> What's nest actually doing? 1) Nesting builds nested results (like GraphQL). This is particularly hard to do in SQL but is allows very large complex data se

> What's nest actually doing? 1) Nesting builds nested results (like GraphQL). This is particularly hard to do in SQL but is allows very large complex data sets to be returned in a single query. https://looker-open-source.github.io/malloy/documentation/language/nesting.html https://looker-open-source.github.io/malloy/documentation/la... For example the dashboard on the page below is a single SQL query: https://looker-open-source.github.io/malloy/documentation/examples/iowa/step6.html https://looker-open-source.github.io/malloy/documentation/ex... > How does aggregate know what function to use? You can pre-define calculations with 'measure:' or decalre them explicitly in a query. > where's the windowing It's missing with a bunch of other things (like union for example). Its coming of course. The goal is that everything represent able in SQL is represent able in Malloy. > heck does "order by: 2" mean Same thing as it does in SQL. We try and have reasonable defaults. https://looker-open-source.github.io/malloy/documentation/language/order_by.html https://looker-open-source.github.io/malloy/documentation/la... > "How is this actually easier?" The goal here is to be able to create data models that are re-usable and compose-able and verifiable. Yeah, there is a learning curve as there is with anything powerful. There are many things expressible in Malloy that cannot be easily expressed in SQL.