21–30 of 91 posts
I skimmed the article for an explanation of why this is needed, what problem it solves, and didn't find one I could follow. Is the point that we want to be able to ask for visualizations directly against tables in remote SQL databases, instead of having to first pull the data into R data frames so we can run ggplot on it? But why create a new SQL-like language? We already have a package, dbplyr, that translates betwe…
my questions are less about the syntax, which i'm largely familiar with knowing both SQL and ggplot.
i'm more interested in the backend architecture. Looking at the Cargo.toml [1], I was surprised to not see a visualization dependency like D3 or Vega. Is this intentional?
I'm certainly going to take this for a spin and I think this could be incredible for agentic analytics. I'm mostly curious right now what "deployment" looks like both currently in a utopian future.
utopia is easier -- what if databases supported it directly?!? but even then I think I'd rather have databases spit out an intermediate representation (IR) that could be handed to a viz engine, similar to how vega works. or perhaps the SQL is the IR?!
another question that arises from the question of composability: how distinct would a ggplot IR be from a metrics layer spec? could i use ggsql to create an IR that I then use R's ggplot to render (or vise versa maybe?)
as for the deployment story today, I'll likely learn most by doing (with agents). My experiment will be to kick off an agent to do something like: extract this dataset to S3 using dlt [2], model it using dbt [3], then use ggsql to visualize.
p.s. @thomasp85, I was a big fan of tidygraph back in the day [4]. love how small our data world is.
[1]: https://github.com/posit-dev/ggsql/blob/main/Cargo.toml
[2]: https://github.com/dlt-hub/dlt
[3]: https://github.com/dbt-labs/dbt-fusion
[4]: https://stackoverflow.com/questions/46466351/how-to-hide-unc...
It is conceivable that this could become a duckdb extension, such that it can be used from within the duckdb CLI? That would be pretty slick.
Will this ever integrate rest of the ggplot2 dependent packages described here: https://exts.ggplot2.tidyverse.org/gallery/ in the near or distant future? Sorry if it already mentioned somewhere.
The point of this is not to superseed ggplot2 in any way, but to provide a different approach which can do a lot of the things ggplot2 can, and some that it can't. But ggplot2 will remain more powerful for a lot of tasks in many years to come I predict
I skimmed the article for an explanation of why this is needed, what problem it solves, and didn't find one I could follow. Is the point that we want to be able to ask for visualizations directly against tables in remote SQL databases, instead of having to first pull the data into R data frames so we can run ggplot on it? But why create a new SQL-like language? We already have a package, dbplyr, that translates betwe…
It seems to be for sql users who don’t know python or r.
Maybe I skim read it too fast, but I did not find any clear description in the blog post or website docs of how this relates to SQL databases I was kind of guessing that it doesn't run in a database, that it's a SQL-like syntax for a visualisation DSL handled by front end chart library. That appears to be what is described in https://ggsql.org/get_started/anatomy.html But then https://ggsql.org/faq.html has a section…
"SQL" and "databases" are different things
SQL is a declarative language for data manipulation. You can use SQL to query a database, but there's nothing special about databases. You can also write SQL to query other non-database sources like flat files, data streams, or data in a program's memory.
Conversely, you can query a database without SQL.
ok, this is definitely up my alley. color me nerd-sniped and forgive the onslaught of questions. my questions are less about the syntax, which i'm largely familiar with knowing both SQL and ggplot. i'm more interested in the backend architecture. Looking at the Cargo.toml [1], I was surprised to not see a visualization dependency like D3 or Vega. Is this intentional? I'm certainly going to take this for a spin and I…
ggsql is modular by design. It consists of various reader modules that takes care of connecting with different data backends (currently we have a DuckDB, an SQLite, and an ODBC reader), a central plot module, and various writer modules that take care of the rendering (currently only Vegalite but I plan to write my own renderer from scratch).
As for deployment I can only talk about a utopian future since this alpha-release doesn't provide much tangible in that area. The ggsql Jupyter kernel already allows you to execute ggsql queries in Jupyter and Quarto notebooks, so deployment of reports should kinda work already, though we are still looking at making it as easy as possible to move database credentials along with the deployment. I also envision deployment of single .ggsql files that result in embeddable visualisations you can reference on websites etc. Our focus in this area will be Posit Connect in the short term
I'm afraid I don't know what IR stands for - can you elaborate?
I skimmed the article for an explanation of why this is needed, what problem it solves, and didn't find one I could follow. Is the point that we want to be able to ask for visualizations directly against tables in remote SQL databases, instead of having to first pull the data into R data frames so we can run ggplot on it? But why create a new SQL-like language? We already have a package, dbplyr, that translates betwe…
In my experience, the only thing data fields share is SQL (analysts, scientists and engineers). As you said, you could do the same in R, but your project may not be written in R, or Python, but it likely uses an SQL database and some engine to access the data.
Also I've been using marimo notebooks a lot of analysis where it's so easy to write SQL cells using the background duckdb that plotting directly from SQL would be great.
And finally, I have found python APIs for plotting to be really difficult to remember/get used to. The amount of boilerplate for a simple scatterplot in matplotlib is ridiculous, even with a LLM. So a unified grammar within the unified query language would be pretty cool.
It is conceivable that this could become a duckdb extension, such that it can be used from within the duckdb CLI? That would be pretty slick.
That is conceivable, not a top priority as we want to focus on this being a great experience for every backend, but certainly something we are thinking of