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Comment by bluejekyll | Hacker News Reader

I think this was truly the most amazing thing about learning Rust. After having experienced the pain (the issues brought up in the linked slide deck) of threads in C, then C++ and Java, it was wild to work with a language that provided some significant safety rails for working with data across threads.

Now async/await gives us even better options on top of that, but it’s truly what made me enjoy the language so much. This article is what resonated with me and got me to invest so much spare time over the last 5 years in working with Rust: https://blog.rust-lang.org/2015/04/10/Fearless-Concurrency.h...

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Rust does a great job here, but so do languages that make multithreading safer at a higher level -- Erlang/OTP and Haskell are two great examples. Immutable data may not solve every concurrency problem, but it sure goes a long way.

I also have a lot of respect for Ada's task-based concurrency approach (independent actors, communicating by rendezvous). You don't get the flexibility to roll your own concurrency strategy in Ada, but the language's support for its chosen mechanism is truly excellent. Even if you'll never use Ada, this part of the language is worth studying just as an example of great engineering design.

There's a nice Kevlin Henney talk where he lays out this diagram:

                                 |
       non-shared mutable state  |  shared mutable state
                                 |
     ----------------------------+------------------------
                                 |
      non-shared immutable state | shared immutable state 
                                 |

Each quadrant is safe, except the one in the top right: shared mutable state.

Functional languages are great at the bottom two, since they strongly encourage immutable state. Message-passing based concurrency strongly encourages non-shared state, the safe two on the left.

Rust is the only language I've seen which encourages all three safe quadrants, while making the fourth a compile-time error.

Speaking of Shared mutable state, unlearning OOP is going to be a big task for the industry to tackle. Feels like it's on its way out on the backend at least already. It's definitely been my biggest stumbling block in grokking parallel compute.

> Functional languages are great at the bottom two, since they strongly encourage immutable state.

Haskell actually has safe & ergonomic shared mutable state via STM

And it has proven-to-be-not-shared mutable state via ST.

> Each quadrant is safe, except the one in the top right: shared mutable state.

No. Your database is one giant shared mutable state.

How is using a database safe then? Transactions.

Haskell has had software transactional memory for fifteen years now. Microsoft tried to copy it in .NET but it's nearly impossible to do right in a language without clear separation of pure and impure code.

"> Each quadrant is safe, except the one in the top right: shared mutable state.
No. Your database is one giant shared mutable state.

How is using a database safe then? Transactions."

Transactions are less an occasion where shared mutable state is made 'safe' during concurrency and more a situation where concurrent processes are forced to temporarily interact and operate in a sequential, non-concurrent, manner. They use locks under the covers. Databases manage to be parallel because different processes operate on different sets of data at the same time; they lock when two or more processes attempt to access the same row on a table. Transactional state access is still vulnerable to deadlocks and other difficulties of concurrent programming. This means that transactional state is not 'safe' in the same way that immutable and non-shared state are safe. It's just a much easier way of managing the kind of difficulties you have with shared mutable state than say, raw locks.

No. Please read about MVCC: https://en.m.wikipedia.org/wiki/Multiversion_concurrency_con...

The tl;dr is that

> Locks are known to create contention especially between long read transactions and update transactions. MVCC aims at solving the problem by keeping multiple copies of each data item. In this way, each user connected to the database sees a snapshot of the database at a particular instant in time. Any changes made by a writer will not be seen by other users of the database until the changes have been completed (or, in database terms: until the transaction has been committed.)

In other words, the system uses immutable state under the hood plus some atomics/locking to present the abstraction of safe shared mutable state.

> No. Your database is one giant shared mutable state.

That doesn't refute anything from the parent post. In fact you prove the parent's point in the very next sentence:

> How is using a database safe then? Transactions.

Which is to say, you can have shared mutable state, but you need some mechanism to protect access to that state. It is not safe to just access it however you like, which is why database have transactions, and why we have primitives like mutexes for dealing with OS-level threads.

The trick is using the three safe quadrants without bottlenecking on memory bandwidth copying the data over and over again.

If immutability is a language level guarantee and not just a convention, you can use structure sharing to address this problem pretty effectively. Just about any functional language with immutable datastructures does it.

For the record, Erlang also has an internal transactional in-memory database called Mnesia, which is essentially large-scale shared mutable state.

I think the idea that finding ways of working with threads (and ownership) with more safety while minimizing performance impact is a healthy side effect of rust.

I think though that rust is one approach of many and that they aren't orthogonal.

I personally think libraries for multi threading on top of rust or C++ are necessary to really nail the problem down. Even async and await are too granular and difficult to get right in my opinion.

I think regardless of the language, queues of data chunks (not just tasks) combined with solid concurrent data structures will go a very long way. Rust may help get those libraries and data structures to be more correct with less effort, but ultimately getting threading right at the lower level just isn't practical for most programmers most of the time, and I say this as someone confident in their parallel programming skills.

Yeah, there are some pretty solid crates coming up. Obviously Tokio as a runtime, Rayon for parallel iterators,and the whole Async Std crate. Rayon is a good example of a crate that helps add concurrency without much headache for embarrassingly parallel operations.

Even still, even in languages with built-in runtimes and GC like GO, it is very easy to create deadlocks/livelocks. Programmers intuitions of concurrency are generally wrong, and the correct intuitions are complex. I don't know how we make concurrency easy. I do like Futures however, they provide a nice abstraction over threads.

I'm gonna be That Guy and point out that rayon addresses parallelism, not concurrency (which is crossbeam's domain). My favorite explanation of the difference (by the inimitable yosefk): https://yosefk.com/blog/parallelism-and-concurrency-need-dif....

Was an interesting read, thanks! Excited for the future where now I can become That Guy™!

I still feel that, while all these abstractions are very fine and handy, there is only so much you can do without actually understanding how threading and locking works. If you grow up as a developer without actually touching it I wonder how you can actually understand this.

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