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Building a Simple Search Engine That Works
- eduction 11mo agoI completely agree with the insight that full text search has been complexified. People seem to want to jump straight to clustering or other enterprise level things. I also appreciate the moxie of getting in there and building it yourself. Myself, I reach for Lucene. Then you don’t need to build all this yourself if you don’t want. It lives in a dir on disk. True, it’s a separate database, but one optimized for this problem.
- aorloff 11mo agoThis was the solution I was thinking about, but I thought, well that's the way someone would have done it 20 years ago
- shevy-java 11mo agoAlright but why do we not have more search engines that are actually good? I'd love to cut myself off from Google, including Google Search, but any alternatives manage to be even worse. Consistently so. It's as if Google won the war by being just permanently slightly better - while everyone is actually really crap. That wasn't the case, say, 10 years ago or so.
- 19l21 11mo agoI use the '4get' proxy search engine, which lets you use pretty much every search engine under the sun, for both websites and images. It's really useful because it is faster than google, and if you need to find some pages you can just change the search engine quickly. It is open source and there are many instances available, I use '4get.bloat.cat' or '4get.lunar.iu' It is a better alternative to SearX for sure
- wheybags 11mo agoI checked the about page on 4get.bloat.cat, and within the first paragraph of the "what is this" section, it used the phrase "globohomo bullshit". I dont think these are people I want to support.
- inferiorhuman 11mo agoThese days I default to DDG. Not because it's improved but because Google's results are just that bad. Even a couple years ago I was reaching for Google with a lot more frequency.
- jillesvangurp 11mo agoBecause it's not a simple problem space. Lucene has gone through about three decades of lots of optimization, feature development, and performance tuning. A lot of brain power goes into that. Google bootstrapped the AI revolution as a side effect of figuring out how to do search better. They started by hiring a lot of expert researchers that then got busy iterating on interesting search engine adjacent problems (like figuring out synonyms, translations, etc.). In the process they got into running neural networks at scale, figuring out how to leverage GPUs and eventually building their own TPUs. The Acquire Podcast recently did a great job of outlining the history of Google & Alphabet. Doing search properly at scale mainly requires a lot of infrastructure. And that's Google's real moat. They get to pay for all that with an advertising money printing machine. Which BTW. leverages a lot of search algorithms. Matching advertisements to content is a search problem. Google just got really good at that. That's what finances all the innovation in this space from deep learning to TPUs. Being able to throw a few hundred million at running some experiments is what makes the difference here.
- eduction 11mo agoNot all search is web-wide search. The best-known example of this is probably Amazon's search bar. No one really wants to search Amazon via Google. They have staffers contributing heavily to Lucene. But also there are all kinds of other applications. Let's say you run a reviews site; you can build a bespoke power search form allowing people to sort on things like price, date of review, set a minimum star threshhold, etc. You can also weigh product names or review titles more heavily in the index scoring (a review /of/ the Pixel 10 should rank higher than a review that mentions the Pixel 10 prominently). Even being able to sort results of searching blog posts or other dated content by date is powerful - Google can only guess at the actual dates of those posts. You can search with required tags, or weigh tags more heavily in result scoring. You can put your finger on the scale and say, effectively, post A should always rank more highly than post B for term X. Also, site operators know traffic/popularity, which internet search engine can only sort of guess at, and can use this to score/sort. Amazon clearly does this. For some reason a lot of web devs seem to think search is this really hard problem. But once you learn the basics of how it works, and if you use a library like Lucene, it does not need to be hard at all. Mostly you just have to be strategic and consistent about where and when you index and deindex content, it's usually alongside your db persistence calls. Once it's running you optimize by sprinkling some minimum amount of magic on your scoring setup to make it worthwhile/differentiated from Google.
- aorloff 11mo agoBefore Lucene, search was really hard
- MatejKafka 11mo agoHave you tried Kagi?
- mobeigi 11mo agoGreat read. It makes you wonder how heavily optimised the tokenizers used by popular search enginea truly are.
- tombert 11mo agoAbout a decade ago, I was working with a guy who was getting a PhD in search engine design, which I knew/know nothing about. It was actually a lot of fun to chat with him, because he was so enthusiastic about how searching works and how it can integrate with databases, and he was eager to explain this all to anyone who would listen. I learned a fair amount from him, though admittedly I still don't know much about the intricacies of how search engines work. Some day, I am going to really go through the guts of Apache Solr and Lucene to understand the internals (like I did for Kafka a few years ago), and maybe I'll finally be competent with it.
- DanielHB 11mo agoPeople who work on really obscure things love to talk about their work, heck if someone would listen to me I could talk for hours about what I do. Unfortunately very few people care about the minutia of making a behemoth system work.
- puilp0502 11mo agoI would. Heck, I bet half of HN would be interested in what kind of insanity lies under those behemoths.
- DanielHB 11mo agoI work with music streaming, it is mostly just a lot of really banal business rules that become an entangled web of convoluted if statements. Where to show a single button might mean hitting 5 different microservices and checking 10 different booleans
- Bengalilol 11mo agoI would be more than interested to listen to you and what you do. Do not hesitate to share (blog post, AskHN, ShowHN, ...)
- vjvjvjvjghv 11mo agoIt seems a common problem in our profession that you can’t really talk to anybody about what you are doing. My friends have a vague idea but that’s it.
- nmstoker 11mo agoReminds me of reading Programming Collective Intelligence by Toby Segaran, which inspired me with a range of things, like building search, recommenders, classifiers etc.
- cipherself 11mo agoThat was a great book, I wonder what the 2025 equivalent of it is...
- RestartKernel 11mo agoPrompting Inferred Intelligence: from ChatGPT to Claude
- _s_a_m_ 11mo agoI loved that book also, but saw him a few year later saying in some youtube video "don't use that book" because it is obsolete in his opinion.
- shevy-java 11mo agoGood. Now please someone replace Google's search engine. I am always annoyed using it, how bad it is these days. Then I try the alternatives such as Duck Duck Go and they manage to be even worse. Qwant is semi-ok but it also omits tons of things that Google Search finds (and also is slower, for some weird reason). Google's UI nerf is also annoying - so much useless stuff. In the past I could disable that via ublock origin but Google killed that for chrome. We need to do something against this Evil that Google brought into this world.
- ku1ik 11mo agoTry kagi.com. I tried and stayed. It’s paid though.
- dyml 11mo agoI also used Kagi, but decided to cancel my subscription last year when it was revealed they pay Yandex for their search, which is a Russian company that ultimately fuels the Russian war on Ukraine. Once Kagi stops transferring money to Russia, I’d be happy re-subscribe.
- ramon156 11mo agoDo you have a source how funding yandex funds the war? Yandex is a great search engine, so I would hate to find out that this is true
- b2ccb2 11mo agohttps://en.wikipedia.org/wiki/Yandex#Legal_issues_in_Ukraine https://www.zois-berlin.de/en/publications/zois-spotlight/the-sad-fate-of-yandex-from-independent-tech-startup-to-kremlin-propaganda-tool
- ninalanyon 11mo agoIt's based in Russia so it presumably pays taxes and salaries in Russia.
- precompute 11mo agoIncredible article. Does what it claims in the title, is written well and follows a linear chain of reasoning with a minumum of surprises.
- marginalia_nu 11mo agoThe idea behind search itself is very simple, and it's a fun problem domain that I encourage anyone to explore[1]. The difficulties in search are almost entirely dealing with the large amounts of data, both logistically and in handling underspecified queries. A DBMS-backed approach breaks down surprisingly fast. Probably perfectly fine if you're indexing your own website, but will likely choke on something the size of English wikipedia. [1] The SeIRP e-book is a good (free) starting point https://ciir.cs.umass.edu/irbook/ https://ciir.cs.umass.edu/irbook/
- submeta 11mo agoThank you very much for the recommendation. I am in the process of building knowledge base bots, and am confronted with the task of creating various crawlers for the different sources the company has. And this book comes in very handy.
- SenanG 11mo ago[dead]
- HelloUsername 11mo agoI love your https://marginalia-search.com https://marginalia-search.com :)
- marginalia_nu 11mo ago"Building A Complex Search Engine That Works Sometimes"
- moffkalast 11mo ago15% of the time it works every time.
- gcanyon 11mo ago> The difficulties in search are almost entirely dealing with the large amounts of data, both logistically and in handling underspecified queries. I would expect the difficulty to be deciding which item to return when there are multiple that contain the search term. Is wikipedia's article on Gilligan's Island better than some guy's blog post? Or is that guy a fanatic who has spent his entire life pondering whether Wrongway Feldman was malicious or how Irving met Bingo Bango and Bongo? Add in rank hacking, keyword stuffing, etc. and it seems like a very hard problem, while scaling... is scaling? ¯\_(ツ)_/¯
- jillesvangurp 11mo agoBuilding a simple text search engine isn't that hard. People show them off on HN on a fairly regular basis. Most of those are fairly primitive. Unfortunately building a good search engine isn't that straightforward. There's more to it than just implementing bm25 (the goto ranking algorithm), which you can vibe code in a few minutes these days. The reason this is easy is because this is nineties era research that is all well publicized and documented and not all that hard once you figure it out. Building your own search engine is a nice exercise for understanding how search works. It gets you to the same level as a very long tail of "Elasticsearch alternatives" that really aren't coming even close to implementing a tiny percentage of its feature set. That can be useful as long as you are aware of what you are missing out on. I've been consulting companies for a few years with going from in house coded solutions to something proper (typically Opensearch/Elasticsearch). Usually people fight themselves into a corner where their in house solution starts simple and then grows more complicated as they inevitably deal with ranking problems their users encounter. Usual symptoms: "it's slow" (they are doing silly shit with multiple queries against postgres or whatever), "it's returning the wrong things" (it turns out that trigrams aren't a one size fits all solution and returns false positives), etc. Add aggregations and other things to the mix and you basically have a perfect use case for Elasticsearch about 10 years ago before they started making it faster, smarter, and better. The usual arguments against Elasticsearch & Opensearch: "Elasticsearch/Opensearch are hard to run". Reality, there isn't a whole lot to configure these days. Yes you might want to take care of monitoring, backups, and a few other things. As you would with any server product. But it self configures mostly. Particularly, you shouldn't have to fiddle with heap settings, garbage collection, etc. The out of the box defaults work fine. Get a managed setup if all this scares you; those run with the same defaults typically. Honestly, running postgres is harder. There's way more to configure for that. Especially for high availability setups. The hardest part is sizing your vms correctly and making sure you don't blow through your limits by indexing too much data. Most of your optimizations are going to be at the index mapping level, not in the configuration. "It's slow". That depends what you do and how you use it. Most of the simple alternatives have some hard limitations. If you under engineer your search (poor ranking, lots of false positives) it's probably going to be faster. That's what happens if you skip all the fancy algorithmic stuff that could make your search better. I've seen all the rookie mistakes that people make with Elasticsearch that impact performance. They are usually fairly easy to fix. (e.g. let's turn off dynamic mapping and not index all those text fields you never query on that fill up your disk and memory and bloat your indexing performance ...). "I don't need all that fancy stuff". Yes you do. You just don't know it yet because you haven't figured out what's actually needed. Look, if your search isn't great and it doesn't matter, it's all fine. But if search quality matters and you lose user's interest when they fail to find stuff in your app/website it quickly can become an existential problem. Especially if you have competitors that do much better. That fancy stuff is what you would need to build to solve that. Unless you employ some hard core search ranking experts, your internally crafted thing is probably not going to be great. If you can afford to run at ~2005 era state of the art (Lucene existed, SOLR & Elasticsearch did not, Lucene was fairly limited in scope), then go for it. But it's going to be quite limited when you need those extra features after all. There are some nice search products out there other than Elasticsearch & Opensearch that I would consider fit for purpose; especially if you want to do vector search. And in fairness, using a search engine properly still requires a bit of skill. But that isn't any different if you do things yourself. Except it involves a lot less wheel reinvention. There just is a bit of necessary complexity to building a good search product.
- entropoem 11mo agoSearching in general is difficult. It is really a difficult thing. If you haven't felt it, look at companies like Apple, Microsoft, or "The most important AI research lab in the world" OpenAI, for example, their products have terrible search features even though their resources - money - technology can be considered top-notch.
- marginalia_nu 11mo agoI think the reason most companies can't implement a working search box is the sort of work needed to make it perform adequately clashes catastrophically with the software development culture that has emerged in the corporate world (anything to do with sprints, jira, and daily standups). Getting search to work well requires a lot of fiddling with ranking parameters, work that is difficult bordering on impossible to plan or track. The work requires a degree of trust that developers are rarely afforded these days.
- shortrounddev2 11mo agoidk if that argument really makes sense. A lot of AI chatbot companies have terrible or broken webapps and backend servers because it's not what they really care about. They put billions into their AI models, not their search features. I think the shittiness of their search features is symptomatic of the company's incentives, not necessarily the difficulty of the problem.
- renegade-otter 11mo agoIt's an interesting exercise. Having built searches before easily-available OSS products were available, and when even the commercial offerings sucked, do not ever build your a) database b) search engine, unless you can clearly state the reason for doing so. Entire cubicle farms of people have been devoted to this problem for years, and if you dare to do this for work because "I think I can", you will find yourself in an ocean of hurt. "Hey, so it won't be so hard to add 'did you mean' functionality, right? And we were thinking of adding a taxonomy next year for easy navigation..." Check. Mate.
- pelasaco 11mo agolove the style, colors and the cookie popup from https://karboosx.net/ https://karboosx.net/. Anyone knows if its an open source framework/style/tool being used here or it just the web dev skills of the author that are superb?
- journal 11mo agowhy isn't there a place to post something where someone else will find it when searching that doesn't require auth? i get the logistics of what i'm asking, but i really think we need a global index.
- wink 11mo agoMy pet peeve for search engines for content I use is that they regularly ignore 2-letter and 3-letter "words" or acronyms. If all I need is a search for "mp3" then stripping exactly that is not useful ;) (was just the first file extension that came to my mind, but "PHP" works just as well).
- dominicrose 11mo agoI wonder how well it would scale. Elasticsearch's performance is impressive even at an unrecommended scale.
- franczesko 11mo agoLong time ago, I've really enjoyed a course by David Evans from Virginia University about building a search engine and concepts of computer science. Building a "classic" search engine is a very fun project to go through. https://www.cs.virginia.edu/~evans/courses/cs101/ https://www.cs.virginia.edu/~evans/courses/cs101/ List: https://www.youtube.com/watch?v=9nkR2LLPiYo&list=PLAwxTw4SYaPmjFQ2w9j05WDX8Jtg5RXWW https://www.youtube.com/watch?v=9nkR2LLPiYo&list=PLAwxTw4SYa... Dave's profile: https://www.cs.virginia.edu/~evans/ https://www.cs.virginia.edu/~evans/
- hammeiam 11mo agoI took this one as well - even as a new programmer is was really engaging and information-dense.