51–60 of 124 posts
I really like duckdb's notebooks for exploration and this feature makes them even more awesome, but the fact that I can't share, export or commit them into a git repo feels extremely limiting. It's neat-ish that it dodfoods and store them in a duckdb database. It even seems to stores historical versions, but I can't really do anything with it..
Please finally add q language with proper integration to your tables so that our precious q-SQL is available there. Stop reinventing the wheel, let's at least catch up to the previous generation (in terms of convenience). Make the final step.
What is q-SQL?
It would be even better if SQL had pipe syntax. SQL is amazing, but its ordering isn’t intuitive, and only CTEs provide a reliable way to preview intermediate results. With pipes, each step could clearly show intermediate outputs. Example: FROM orders |> WHERE order_date >= '2024-01-01' |> AGGREGATE SUM(order_amount) AS total_spent GROUP BY customer_id |> WHERE total_spent > 1000 |> INNER JOIN customers USING(custome…
https://cloud.google.com/blog/products/data-analytics/simpli...
It's pretty neat:
FROM mydataset.Produce
|> WHERE sales > 0
|> AGGREGATE SUM(sales) AS total_sales, COUNT(\*) AS num_sales
GROUP BY item;
It would be even better if SQL had pipe syntax. SQL is amazing, but its ordering isn’t intuitive, and only CTEs provide a reliable way to preview intermediate results. With pipes, each step could clearly show intermediate outputs. Example: FROM orders |> WHERE order_date >= '2024-01-01' |> AGGREGATE SUM(order_amount) AS total_spent GROUP BY customer_id |> WHERE total_spent > 1000 |> INNER JOIN customers USING(custome…
Earlier quoted context omitted.
The blog specifically says that they're getting the SQL AST so presumably they would not execute something like a DELETE.
Correct. We only enable fast previews for SELECT statements, which is the actual hard problem. This said, at some point we're likely to also add support for previewing a CTAS before you actually run it.
It would be even better if SQL had pipe syntax. SQL is amazing, but its ordering isn’t intuitive, and only CTEs provide a reliable way to preview intermediate results. With pipes, each step could clearly show intermediate outputs. Example: FROM orders |> WHERE order_date >= '2024-01-01' |> AGGREGATE SUM(order_amount) AS total_spent GROUP BY customer_id |> WHERE total_spent > 1000 |> INNER JOIN customers USING(custome…
This is one of the reasons I'm excited about DuckDB's upcoming [2]PEG parser. If they can pull it off, we could have alternative dialects that run on DuckDB.
[1] https://www.malloydata.dev/ [2] https://duckdb.org/2024/11/22/runtime-extensible-parsers.htm...
It would be even better if SQL had pipe syntax. SQL is amazing, but its ordering isn’t intuitive, and only CTEs provide a reliable way to preview intermediate results. With pipes, each step could clearly show intermediate outputs. Example: FROM orders |> WHERE order_date >= '2024-01-01' |> AGGREGATE SUM(order_amount) AS total_spent GROUP BY customer_id |> WHERE total_spent > 1000 |> INNER JOIN customers USING(custome…
Google SQL has it now: https://cloud.google.com/blog/products/data-analytics/simpli... It's pretty neat: FROM mydataset.Produce |> WHERE sales > 0 |> AGGREGATE SUM(sales) AS total_sales, COUNT(\*) AS num_sales GROUP BY item; Edit: formatting
FROM table SELECT foo, bar WHERE zoo=“goo”
Earlier quoted context omitted.
It is already available in the local DuckDB UI! Let us know what you think! -Customer software engineer at MotherDuck
Does local DuckDB UI work without an internet connection?
Kinda like regex101, draw.io or excalidraw.
I hope this doesn't work with DELETE queries.
Maybe in the next version they could also implement support for DROP, with autocorrect for the nearest (not yet dropped) table name.
I just watched the author of this feature and blog post give a talk at the DataCouncil conference in Oakland, and it is obvious what a huge amount of craft, ingenuity, and care went into building it. Congratulations to Hamilton and the MotherDuck team for an awesome launch!