix a problem with an error Up migration by introducing a worse problem.
• How about the data? What happen if an Up migration removes some data? How can the Down migration recover the data? You can never recover the previous state correctly. Your database will end up in an inconsistent state, which is even more terrible. Trust me, Inconsistency is one of the most annoying problem when dealing with database.

So the solution is simply to delete all the down migrations from your source control. When you want to fix a problem, create another Up migration to correct your mistake and go through your normal SDLC testing workflow.