Thanks @natac13, but I’m still not sure I get it. In my mind, qualitative means “this fruit bowl contains apples, pears and bananas, so you should put the bananas somewhere else because they give off ethylene which can cause the other fruit to over-ripen”, whereas quantitative means “this fruit bowl contains 70% apples, 20% bananas and 10% pears, but bananas are consumed twice as fast as apples so you should buy more bananas”.
Are you suggesting that I should forget about the difference between the two?
Your point 1 - by “important”, do you mean the operations without which the application cannot provide any business value? Now I’ve seen the detailed answer for this lab, it doesn’t seem to take this factor into account.
And your point 2 - the detailed answer does take frequency of the operations into account (both average and peak), but it also considers whether the operation is real-time, whether it requires low latency and the size of the data. I’m unable to reverse engineer from the detailed answer a set of rules to decide in which order all these factors should be considered in order to determine the overall importance of an operation.
In the M201 performance course, when looking at how to optimise indexes, we were given the rule “equality, sort, range”, i.e. to create an index which is optimised for a particular query, index first on the fields which the query tests for equality, then on the fields which the query uses to sort the results, and finally on the fields which the query tests for things like greater than, less than or $in. This is a nice, simple, easy to remember rule which has served me well when creating indexes.
Am I over-simplifying things by expecting a similar rule for which factors to take into account and in what order, when deciding which are the most important operations?
