Future of our industry? Such languages are popular and suited to certain types of projects and solutions certainly. Particularly for systems in computing, and information and data science.
However, for complex representational systems, including both transactional and continuous systems in business, commerce and industry, other languages and paradigms can remain better suited.
> However, for complex representational systems, including both transactional and continuous systems in business, commerce and industry, other languages and paradigms can remain better suited.
Hello. Respectfully, what is a complex representational system? Why are other languages/paradigms better suited over a language like F#?
> Respectfully, what is a complex representational system?
A database is one example.
A database is also global mutable state for the programs that write to it, and that significantly compromises the advantages of using functional programming languages for such programs. You might start with some nice pure functional code, but the database adds massive side effects.
Actually, the benefits of pure functional programming are even more clearly exposed if you're doing complex IO operations like disk access and mutability. The ability to capture the effectful operations (read a table, write a row) as statically-typed action containers is invaluable because it lets you sequence the effects in a correct order with very little effort.
This is the #1 misconception I see surrounding pure functional programming - that once you run into mutable state, you run into problems.
It is entirely the opposite. PFP exposes the murky aspects of mutability, provides abstractions around it, and ensures that you're not tripping over yourself in regards to mutability.
Maybe we should get rid of databases (or limit them to reporting).
Back in the days they were mandatory since memory was expensive and you simply had to access stuff from disk and needed something that made it reasonably efficient. Now memory is so cheap and for quite many business applications it would be feasible to keep everything in memory. SSDs with GB/s level read speeds would enable restoring the stuff back to memory in reasonable time in case the cluster goes down.
I think the whole database thing also caused major issues on the object oriented side and actually stopped people from really using OO (or getting benefits out of it). Instead of building intelligent and smart objects it is easy to end up with objects that are just containers for data.
Probably there has been thoughts on how to do this, one old project I remember is Prevayler[1].
SQL and ORM are a superb fit for a great many applications, incidentally a large share of real world applications. The four-letter abbrev. CRUD comes to mind, as well as reporting.
Most kinds of NoSQL remove some benefits of the relational model while not really giving you the benefits of object persistence. I never felt a great need to use it; since quite some of these databases also had all sorts of issues that not exactly endeared trust for serious applications -- I'm not working on software where that's an OK thing to have (though for others it might be an acceptable tradeoff).
The real deal persistent object databases are a completely different beast from both NoSQL and relational models (only some NoSQL concepts like explicit / application-level indexing carry over). Two important things to note about these: 1.) There are not many of them 2.) Properly using them already requires proper OO technique. Failing 2.) will make it an unmaintainable mess. Certain kinds of applications benefit greatly from these, and there they also tend to perform better in both developer experience and efficiency as well as application performance than forcing a huge impedance mismatch down the throat of an ORM -- which pretty much always means that the underlying relational DB is used in very anti-patternish ways, resulting in poor performance regardless how good the DB actually is.
The idea is not to query things from the persistent store. Instead you would keep all the data in memory. The persistent store is just there in case your server goes down. In case of OO, there would be one big object graph which you then navigate using the functionality available in your programming language. For example take a list of things, pass it through the filter function to pick what you want.
My feeling is that in traditional business apps you don't have so much needs to these random searches over huge amount of data. It's more about taking hold of one piece of the graph and then navigating to related objects (dummy example: search for customer, then start looking at that customers orders).
I'm not familiar with Smalltalk, but I'm sure there was some ideas related to persistence other than just ORM and relational database (but could be those ideas have been proven as bad over the years). I just find it a bit strange that we have been building these things pretty much the same way for the last 20+ years. Meanwhile the hardware has changed much. Even with quite small corporate hw budget you are looking at half a terabyte of RAM and tens of cores in a single server.
It's the basis of most Zope apps, including Plone, but also many other applications; there's not much talk about it, because it just works. Like in the comment I made below; if it's a good fit ze ZODB is quite literally worth every LoC in gold.
The database itself doesn't do that much (apart from giving you transparent object/application persistence, transactions and MVCC :), as one would expect.
The Zope people made an excellent job of modularising it (or, in other words: this is by principle extremely modular), so there are a bunch of packages commonly used around it (eg. BTrees, zodburi, often either ZEO or RelStorage and stuff like eg. zope.container).
(Historically it's also very interesting - development started in 1997! The revision history is an interesting read, too, many familiar names pop up, including GvR)
a. Transactional systems [1], based around actions that need to be recorded, typically for commercial or legal reasons, like software used to record your purchases, payments, reservations, participation, interactions, obligations, results, commitments, plans, and significant events.
b. Non-transactional continuous systems, like software controlling an elevator, warehouse conveyor system, or a vehicle engine management system.
The Tezos project is writing a new safety-focused blockchain implementation in OCaml. Would you classify that as a representational system or otherwise?
I don't know anything about Tezos or blockchain implementations sorry, but I suspect that it is primarily focused on the processing of data, rather than the modeling of the concepts in a domain – a specific area of activity or knowledge.
As such it is more of a Type 2B project - "Information, data science and analysis projects, systems often focused on the processing of data." (http://aryehoffman.com/entry/project-types)
Most mainstream languages don't even have sum types, but have to encode them via other means (enums, tags, inheritance). They are not necessarily the best choice for modelling data, just your preferred choice.
From the description, 2(b) sounds like a strict superset of 1(a). In fact, it sounds like the
most generic possible description of an IT system. I mean, what computer system is not focused on the processing of data?
Anyway, I asked you about a blockchain technology because it fits perfectly into your description of a representational technology. In fact it's a breakthrough in the space, and I'm finding it hard to believe that an IT professional doesn't have even a basic idea about about it.
There's not enough detail here to really comment. I can say that Haskell has the best software transactional memory implementation out there, thanks to purity and controlled side-effects. Haskell's explicit handling of state also helps provenance and keeping state managed / in the database.
However, for complex representational systems, including both transactional and continuous systems in business, commerce and industry, other languages and paradigms can remain better suited.