5 ms·

Amongst many other things, the README tells me that `Malloy is immediately understandable by SQL users, and far easier to use and learn`. Having just looked at

Amongst many other things, the README tells me that `Malloy is immediately understandable by SQL users, and far easier to use and learn`. Having just looked at this code sample, I really don't agree with that README.

civilized 5y ago
That's why they tell rather than show.
wruza 5y ago
Which part of it you couldn’t understand?
- fphhotchips 5y ago
  I'll bite. What is that code example actually returning? I don't have a clue what fields I expect to get back from that.
  - wruza 5y ago
    I’d expect [{ flight_date: carrier: daily_flight_count: per_plane_data: [ { tail_num: plane_flight_count: flight_legs: [ And so on.
  - ltabb 5y ago
    Scroll to the bottom of the page. It shows the returned JSON https://looker-open-source.github.io/malloy/documentation/patterns/sessionize.html https://looker-open-source.github.io/malloy/documentation/pa... Here is the SQL we generate. https://gist.github.com/lloydtabb/8c144d2dac978dda9bf3ec4d6bbd2015 https://gist.github.com/lloydtabb/8c144d2dac978dda9bf3ec4d6b...
- da_chicken 5y ago
  What's nest actually doing? Is it an inner join/lateral/apply? An outer join/lateral/apply? A correlated subquery? If so, what's the key? It doesn't look like it has a key, so it's equivalent to a cross join? That's hardly ever useful. Even this example query feels like it would just be better as 3 queries if it's just a cross join. I don't want every row to have a list of the exact same 20 records on it. How does aggregate know what function to use? The examples on the aggregate page actually list aggregate functions, but everywhere else it's just... magically decided? It supports TOP or LIMIT, but where's the windowing? Where's OFFSET 100 ROWS FETCH NEXT 25 ROWS ONLY for page 5? What the heck does "order by: 2" mean? Even if it's an ordinal position, that's not a great example. Yes, SQL technically allows you to use ordinal positioning of columns in the ORDER BY, but it's horrible practice to use that because it's difficult to maintain. There's no way to tell what the original intent was, and the output columns change all the time when queries are reused. My real question, however, is: "How is this actually easier?". Yes, sure, using symbols instead of English words is shorter, and a lot of programmers mistake a lower character count for being easier. However, it's not actually easier. It's just a bit less typing.
  - ltabb 5y ago
    > 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.

civilized 5y ago

That's why they tell rather than show.

wruza 5y ago

Which part of it you couldn’t understand?

fphhotchips 5y ago
I'll bite. What is that code example actually returning? I don't have a clue what fields I expect to get back from that.
- wruza 5y ago
  I’d expect [{ flight_date: carrier: daily_flight_count: per_plane_data: [ { tail_num: plane_flight_count: flight_legs: [ And so on.
- ltabb 5y ago
  Scroll to the bottom of the page. It shows the returned JSON https://looker-open-source.github.io/malloy/documentation/patterns/sessionize.html https://looker-open-source.github.io/malloy/documentation/pa... Here is the SQL we generate. https://gist.github.com/lloydtabb/8c144d2dac978dda9bf3ec4d6bbd2015 https://gist.github.com/lloydtabb/8c144d2dac978dda9bf3ec4d6b...
da_chicken 5y ago
What's nest actually doing? Is it an inner join/lateral/apply? An outer join/lateral/apply? A correlated subquery? If so, what's the key? It doesn't look like it has a key, so it's equivalent to a cross join? That's hardly ever useful. Even this example query feels like it would just be better as 3 queries if it's just a cross join. I don't want every row to have a list of the exact same 20 records on it. How does aggregate know what function to use? The examples on the aggregate page actually list aggregate functions, but everywhere else it's just... magically decided? It supports TOP or LIMIT, but where's the windowing? Where's OFFSET 100 ROWS FETCH NEXT 25 ROWS ONLY for page 5? What the heck does "order by: 2" mean? Even if it's an ordinal position, that's not a great example. Yes, SQL technically allows you to use ordinal positioning of columns in the ORDER BY, but it's horrible practice to use that because it's difficult to maintain. There's no way to tell what the original intent was, and the output columns change all the time when queries are reused. My real question, however, is: "How is this actually easier?". Yes, sure, using symbols instead of English words is shorter, and a lot of programmers mistake a lower character count for being easier. However, it's not actually easier. It's just a bit less typing.
- ltabb 5y ago
  > 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.