prql VS gc

> I completely attribute this to SQL being difficult or "backwards" to parse. I mean backwards in the way that in SQL you start with what you want first (the SELECT) rather than what you have and widdling it down.

> The turning point for me was to just accept SQL for what it is.

Or just write PRQL and compile it to SQL

https://github.com/PRQL/prql

Hey HN! We’ve built Pretzel, an open-source data exploration and visualization tool that runs fully in the browser and can handle large files (200 MB CSV on my 8gb MacBook air is snappy). It’s also reactive - so if, for example, you change a filter, all the data transform blocks after it re-evaluate automatically. You can try it here: https://pretzelai.github.io/ (static hosted webpage) or see a demo video here: https://www.youtube.com/watch?v=73wNEun_L7w

You can play with the demo CSV that’s pre-loaded (GitHub data of text-editor adjacent projects) or upload your own CSV/XLSX file. The tool runs fully in-browser—you can disconnect from the internet once the website loads—so feel free to use sensitive data if you like.

Here’s how it works: You upload a CSV file and then, explore your data as a series of successive data transforms and plots. For example, you might: (1) Remove some columns; (2) Apply some filters (remove nulls, remove outliers, restrict time range etc); (3) Do a pivot (i.e, a group-by but fancier); (4) Plot a chart; (5) Download the chart and the the transformed data. See screenshot: https://imgur.com/a/qO4yURI

In the UI, each transform step appears as a “Block”. You can always see the result of the full transform in a table on the right. The transform blocks are editable - for instance in the example above, you can go to step 2, change some filters and the reactivity will take care of re-computing all the cells that follow, including the charts.

We wanted Pretzel to run locally in the browser and be extremely performant on large files. So, we parse CSVs with the fastest CSV parser (uDSV: https://github.com/leeoniya/uDSV) and use DuckDB-Wasm (https://github.com/duckdb/duckdb-wasm) to do all the heavy lifting of processing the data. We also wanted to allow for chained data transformations where each new block operates on the result of the previous block. For this, we’re using PRQL (https://prql-lang.org/) since it maps 1-1 with chained data transform blocks - each block maps to a chunk of PRQL which when combined, describes the full data transform chain. (PRQL doesn’t support DuckDB’s Pivot statement though so we had to make some CTE based hacks).

There’s also an AI block: This is the only (optional) feature that requires an internet connection but we’re working on adding local model support via Ollama. For now, you can use your own OpenAI API key or use an AI server we provide (GPT4 proxy; it’s loaded with a few credits), specify a transform in plain english and get back the SQL for the transform which you can edit.

Our roadmap includes allowing API calls to create new columns; support for an SQL block with nice autocomplete features, and a Python block (using Pyodide to run Python in the browser) on the results of the data transforms, much like a jupyter notebook.

There’s two of us and we’ve only spent about a week coding this and fixing major bugs so there are still some bugs to iron out. We’d love for you to try this and to get your feedback!

> Looks like PRQL doesn't have a Go library so I guess they just really wanted something in Go?

There's some C bindings and the example in the README shows integration with Go:

https://github.com/PRQL/prql/tree/main/prqlc/bindings/prqlc-...

Can someone tell me why PRQL is better? I went here: https://github.com/PRQL/prql

It looks nice, but what's the strengths compared to SQL?

PRQL [1] is a compile-to-SQL relational querying language that puts FROM first.

[1] https://prql-lang.org

https://prql-lang.org/ might be an answer for this. As a cross-database pipelined language, it would allow RAG to be intermixed with the query, and the syntax may(?) be more reliable to generate

It may take some time for WasmGC to be usable by .NET. Based on the discussions the first version of WasmGC does not have a good way to handle a few .NET specific scenarios, and said scenarios are "post-post-mvp". [0]

My concern, of course, is that there is not much incentive for those features to be added if .NET is the only platform that needs them... at that point having a form of 'include' (to where a specific GC version can just be cached and loaded by another WASM assembly) would be more useful, despite the pain it would create.

[0] - https://github.com/WebAssembly/gc/issues/77

Yes, that's definitely true: a single GC will not be optimal for everything, or even possible. Atm interior pointers are not supported at all, for example, but they are on the roadmap for later:

https://github.com/WebAssembly/gc/blob/main/proposals/gc/Pos...

What launched now is enough WasmGC to support a big and useful set of languages (Java, Kotlin, Dart, OCaml, Scheme), but a lot more work will be required here!

GC proposal is from 2018: https://github.com/WebAssembly/proposals/issues/16 and there’s code: https://github.com/WebAssembly/gc/blob/master/proposals/gc/O...

Seems like an awefully long time for progress to be made, given all the possibilities it would unlock.

First is the size. Writing a server-side and client-side program is possible with Rust, and the resulting WASM package will be small enough. At the same time, Microsoft Blazor converts C# code to WASM, but the client delivery has to include the reduced .NET runtime, taking several megabytes for a script. The same is true for GoLang, even with an attempt to reduce the runtime delivery in TinyGo WASM. Developers want to work with their favorite languages, whether it is Java, Kotlin, Dart, C#, F#, Swift, Ruby, Python, C, C++, GoLang, or Rust. These languages produce groups of runtimes. For example, JVM and .NET have many common parts, Ruby and Python are dynamically interpreted at runtime, and all mentioned depend on automatic garbage collection. For smaller WASM packages, browser vendors can include extended runtime implementations, for example, by delivering a general garbage collector as part of WASM. Garbage collection support by WASM is currently in progress: WASM GC, .NET WASM Notes.

My understanding is that the main limitation is technical. WASM doens't do GC or the host system calling conventions and cannot interact directly with object from Javascript because of this. However, this is being worked[0] on and will be solved eventually. Even without this the performance overhead of bridging to JS is low enough that WASM frameworks can beat out React.

0: https://github.com/WebAssembly/gc/blob/main/proposals/gc/Ove...

I’ve just watched a video on YouTube from Google I/O 2023 on Flutter for the web. Kevin Moore explains that Flutter can compile to Wasm, but now that GC support has been added to the standard and WasmGC is supported in Chromium and Firefox, I’m quite intrigued.

I have found the main thread about using WebAssembly GC in C#: https://github.com/WebAssembly/gc/issues/77. If I understand it correctly, it is not possible to use the current prototype version of GC in C#.

The .net team has given their notes on it, the concern is more on the memory layout from what I remember. Though it may be possible still. The runtime would likely still ship some gc code, but only a subset for cases not supported by the wasm gc itself and a few more for interfacing with the gc service, which overall should still result on smaller payloads compared to current sizes.

I assume that's one of the parts of the work done at https://github.com/WebAssembly/gc - not happening any soon yet, but it'll eventually be done.