I’m very guilty of all those sins. Select all, then use array map, reduce and filter in the app code. I could draw a line in my life where I discovered window functions.
If the dataset is big enough, those operations actually do make sense because they can be translated to e.g. a Hadoop job - map / reduce / filter are all operations that don't depend on the sorting of a dataset, so in theory the dataset can be sharded across many machines.
Of course, that is a solution to a problem that people wish they had. Relational databases can run multi-million row queries in seconds, and then there's BigTable / BigQuery which scales SQL to improbable scales.
Exactly. I'm talking about the "select 5000 rows, serialize them to JSON, and send them over HTTP to the browser, only to render them in a table that never changes" type code.
