In the linked article, these projects are all explicitly described as opportunities to learn about low-level stuff like how to efficiently store editable text. The difference with a web search engine is that nobody today can build such a thing completely from scratch, therefore it forces you to give up the toxic NIH mentality, which in my experience is usually driven by elitism and ego (on full display in this comment thread), not by some lofty desire to learn something new.
I'm sorry, but can you substantiate this claim? I've seen no indication that a search engine is not buildable from scratch at all.
The point is that it's too much work for a single person to build all the parts themselves. It's only feasible if you rely on pre-existing HTTPS libraries and database and text search technologies.
That's not a textbook algorithm.
The problem space is embarassingly parallel, so sharding is no problem. Although, realistically, you probably only need 1 server to cope with the load and storage needs. This isn't 2004. Servers are big and fast now, as long as you don't try to use cloud compute.
And of course all of this is based on "standard" algorithms. But it doesn't change the fact that implementing them all to build a functional performant web crawler+database+search is a project that is larger than any one person could build from scratch.
It would only be feasible to build on top of existing libraries, which is the whole point here.
I don't think you've made a single point that substantiates that claim and neither has anyone else, really. The person you're arguing with has built (as per their own estimation) more from scratch when it comes to the actual search engine core than anything else in their own project (https://marginalia.nu/).
Honestly, it seems more like the people arguing a search engine is somehow "off limits" from scratch are doing so because they imagine it's less feasible, probably because they simply don't know or are in general pretty bad at implementing things from scratch, period.
To a large degree there is also a wide difference in actual project scope. Remember that we are comparing this to implementing Space Invaders, one of the simplest games you can make, and one that is doable in an evening even if you write your own renderer.
To talk about "webscale" (a term that is so deliciously dissonant with most of the web world which runs at a scale several 100 times slower and less efficient than things should be) is like suddenly talking about implementing deferred shading for the Space Invaders game. Even if this was something you'd want to explore later, it's just not something you're doing right now because this is something you're using to learn as you go.
Well let's do the math!
1 billion bytes is 1 GB. The average text-size of a document is ~5 KB, that is the HTML, uncompressed. 1 billion documents is thus about 5 TB raw HTML. In practice the index would be smaller, say 1 TB, because you're not indexing the raw HTML, but a fixed width representation of the words therein, typically with some form of compression as well. (In general, the index is significantly smaller than the raw data unless you're doing something strange)
You could buy a thumbdrive that would a search index for 1 billion documents. A real server uses enterprise SSDs for this stuff, but even so, you don't even have to dip into storage server specs to outfit a single server with hundreds of terabytes of SSD storage.
> And of course all of this is based on "standard" algorithms. But it doesn't change the fact that implementing them all to build a functional performant web crawler+database+search is a project that is larger than any one person could build from scratch.
I'm still not seeing why this is impossible.
> It would only be feasible to build on top of existing libraries, which is the whole point here.
I don't think there are existing libraries for most of this stuff. Most off-the-shelf stuff in the search space is for indexing smaller corpuses, they generally aren't built to scale up to corpus sizes in the billions (e.g. using 32 bit keys etc.)
Add docids to sorted update lists. Zipper merge and arithmetic coding once lists get large, is the textbook baseline from back then.
Tack on a skip list, and you have fast intersections.
This is well trodden ground.
I do pull a lot of libraries, but an enormous amount of what the search engine does is very much built from scratch. The libraries generally deal with parsing common formats, compression, serialization, and various service glue like dependency injection. I think the number of explicit dependencies is a bit inflated by the choice to not use a framework like springboot, which pulls many of the same (or equivalent ones) implicitly.
What makes the search engine a search engine, the indexing software (all the way down to database primitives like btrees etc.), a large chunk of the language processing, and so forth; that's all bespoke. I think it needs to be. A lot of existing code just doesn't scale, or has too many customizations that would add unnecessary glue and complexity to my own code.
I'm going to echo SerenityOS Andreas and suggest that it's a skill like any other. If you shy away from building custom solutions to hard problems, you will never be good at it; and it will become a self-fulfilling prophecy that these NIH solutions are too hard to build.
At the same time, there's a time and a place and you should indeed be judicious as to when to roll your own solutions, but maybe that time and place is exactly in a hobby project like the ones suggested in this thread (and is how my search engine started out; a place to dick around with difficult problems).
I'd also add that being able to tackle problems yourself, rather than needing a library to do all the heavy lifting at all times, is a great enabler. Sometimes there is no adequate library, but that doesn't mean the conclusion has to be "welp, I guess we can't do that yet..."
You can still find search-engine-from-scratch courses on Udemy, complete with all the necessary algorithms [1].
[1]: https://www.udemy.com/course/build-a-search-engine-with-pyth...
"introduction online cs course that uses Python the build a search engine from scratch"
is udemy CS 101
Even through my smartphone autocorrect mistakes of 'introductory -> introduction' and 'the -> to'
You know those car guys who will rebuild their engine, just because? Or those retro computer guys that will recap an ancient board rather than buying a modern pc?
For you it is a job, for me it is a hobby. I have no interest in making something 'professional' I want to take it apart to understand how it works. Want to understand how a text editor works? Write one.
What component of that is ego?
It seems to me you're the elitist, you're not far off saying mere users shouldn't be allowed to modify their own software, shouldn't be allowed to install software that hasn't been okayed by the people who know what they're doing.
Your lack of constraints on personal exploration in software is interpreted as hubris by people who came to software seeking high paying regimented recipe-following.
Similar to compilers or tiny OSes, one can go as hardcore as necessary, or just stick to basic stuff.
Of all the typical personal challenge style projects, databases are probable the hardest to build, and even that is not impossible.
Does not have domain-specific dependencies.
So a code editor based on ACE or CodeMirror would not be from scratch, obviously, but one that involves writing all of the domain-specific logic would be. Using generic libraries doesn't stop something being from scratch. (In my case Tree-sitter is arguably domain-specific, but an early version did use a hand-coded JavaScript tokeniser in its place.)
Case in point, I've spent a year excising bloated frameworks from my stack at work and replacing the few corners we needed from those frameworks with, e.g. 50 lines of curl calls. The C compiles instantly and is tailored for our tiny use case, produced much quicker delivery on our one related feature we wanted, and removed chains of dependencies.
Being reliant on far-too-abstract libraries and frameworks to do simple jobs is also a curse. But nobody at work has the experience to know that curl was sitting right there on our image available for our use. And nobody has that experience because nobody took the time to build something from low level libraries. Now we know how and can make an intelligent decision without defaulting in either direction because we were afraid to try.
It's just faster, cleaner, and easier in a few cases to do precisely what you need right now, rather than anticipate a million things you might need and refactor your code to adopt a given "solution".
Having said that, there are libraries there are high value/cost. So I keep those. But the dirty reality is that most libraries are pretty bad.
Really? I think there are a couple out there. The main issue today is scale, but you could constrain that by limiting your crawler to a fixed set of sites.
Because when you write things from scratch, you actually have the space to innovate. But when building product with preexisting puzzles, there is much less space to actually make any usefull changes that would make your product actually standout from existing alternatives (which nih is all about)
That's my read as well.
Amen. And further, what better prepares a programmer to assess the relative costs of implementing a thing vs using a library providing that thing than having attempted an implementation?
Learning by doing is a valid approach, and this can even be called fun.
Literally all of the listed projects, text editors, compilers, operating systems, and ray tracers, can exercise the exact same activities.
I'm more inclined to think that your comment is really more revealing about what kind of knowledge is in your own personal wheelhouse. Having worked on a ray tracer that was subsequently used on many feature films, I can assure you that all of your bullet points apply to that project, too.
It's much more a matter of whether you want to do something small scale and fun, or whether you want to suck all the joy out of it by applying the same soul crushing constraints we already get paid to do in our day jobs. Bleh.