Checker Framework VS dolt

It is interesting! I experimented with creating a bad borrow checker for Java using annotations from

https://checkerframework.org/

It supports some level of substructural types using must-call annotations,

https://checkerframework.org/manual/#resource-leak-checker

Lombok is not a compiler extension. Compiler extensions, aka annotation processors, are offered only specific capabilities that ensure that they preserve the Java language specification. Particularly, code that compiles successfully with an extension also compiles without it (perhaps requiring other classes to be available) and it compiles down to the same bytecode. Annotation processors are used to implement pluggable type systems (e.g. https://checkerframework.org) or to generate other classes (e.g. https://immutables.github.io/).

Unlike compiler extensions, Lombok compiles source files that do not conform to the Java language specification. Lombok is an alternative Java Platform language, like Clojure or Kotlin or Scala, except that it's a superset of the Java language. However, rather than forking `javac` source code and modifying it to compile Lombok source files, the Lombok compiler modifies `javac`'s operation by hacking into its internals and modifying them as it runs to compile Lombok sources rather than Java sources.

Having alternative Java Platform languages is perfectly fine. The problem with Lombok is that it doesn't present itself as such but as a library or a compiler extension even though it violates the Java language specification in ways that compiler extensions are forbidden from doing.

And then I found (thanks Oracle), https://checkerframework.org/ zomg, this thing is awesome. Pluggable Type Systems!

Java should adopt something like the Checker Framework Nullness Checker in its first-party tooling.

https://github.com/typetools/checker-framework

And modern (real, non-android) Java via project amber and so on has gone more and more quasi functional with its immutability and sealed and record types for effective sum types, as well as its pretty cool type-use annotation extensible static type checks.

Checkerframework - a really academic take, and as one might expect from such a thing, backed by tons of papers and analysed to perfection. Specifically, this is the only framework I'm aware of that realizes nullity is a little more complicated than just a boolean yes-or-no; just like generics actually have 4 flavours for any given type: List, List, List, and List are all 4 important and unique, and nullity is no different. Specifically, it can occur that you want to write a method that ought to accept both lists of nullable strings as well as list of nonnull strings, and needs to 'convey' this nullity again on its output. You can either attempt to lift along the existing generics system in java which I think is your intent, but it's not actually all that easy to do this. After all, T extends @Nullable Number super @NonNull Number, or whatnot, isn't legal java. So you.. really just can't do that. Checker Framework solves this problem by introducing the @PolyNull annotation, which still isn't perfect but covers almost all real world use cases you can think of. I'm missing any acknowledgement in your documentation. An oversight, or, something you hadn't thought of yet? You're in good company: Both eclipse and intellij's engineers, when I asked them about it, just hadn't realized it was a thing. Point is: If you think the primary problem with e.g. eclipse's and intellij's take is that they lack academic rigour - checkerframework has you beat.

NullAway or the Checker Framework should greatly help eliminate the issue. Also, when Java gets value types you should be able to define your own non nullable value types and use them safely.

There are a lot of existing libraries for type checking modules. For example the Checker Framework created by University of Washington. This framework includes a NonNull module, as well as regular expression module and a mutex lock module. See this for more information.

Hi, this is my project :)

For us this package is most important as the query engine that powers Dolt:

https://github.com/dolthub/dolt

We aren't the original authors but have contributed the vast majority of its code at this point. Here's the origin story if you're interested:

https://www.dolthub.com/blog/2020-05-04-adopting-go-mysql-se...

It's a pretty good default stance, yeah.

We have been trying to convince people to use our new database [1] for several years and it's an uphill battle, because Postgres really is the best choice for most people. They really have to need our unique feature (version control) to even consider it over Postgres, and I don't blame them.

[1] https://github.com/dolthub/dolt

We implemented a query optimizer with a flexible intermediate representation in pure Go:

https://github.com/dolthub/go-mysql-server

Getting the IR correct so that it's both easy to use and flexible enough to be useful is a really interesting design challenge. Our primary abstraction in the query plan is called a Node, and is way more general than the IR type described in the article from OP. This has probably hurt us: we only recently separated the responsibility to fetch rows into its own part of the runtime, out of the IR -- originally row fetching was coupled to the Node type directly.

This is also the query engine that Dolt uses:

https://github.com/dolthub/dolt

But it has a plug-in architecture, so you can use the engine on any data source that implements a handful of Go interface.

Just want to point out that we're announcing development on the project. It's absolutely not ready for mainstream use yet! We have Dolt (https://github.com/dolthub/dolt) which is production-ready and widely in use, but it uses MySQL's syntax and wire protocol. We are building the Dolt equivalent for PostgreSQL, which is DoltgreSQL, but it's only pre-alpha.

Interesting that branching is now better supported and almost free. I wonder if merging can be simplified or whether it already is as simple and as fast as it can be?

I guess I am inspired by Dolt’s ability to branch and merge: https://github.com/dolthub/dolt

#. SQLite WAL mode

From https://www.sqlite.org/isolation.html https://news.ycombinator.com/item?id=32247085 :

> [sqlite] WAL mode permits simultaneous readers and writers. It can do this because changes do not overwrite the original database file, but rather go into the separate write-ahead log file. That means that readers can continue to read the old, original, unaltered content from the original database file at the same time that the writer is appending to the write-ahead log

#. superfly/litefs: aFUSE-based file system for replicating SQLite https://github.com/superfly/litefs

#. sqldiff: https://www.sqlite.org/sqldiff.html https://news.ycombinator.com/item?id=31265005

#. dolthub/dolt: https://github.com/dolthub/dolt

> Dolt can be set up as a replica of your existing MySQL or MariaDB database using standard MySQL binlog replication. Every write becomes a Dolt commit. This is a great way to get the version control benefits of Dolt and keep an existing MySQL or MariaDB database.

#. pganalyze/libpg_query: https://github.com/pganalyze/libpg_query :

> C library for accessing the PostgreSQL parser outside of the server environment

#. Ibis + Substrait [ + DuckDB ]

> ibis strives to provide a consistent interface for interacting with a multitude of different analytical execution engines, most of which (but not all) speak some dialect of SQL.

> Today, Ibis accomplishes this with a lot of help from `sqlalchemy` and `sqlglot` to handle differences in dialect, or we interact directly with available Python bindings (for instance with the pandas, datafusion, and polars backends).

> [...] `Substrait` is a new cross-language serialization format for communicating (among other things) query plans. It's still in its early days, but there is already nascent support for Substrait in Apache Arrow, DuckDB, and Velox.

#. benbjohnson/postlite: https://github.com/benbjohnson/postlite

> postlite is a network proxy to allow access to remote SQLite databases over the Postgres wire protocol. This allows GUI tools to be used on remote SQLite databases which can make administration easier.

> The proxy works by translating Postgres frontend wire messages into SQLite transactions and converting results back into Postgres response wire messages. Many Postgres clients also inspect the pg_catalog to determine system information so Postlite mirrors this catalog by using an attached in-memory database with virtual tables. The proxy also performs minor rewriting on these system queries to convert them to usable SQLite syntax.

> Note: This software is in alpha. Please report bugs. Postlite doesn't alter your database unless you issue INSERT, UPDATE, DELETE commands so it's probably safe. If anything, the Postlite process may die but it shouldn't affect your database.

#. > "Hosting SQLite Databases on GitHub Pages" (2021) re: sql.js-httpvfs, DuckDB https://news.ycombinator.com/item?id=28021766

#. awesome-db-tools https://github.com/mgramin/awesome-db-tools

If you are just looking for data versioning there is Dolt:

https://github.com/dolthub/dolt

And that has a user-friendly UI in DoltHub:

https://www.dolthub.com/

You wouldn't store the images themselves in Dolt, those would likely be links to S3 but al the labels and surrounding metadata could be stored in Dolt?

DISCLAIMER: I'm the CEO of DoltHub so this is self-promotion.