zetasql VS dex-lang

There are even table-valued functions.

These things are not widespread, and differ by implementation, and the way these are used by clients are copy-and-paste. Something as thoughtful as ZetaSQL https://github.com/google/zetasql does not have mechanisms for structuring (modules, packages, interfaces). SQL will not, cannot evolve into such a direction (or, anything that evolves, will not be recognizable as SQL).

Hi, I develop a BigQuery emulator ( https://github.com/goccy/bigquery-emulator ) from early 2022. It is written in Go, but can be used from bq command line tool and other language's (e.g. Python ) client SDK after installing docker image or released binary. It currently supports over 200 of the nearly 330 standard functions in BigQuery and all data types except GEOGRAPHY ( see https://github.com/goccy/go-zetasqlite#status for details ). ZetaSQL ( https://github.com/google/zetasql ) is used to parse and analyze queries.

We are using a Python client binding for ZetaSQL GRPC local service in our application to analyze statements and extract referenced tables and output columns.

If you don't want to do it yourself, there's this:

https://github.com/google/zetasql

Parsing is huge but it's amazing how small a part of the job it is. This library isn't even the half of it.

I mean the postgres parser (and semantic changes) for ZetaSQL. The zetasql parser is in a file called zetasql/parser/bison_parser.y, I strongly suspect they now have a file called something like zetasql/pgparser/bison_parser.y as well (and much more pervasive changes to support the deeper differences in the dialects).

This is the lexical structure and syntax docs for the new postgres inteface to cloud spanner:

https://cloud.google.com/spanner/docs/postgresql/lexical

And this is the zetasql lexical structure and syntax docs:

https://github.com/google/zetasql/blob/master/docs/lexical.m...

Notice that the new PG docs are an edit of the Zeta ones - evidence that my hypothesis is correct.

zetasql implements BigQuery, Spanner, and Dataflow dialects.

A really nice approach to this I've seen recently is Google's research on [Dex](https://github.com/google-research/dex-lang).

Dex

Have you tried Dex? https://github.com/google-research/dex-lang It is in a relatively early stage, but it is exploring some interesting parts of the design space.

I think [Dex](https://github.com/google-research/dex-lang) might be along the lines of what you're looking for, although its focus is on SIMD GPU-style parallelism rather than thread-level parallelism.

Dex proves indexing correctness without a full dependent type system, including loops.

See: https://github.com/google-research/dex-lang/pull/969

In case you want to see one research direction that's combining practical machine learning and functional programming, one of the authors of JAX (and the main author of its predecessor, Autograd) is writing Dex (https://github.com/google-research/dex-lang), a functional language for array processing. The compiler itself is written in Haskell. JAX is one of the most popular libraries for doing a lot of machine learning these days, along with Tensorflow and PyTorch. You might also want to see the bug in the JAX repo about adding Haskell support, for some context: https://github.com/google/jax/issues/185