Don't miss how this works. It's not a server-side application - this code runs entirely in your browser using SQLite compiled to WASM, but rather than fetching a full 22GB database it instead uses a clever hack that retrieves just "shards" of the SQLite database needed for the page you are viewing.
I watched it in the browser network panel and saw it fetch:
It's reminiscent of that brilliant SQLite.js VFS trick from a few years ago: https://github.com/phiresky/sql.js-httpvfs - only that one used HTTP range headers, this one uses sharded files instead.
this does not caches the data right? it would always fetch from network? by any chance do you know of solution/extension that caches the data it would make it so much more efficient.
Thanks! I'm glad you enjoyed the sausage being made. There's a little easter egg if you click on the compact disc icon.
And I just now added a 'me' view. Enter your username and it will show your comments/posts on any day. So you can scrub back through your 2006 - 2025 retrospective using the calendar buttons.
I almost got tricked into trying to figure out what was Easter eggy about August 9 2015 :-) There's a clarifying tooltip on the link, but it is mostly obscured by the image's "Archive" title attribute.
Oh, shit that was the problem! You solved the bug! I was trying to figure out why the right tooltip didn't display. A linked wrapped in an image wrapped in an easter egg! Or something. Ha, thank you. Will fix :)
edit: Fixed! Also I just pushed a new version with a Dec 29th Data Dump, so ... updates - yay!
Yes — PMTiles is exactly that: a production-ready, single-file, static container for vector tiles built around HTTP range requests.
I’ve used it in production to self-host Australia-only maps on S3. We generated a single ~900 MB PMTiles file from OpenStreetMap (Australia only, up to Z14) and uploaded it to S3. Clients then fetch just the required byte ranges for each vector tile via HTTP range requests.
It’s fast, scales well, and bandwidth costs are negligible because clients only download the exact data they need.
Hadn't seen PMTiles before, but that matches the mental model exactly! I chose physical file sharding over Range Requests on a single db because it felt safer for 'dumb' static hosts like CF. - less risk of a single 22GB file getting stuck or cached weirdly. Maybe it would work
My only gripe is that the tile metadata is stored as JSON, which I get is for compatibility reasons with existing software, but for e.g. a simple C program to implement the full spec you need to ship a JSON parser on top of the PMTiles parser itself.
At that point you're just io bound, no? I can easily parse json at 100+GB/s on commodity hardware, but I'm gonna have a much harder time actually delivering that much data to parse.
Look into using duckdb with remote http/s3 parquet files. The parquet files are organized as columnar vectors, grouped into chunks of rows. Each row group stores metadata about the set it contains that can be used to prune out data that doesn’t need to be scanned by the query engine. https://duckdb.org/docs/stable/guides/performance/indexing
LanceDB has a similar mechanism for operating on remote vector embeddings/text search.
> Look into using duckdb with remote http/s3 parquet files. The parquet files are organized as columnar vectors, grouped into chunks of rows. Each row group stores metadata about the set it contains that can be used to prune out data that doesn’t need to be scanned by the query engine. https://duckdb.org/docs/stable/guides/performance/indexing
But, when using this on frontend, are portions of files fetched specifically with http range requests? I tried to search for it but couldn't find details
There was a UK government GitHub repo that did something interesting with this kind of trick against S3 but I checked just now and the repo is a 404. Here are my notes about what it did: https://simonwillison.net/2025/Feb/7/sqlite-s3vfs/
From reading the TIL, it doesn't appear as if Simon used LLM for a large portion of what he did; only the initial suggestion to check the archive, and the web tool to make his process reproducible. Also, if you read the script from his chat with Claude code, the prompt really does the heavy lifting.
Sure, the LLM fills in all the boilerplate and makes an easy-to-use, reproducible tool with loads of documentation, and credit for that. But is it not more accurate to say that Simon is absurdly efficient, LLM or sans LLM? :)
Nothing smart with HTTP range requests yet - I have https://lite.datasette.io which runs the full Python server app in the browser via WebAssembly and Pyodide but it still works by fetching the entire SQLite file at once.
i played around with this a while back. you can see a demo here. it also lets you pull new WAL segments in and apply them to the current database. never got much time to go any further with it than this.
This is somewhat related to a large dataset browsing service a friend and I worked on a while back - we made index files, and the browser ran a lightweight query planner to fetch static chunks which could be served from S3/torrents/whatever. It worked pretty well, and I think there’s a lot of potential for this style of data serving infra.
I tried to implement something similar to optimize sampling semi-random documents from (very) large datasets on Huggingface, unfortunately their API doesn't support range requests well.
A recent change is I added date spans to the shard checboxes on query view so it's easier to zero dates you want if you have that in mind. Because if your copy isn't local all those network pulls take a while.
The sequence of shards you saw when you paginated to days is faciliated by the static-manifest which maps HN item ID ranges to shards, and since IDs are increasing and a pretty good proxy of time (a "HN clock"), we can also map the shards that we cut up by ID to the time spans their items cover. An in memory table sorted by time is created from the manifest on load so we can easily look up which shard we need when you pick a day.
Funnily enough, this system was thrown off early on by a handful of "ID/timestamp" outliers in the data: items with weird future timestamps (offset by a couple years), or null timestamps. To cleanse our pure data from this noise, and restore proper adjacent-in-time shard cuts we just did a 1/99 percentile grouping and discarded the outliers leaving shards with sensible 'effective' time spans.
Sometimes we end up fetching two shards when you enter a new day because some items' comments exist "cross shard". We needed another index for that and it lives in cross-shard-index.bin which is just a list of 4-byte item IDs that have children in more than 1 shard (2-bytes), which occurs when people have the self-indulgence to respond to comments a few days after a post has died down ;)
Thankfully HN imposes a 2 week horizon for replies so there aren't that many cross-shard comments (those living outside the 2-3 days span of most, recent, shards). But I think there's still around 1M or so, IIRC.
The GitHub page is no longer available, which is a shame because I'm really interested in how this works.
How was the entirety of HN stored in a single SQLite database? In other words, how was the data acquired? And how does the page load instantly if there's 22GB of data having to be downloaded to the browser?
I wonder how much smaller it could get with some compression. You could probably encode "This website hijacks the scrollbar and I don't like it" comments into just a few bits.
It'd be great if you could add it to Kiwix[1] somehow (not sure what the process is for that but 100rabbits figured it out for their site) - I use it all the time now that I have a dumb phone - I have the entirety of wikipedia, wiktionary and 100rabbits all offline.
I also want to make sure we can build this in CI. My goal is to have this updated every day using the BigQuery update process, so it becomes a 1–2 day delayed static archive of the current state of Hacker News, which is honestly very cool.
I can probably run the build for free on GitHub Actions runners, as long as the runner has about 40 GB of disk space available. If needed, I can free up space on the runner before the build starts.
I’ll also write to GitHub support and ask if they can sponsor the cost of a larger runner, mainly because I need the extra disk space to run the build reliably.
I use the Mudita Kompakt specifically cause it allows sideloading so I can still have a few extras. Right now I have Kiwix and Libby. It works really well.
I have a $10 a month plan from US cellular with only 2gigs so I try to keep everything offline that I can.
Honestly it's mostly the news... so I draw the line at browser, I'll never install a browser, that's basically something I can do when I sit down at a PC. I read quite a bit and I like to have the ability to look up a word or a historical event or some reference from something I read using Kiwix and it's been great for that, just needed to add a 512gb micro sd card. And Libby I just use at the gym when I'm on the treadmill.
Similar to Single-page applications (SPA), single-table application (STA) might become a thing. Just a shard a table on multiple keys and serve the shards as static files, provided that the data is Ok to share, similar to sharing static html content.
do you mean single database? it'd be quite hard if not impossible to make applications using a single table (no relations). reddit did it though, they have a huge table of "things" iirc.
> Next, we've got more than just two tables. The quote/paraphrase doesn't make it clear, but we've got two tables per thing. That means Accounts have an "account_thing" and an "account_data" table, Subreddits have a "subreddit_thing" and "subreddit_data" table, etc.
And the important lesson from that the k/v-like aspect of it. That the "schema" is horizontal (is that a thing?) and not column-based. But I actually only read it on their blog IIRC and never even got the full details - that there's still a third ID column. Thanks for the link.
I did something similar. I build a tool[1] to import the Project Arctic Shift dumps[2] of reddit into sqlite. It was mostly an exercise to experiment with Rust and SQLite (HN's two favorite topics). If you don't build a FTS5 index and import without WAL (--unsafe-mode), import of every reddit comment and submission takes a bit over 24 hours and produces a ~10TB DB.
SQLite offers a lot of cool json features that would let you store the raw json and operate on that, but I eschewed them in favor of parsing only once at load time. THat also lets me normalize the data a bit.
I find that building the DB is pretty "fast", but queries run much faster if I immediately vacuum the DB after building it. The vacuum operation is actually slower than the original import, taking a few days to finish.
I haven't tested that, so I'm not sure if it would work. The import only inserts rows, it doesn't delete, so I don't think that is the cause of fragmentation. I suspect this line in the vacuum docs:
> The VACUUM command may change the ROWIDs of entries in any tables that do not have an explicit INTEGER PRIMARY KEY.
means SQLite does something to organize by rowid and that this is doing most of the work.
Reddit post/comment IDs are 1:1 with integers, though expressed in a different base that is more friendly to URLs. I map decoded post/comment IDs to INTEGER PRIMARY KEYs on their respective tables. I suspect the vacuum operation sorts the tables by their reddit post ID and something about this sorting improves tables scans, which in turn helps building indices quickly after standing up the DB.
Holy cow, I didn't know getting reddit was that straightforward. I am building public readonly-SQL+vector databases optimized for exploring high-quality public commons with Claude Code (https://exopriors.com/scry), I so cannot wait until some funding source comes in and I can upgrade to a $1500/month Hetzner server and pay the ~$1k to embed all that.
One interesting feature of DuckDB is that it can run queries against HTTP ranges of a static file hosted via HTTPS, and there's an official WebAssembly build of it that can do that same trick.
So you can dump e.g. all of Hacker News in a single multi-GB Parquet file somewhere and build a client-side JavaScript application that can run queries against that without having to fetch the whole thing.
DuckDB is an open-source column-oriented Relational Database Management System (RDBMS). It's designed to provide high performance on complex queries against large databases in embedded configuration.
"DICT FSST (Dictionary FSST) represents a hybrid compression technique that combines the benefits of Dictionary Encoding with the string-level compression capabilities of FSST.
This approach was implemented and integrated into DuckDB as part of ongoing efforts to optimize string storage and processing performance."
https://homepages.cwi.nl/~boncz/msc/2025-YanLannaAlexandre.p...
It is very similar to SQLite in that it can run in-process and store its data as a file.
It's different in that it is tailored to analytics, among other things storage is columnar, and it can run off some common data analytics file formats.
Hey jacquesm! No, I just forgot to make it public.
BUT I did try to push the entire 10GB of shards to GitHub (no LFS, no thanks, money), and after the 20 minutes compressing objects etc, "remote hang up unexpectedly"
To be expected I guess. I did not think GH Pages would be able to do this. So have been repeating:
Pretty neat project. I never thought you could do this in the first place, very much inspiring. I've made a little project that stores all of its data locally but still runs in the browser to protect against take downs and because I don't think you should store your precious data online more than you have to, eventually it all rots away. Your project takes this to the next level.
I was thinking more the numeric columns which have pre-built compression mechanisms to handle incrementing columns or long runs of identical values. For sure less total data than the text, but my prior is that the two should perform equivalently on the text, so the better compression on numbers should let duckdb pull ahead.
I had to run a test for myself, and using sqlite2duckdb (no research, first search hit), and using randomly picked shard 1636, the sqlite.gz was 4.9MB, but the duckdb.gz was 3.7MB.
The uncompressed sizes favor sqlite, which does not make sense to me, so not sure if duckdb keeps around more statistics information. Uncompressed sqlite 12.9MB, duckdb 15.5MB
Not the author here. I’m not sure about DuckDB, but SQLite allows you to simply use a file as a database and for archiving, it’s really helpful. One file, that’s it.
At a glance, that is missing (at least) a `parent` or `parent_id` attribute which items in HN can have (and you kind of need if you want to render comments), see http://hn.algolia.com/api/v1/items/46436741
I tried "select * from items limit 10" and it is slowly iterating through the shards without returning. I got up to 60 shards before I stopped. Selecting just one shard makes that query return instantly. As mentioned elsewhere I think duckdb can work faster by only reading the part of a parquet file it needs over http.
I was getting an error that the users and user_domains tables aren't available, but you just need to change the shard filter to the user stats shard.
That depends on the query. SQLite tries to use LIMIT to restrict the amount of reading that it does. It is often successful at that. But some queries, by their very nature, logically require reading the whole input in order to compute the correct answer, regardless of whether or not there is a LIMIT clause.
That's what it does, but if I'm not mistaken (at least in my experience with MariaDB) it'll also return immediately once it ran up to the limit and not try to process further rows. If you have an expensive subquery in the SELECT (...) AS `column_name`, it won't run that for every row before returning the first 10 (when using LIMIT 10) unless you ORDERed BY that column_name. Other components like the WHERE clause might also require that it reads every row before finding the ten matches. So mostly yes but not necessarily
The limit clause isn't official/standard ansi sql, so it's up to the rdbms to implement. Your assumption is true for bigquery (infamously) but not true for things like snowflake, duckdb, etc.
So cool! Would it be impossible fro me to use them on the Archive stats page (https://hackerbook.dosaygo.com/?view=archive) ? If you're okay with that any links/credit line details?
Similar in spirit to a recent tool I recently posted Show HN on, https://exopriors.com/scry. You can use Claude Code to SQL+vector query HackerNews and many other high quality public commons sites, exceptionally well-indexed and usually 5+ minute query timeout limits, so you can run seriously large research queries, to rapidly refine your worldview (particular because you can do easily to EXHAUSTIVE exploration).
This looks cool but can you make a "Google Search Box" page where I don't have to sign in but can use it? It's just a bit of friction and I feel unbothered to overcome it. It's not personal to you - it's just how I feel about anything that looks unknown and interesting I just want to try, not have to sign up. For now. You know?
The BQ dataset is only ~17GB and the free tier of BQ lets you query 1TB per month. If you're not doing select * on every query you should be able to do a lot with that.
What a reminder on how text is so much more efficient than video, its crazy! Could you imagine the same amount of knowledge (or dribble) but in video form? I wonder how large that would be.
That's what's so sad about youtube. 20 minute videos to encode a hundred words of usable content to get you to click on a link. The inefficiency is just staggering.
Youtube can be excellent for explanations. A picture's worth a thousand words, and you can fit a lot of decent pictures in a 20 minute video. The signal-to-noise can be high, of course.
Unfortunately even the videos that do contain helpful imagery are still dominated by huge sections of low entropy.
For example, one of the most useful applications of video over text is appliance or automotive repair, but the ideal format would be an article interspersed with short video sections, not a video with a talking head and some ~static shaky cam taking up most of the time as the individual drones on about mostly unrelated topics or unimportant details yet you can’t skip past it in case there is something actually pertinent covered in that time.
Ay, there's the rub. Professional video makes tend to be pushed into making videos for a more general audience, and niche topics are left to first-timers who haven't developed video-making skills and (tend to) go on and on.
I've produced a few videos, and I was shocked at how difficult it was to be clear. I have the same problem with writing, but at least it's restricted in a way video making isn't. There's so many ways to make a video about something, and most of them are wrong!
Average high quality 1080p60 video has bitrate of 5Mbps, which is equivalent to 120k English words per second. With average English speech being 150wpm, we end up with text being 50 thousand times more space efficient.
Converting 22GB of uncompressed text into video essay lands us at ~1PB or 1000TB.
one could use a video llm to generate the video, diagrams or the stills automatically based on the text. except when it's boardgames playthroughs or programming i just transcribe to text, summarise and read youtube video's.
How do you read youtube videos? Very curious as I have been wanting to watch PDF's scroll by slowly on a large TV. I am interested in the workflow of getting a pdf/document into a scrolling video format. These days NotebookLM may be an option but I am curious if there is something custom. If I can get it into video form (mp4) then I can even deliver it via plex.
I use yt-dlp to download the transcript, and if it's not available i can get the audio file and run it through parakeet locally. Then I have the plain text, which could be read out loud (kind of defeating the purpose), but perhaps at triple speed with a computer voice that's still understandble at that speed.
I could also summarize it with an llm. With pandoc or typst I can convert to single column or mult column pdf to print or watch on tv or my smart glasses. If I strip the vowels and make the font smaller I can fit more!
One could convert the Markdown/PDF to a very long image first with pandoc+wkhtml, then use ffmpeg to crop and move the viewport slowly over the image, this scrolls at 20 pixels per second for 30s - with the mpv player one could change speed dynamically through keys.
Alternatively one could use a Rapid Serial Visual Presentation / Speedreading / Spritz technique to output to mp4 or use dedicated rsvp program where one can change speed.
One could also output to a braille 'screen'.
Scrolling mp4 text on the the TV or Laptop to read is a good idea for my mother and her macula degeneration, or perhaps I should make use of an easier to see/read magnification browser plugin tool.
Wonder if you could turn this into a .zim file for offline browsing with an offline browser like Kiwix, etc. [0]
I've been taking frequent "offline-only-day" breaks to consolidate whatever I've been learning, and Kiwix has been a great tool for reference (offline Wikipedia, StackOverflow and whatnot).
Site does not load on Firefox console error says 'Uncaught (in promise) TypeError: can't access property "wasm", sqlite3 is null'
Guess its common knowledge that SharedArrayBuffer (SQLite wasm) does not work with FF due to Cross-Origin Attacks (i just found out ;).
Once the initial chunk of data loads the rest load almost instantly on Chrome. Can you please fix the GitHub link (current 404) would like to peak at the code. Thank you!
Strange now the first few days load (getting a new error) 'Ignoring inability to install OPFS sqlite3_vfs: Cannot install OPFS: Missing SharedArrayBuffer and/or Atomics. The server must emit the COOP/COEP response headers to enable those. See https://sqlite.org/wasm/doc/trunk/persistence.md#coop-coep'
But when go back to the 26th none of the shards will load, error out.
Using Windows 11, FF 146.0.1
Since you tested it seems its just a me problem and thanks for fixing the GitHub link
No I've seen that error too, on Safari. I think it's related to the wasm being sent with wrong headers. CF pages _headers file should be ensuring correctness. Can you try busting your cache (or wait for a new Dec 29 Data dump version coming in a couple minutes), or from incognito to see if that fixes the issue? It's possible an earlier version had stale headers or sth. Idk.
Minor bug/suggestion: right-aligned text inputs (eg the username input on the “me” page) aren’t ideal since they are often obscured by input helpers (autocomplete or form fill helper icons).
Is it a thing that the design is almost unusable on a mobile phone? The tech making this possible is beyond cool, but it's just presented in such a brutal way for phone users, even though fixing it would be super simple.
Just following the ordinary guidelines when doing responsive designs, like increasing the text size and sizes of buttons and inputs, so my fat fingers don't missklick every other try. HN has gotten better, but is still below average, hence why I thought it was some kind of aesthetic choice.
Is there a public dump of the data anywhere that this is based upon, or have they scraped it themselves?
Such as DB might be entertaining to play with, and the threadedness of comments would be useful for beginners to practise efficient recursive queries (more so than the StackExchange dumps, for instance).
Yes, you can see the download HN bash script in the repository now that simply extract the data to your local machine from BigQuery and saves it as a series of gzip JSON files
It's really a shame that comment scores are hidden forever. Would the admins consider publishing them after stories are old enough that voting is closed? It would be great to have them for archives and search indices and projects like this.
I wrote to hn@ and asked for this as a feature request:
"1. Delayed Karma Display. I understand why comment karma was hidden. I don't see the harm in un-hiding karma after some time. If not 24 hours, then 72-168 hours. This would help me read through threads with 1300 comments."
This was last January. While I asked for a few more features, it is the only one that seems essential as HN grows with massive threads.
Did anyone get a copy of this before it was pulled? If GitHub is not keen, could it be uploaded to HuggingFace or some other service which hosts large assets?
I have always known I could scrape HN, but I would much rather take a neat little package.
This is pretty neat! The calendar didn't work well for me. I could only seem to navigate by month. And when I selected the earliest day (after much tapping), nothing seemed to be updated.
Alas, HN does not belong to us, and the existence of projects like this are subject to the whims of the legal owners of HN.
From the terms of use [0]:
"""
Commercial Use: Unless otherwise expressly authorized herein or in the Site, you agree not to display, distribute, license, perform, publish, reproduce, duplicate, copy, create derivative works from, modify, sell, resell, exploit, transfer or upload for any commercial purposes, any portion of the Site, use of the Site, or access to the Site. The buying, exchanging, selling and/or promotion (commercial or otherwise) of upvotes, comments, submissions, accounts (or any aspect of your account or any other account), karma, and/or content is strictly prohibited, constitutes a material breach of these Terms of Use, and could result in legal liability.
Don't miss how this works. It's not a server-side application - this code runs entirely in your browser using SQLite compiled to WASM, but rather than fetching a full 22GB database it instead uses a clever hack that retrieves just "shards" of the SQLite database needed for the page you are viewing.
I watched it in the browser network panel and saw it fetch:
As I paginated to previous days.It's reminiscent of that brilliant SQLite.js VFS trick from a few years ago: https://github.com/phiresky/sql.js-httpvfs - only that one used HTTP range headers, this one uses sharded files instead.
The interactive SQL query interface at https://hackerbook.dosaygo.com/?view=query asks you to select which shards to run the query against, there are 1636 total.
A read-only VFS doing this can be really simple, with the right API…
This is my VFS: https://github.com/ncruces/go-sqlite3/blob/main/vfs/readervf...
And using it with range requests: https://pkg.go.dev/github.com/ncruces/go-sqlite3/vfs/readerv...
And having it work with a Zstandard compressed SQLite database, is one library away: https://pkg.go.dev/github.com/SaveTheRbtz/zstd-seekable-form...
Your page is served over sqlitevfs with Range queries? Let's try this here.
I did a similar VFS in Go. It doesn't run client-side in a browser.
But you can use it (e.g.) in a small VPS to access a multi-TB database directly from S3.
That is cool. Maybe i look at the go code
this does not caches the data right? it would always fetch from network? by any chance do you know of solution/extension that caches the data it would make it so much more efficient.
The package I'm using in the HTTP example can be configured to cache data: https://github.com/psanford/httpreadat?tab=readme-ov-file#ca...
But, also, SQLite caches data; you can simply increase the page cache.
Thanks! I'm glad you enjoyed the sausage being made. There's a little easter egg if you click on the compact disc icon.
And I just now added a 'me' view. Enter your username and it will show your comments/posts on any day. So you can scrub back through your 2006 - 2025 retrospective using the calendar buttons.
I almost got tricked into trying to figure out what was Easter eggy about August 9 2015 :-) There's a clarifying tooltip on the link, but it is mostly obscured by the image's "Archive" title attribute.
Oh, shit that was the problem! You solved the bug! I was trying to figure out why the right tooltip didn't display. A linked wrapped in an image wrapped in an easter egg! Or something. Ha, thank you. Will fix :)
edit: Fixed! Also I just pushed a new version with a Dec 29th Data Dump, so ... updates - yay!
Happy to help!
Is there anything more production grade built around the same idea of HTTP range requests like that sqlite thing? This has so much potential
Yes — PMTiles is exactly that: a production-ready, single-file, static container for vector tiles built around HTTP range requests.
I’ve used it in production to self-host Australia-only maps on S3. We generated a single ~900 MB PMTiles file from OpenStreetMap (Australia only, up to Z14) and uploaded it to S3. Clients then fetch just the required byte ranges for each vector tile via HTTP range requests.
It’s fast, scales well, and bandwidth costs are negligible because clients only download the exact data they need.
https://docs.protomaps.com/pmtiles/
PMTiles is absurdly great software.
I know right! I'd never heard of HTTP Range requests until PMTiles - but gee it's an elegant solution.
Hadn't seen PMTiles before, but that matches the mental model exactly! I chose physical file sharding over Range Requests on a single db because it felt safer for 'dumb' static hosts like CF. - less risk of a single 22GB file getting stuck or cached weirdly. Maybe it would work
My only gripe is that the tile metadata is stored as JSON, which I get is for compatibility reasons with existing software, but for e.g. a simple C program to implement the full spec you need to ship a JSON parser on top of the PMTiles parser itself.
How would you store it?
A JSON parser is less than a thousand lines of code.
And where most of CPU time will be wasted in, if you care about profiling/improving responsiveness.
At that point you're just io bound, no? I can easily parse json at 100+GB/s on commodity hardware, but I'm gonna have a much harder time actually delivering that much data to parse.
What's a better way?
That's neat, but.. is it just for cartographic data?
I want something like a db with indexes
Look into using duckdb with remote http/s3 parquet files. The parquet files are organized as columnar vectors, grouped into chunks of rows. Each row group stores metadata about the set it contains that can be used to prune out data that doesn’t need to be scanned by the query engine. https://duckdb.org/docs/stable/guides/performance/indexing
LanceDB has a similar mechanism for operating on remote vector embeddings/text search.
It’s a fun time to be a dev in this space!
> Look into using duckdb with remote http/s3 parquet files. The parquet files are organized as columnar vectors, grouped into chunks of rows. Each row group stores metadata about the set it contains that can be used to prune out data that doesn’t need to be scanned by the query engine. https://duckdb.org/docs/stable/guides/performance/indexing
But, when using this on frontend, are portions of files fetched specifically with http range requests? I tried to search for it but couldn't find details
There was a UK government GitHub repo that did something interesting with this kind of trick against S3 but I checked just now and the repo is a 404. Here are my notes about what it did: https://simonwillison.net/2025/Feb/7/sqlite-s3vfs/
Looks like it's still on PyPI though: https://pypi.org/project/sqlite-s3vfs/
You can see inside it with my PyPI package explorer: https://tools.simonwillison.net/zip-wheel-explorer?package=s...
I recovered it from https://archive.softwareheritage.org/browse/origin/directory... and pushed a fresh copy to GitHub here:
https://github.com/simonw/sqlite-s3vfs
This comment was helpful in figuring out how to get a full Git clone out of the heritage archive: https://news.ycombinator.com/item?id=37516523#37517378
Here's a TIL I wrote up of the process: https://til.simonwillison.net/github/software-archive-recove...
I also have a locally cloned copy of that repo from when it was on GitHub. Same latest commit as your copy of it.
From what I see in GitHub in your copy of the repo, it looks like you don’t have the tags.
Do you have the tags locally?
If you don’t have the tags, I can push a copy of the repo to GitHub too and you can get the tags from my copy.
I don't have the tags! It would be awesome if you could push that.
Uploaded here:
https://github.com/Quantum-Nomad/sqlite-s3vfs
Thanks for that, though actually it turns out I had them after all - I needed to run:
All the better :)
Doing all this in an hour is such a good example of how absurdly efficient you can be with LLMs.
From reading the TIL, it doesn't appear as if Simon used LLM for a large portion of what he did; only the initial suggestion to check the archive, and the web tool to make his process reproducible. Also, if you read the script from his chat with Claude code, the prompt really does the heavy lifting.
Sure, the LLM fills in all the boilerplate and makes an easy-to-use, reproducible tool with loads of documentation, and credit for that. But is it not more accurate to say that Simon is absurdly efficient, LLM or sans LLM? :)
didn't you do something similar for Datasette, Simon?
Nothing smart with HTTP range requests yet - I have https://lite.datasette.io which runs the full Python server app in the browser via WebAssembly and Pyodide but it still works by fetching the entire SQLite file at once.
oh! I must've been confused with your TIL where you linked to an explainer of this technique
https://simonwillison.net/2021/May/2/hosting-sqlite-database...
https://phiresky.github.io/blog/2021/hosting-sqlite-database...
https://news.ycombinator.com/item?id=27016630
i played around with this a while back. you can see a demo here. it also lets you pull new WAL segments in and apply them to the current database. never got much time to go any further with it than this.
https://just.billywhizz.io/sqlite/demo/#https://raw.githubus...
This is somewhat related to a large dataset browsing service a friend and I worked on a while back - we made index files, and the browser ran a lightweight query planner to fetch static chunks which could be served from S3/torrents/whatever. It worked pretty well, and I think there’s a lot of potential for this style of data serving infra.
gdal vsis3 dynamically fetches chunks of rasters from s3 using range requests. It is the underlying technology for several mapping systems.
There is also a file format to optimize this https://cogeo.org/
I tried to implement something similar to optimize sampling semi-random documents from (very) large datasets on Huggingface, unfortunately their API doesn't support range requests well.
This is pretty much well what is so remarkable about parquet files; not only do you get seekable data, you can fetch only the columns you want too.
I believe that there are also indexing opportunities (not necessarily via eg hive partitioning) but frankly - am kinda out of my depth pn it.
I want to see a bittorrent version :P
Maybe webtorrent-based?
Parquet/iceberg
A recent change is I added date spans to the shard checboxes on query view so it's easier to zero dates you want if you have that in mind. Because if your copy isn't local all those network pulls take a while.
The sequence of shards you saw when you paginated to days is faciliated by the static-manifest which maps HN item ID ranges to shards, and since IDs are increasing and a pretty good proxy of time (a "HN clock"), we can also map the shards that we cut up by ID to the time spans their items cover. An in memory table sorted by time is created from the manifest on load so we can easily look up which shard we need when you pick a day.
Funnily enough, this system was thrown off early on by a handful of "ID/timestamp" outliers in the data: items with weird future timestamps (offset by a couple years), or null timestamps. To cleanse our pure data from this noise, and restore proper adjacent-in-time shard cuts we just did a 1/99 percentile grouping and discarded the outliers leaving shards with sensible 'effective' time spans.
Sometimes we end up fetching two shards when you enter a new day because some items' comments exist "cross shard". We needed another index for that and it lives in cross-shard-index.bin which is just a list of 4-byte item IDs that have children in more than 1 shard (2-bytes), which occurs when people have the self-indulgence to respond to comments a few days after a post has died down ;)
Thankfully HN imposes a 2 week horizon for replies so there aren't that many cross-shard comments (those living outside the 2-3 days span of most, recent, shards). But I think there's still around 1M or so, IIRC.
I am curios why they don't use a single file and HTTP Range Requests instead. PMTiles (a distribution of OpenStreetMap) uses that.
This would be a neat idea to try. Want to add a PR? Bench different "hackends" to see how DuckDB, SQLite shards, or range queries perform?
I love this so much, on my phone this is much faster than actual HN (I know it's only a read-only version).
Where did you get the 22GB figure from? On the site it says:
> 46,399,072 items, 1,637 shards, 8.5GB, spanning Oct 9, 2006 to Dec 28, 2025
> Where did you get the 22GB figure from?
The HN post title (:
22GB is non-gzipped.
Hah, well that's embarrassing
The GitHub page is no longer available, which is a shame because I'm really interested in how this works.
How was the entirety of HN stored in a single SQLite database? In other words, how was the data acquired? And how does the page load instantly if there's 22GB of data having to be downloaded to the browser?
You can see it now, forgot to make it public.
- 1. download_hn.sh - bash script that queries BigQuery and saves the data to *.json.gz
- 2. etl-hn.js - does the sharding and ID -> shard map, plus the user stats shards.
- 3. Then either npx serve docs or upload to CloudFlare Pages.
The ./toool/s/predeploy-checks.sh script basically runs the entire pipeline. You can do it unattended with AUTO_RUN=true
Awesome, I'll take a look
Vfs support is amazing.
Is it possible to implement search this way?
I wonder how much smaller it could get with some compression. You could probably encode "This website hijacks the scrollbar and I don't like it" comments into just a few bits.
The hard-coded dictionary wouldn't be much stranger than Brotli's:
https://news.ycombinator.com/item?id=27160590
You can use a BPE variant like SentencePiece to identify these patterns rather than hard coding them.
Dear it is already compressed using G zip – nine for every SQLlight shard and manifest
22 GB is uncompressed and compressed the entire things about 9 GB
That's at least 45%, then you can leave out all of my comments and you're left with only 5!
It might be a neat experiment to use ai to produce canonicalized paraphrasings of HN arguments so they could be compared directly and compress well.
Guilty.
It'd be great if you could add it to Kiwix[1] somehow (not sure what the process is for that but 100rabbits figured it out for their site) - I use it all the time now that I have a dumb phone - I have the entirety of wikipedia, wiktionary and 100rabbits all offline.
https://kiwix.org/en/
I love that you have 100r.ca on that short list.
This is a good idea — we should do it.
I also want to make sure we can build this in CI. My goal is to have this updated every day using the BigQuery update process, so it becomes a 1–2 day delayed static archive of the current state of Hacker News, which is honestly very cool.
I can probably run the build for free on GitHub Actions runners, as long as the runner has about 40 GB of disk space available. If needed, I can free up space on the runner before the build starts.
I’ll also write to GitHub support and ask if they can sponsor the cost of a larger runner, mainly because I need the extra disk space to run the build reliably.
what dumb phone do you use?
and why do you want wikipedia in your pocket, but not a smartphone? where do you draw the line?
(doing a lot of work in that area, so i am asking to learn from someone who might think alike)
I use the Mudita Kompakt specifically cause it allows sideloading so I can still have a few extras. Right now I have Kiwix and Libby. It works really well.
I have a $10 a month plan from US cellular with only 2gigs so I try to keep everything offline that I can.
Honestly it's mostly the news... so I draw the line at browser, I'll never install a browser, that's basically something I can do when I sit down at a PC. I read quite a bit and I like to have the ability to look up a word or a historical event or some reference from something I read using Kiwix and it's been great for that, just needed to add a 512gb micro sd card. And Libby I just use at the gym when I'm on the treadmill.
interesting. thank you. any way i can reach out to you regardibg a project i am working on?
your input would be very valuable.
Similar to Single-page applications (SPA), single-table application (STA) might become a thing. Just a shard a table on multiple keys and serve the shards as static files, provided that the data is Ok to share, similar to sharing static html content.
[The Baked Data architectural pattern](https://simonwillison.net/2021/Jul/28/baked-data/)
do you mean single database? it'd be quite hard if not impossible to make applications using a single table (no relations). reddit did it though, they have a huge table of "things" iirc.
That is a common misconception.
> Next, we've got more than just two tables. The quote/paraphrase doesn't make it clear, but we've got two tables per thing. That means Accounts have an "account_thing" and an "account_data" table, Subreddits have a "subreddit_thing" and "subreddit_data" table, etc.
https://www.reddit.com/r/programming/comments/z9sm8/comment/...
And the important lesson from that the k/v-like aspect of it. That the "schema" is horizontal (is that a thing?) and not column-based. But I actually only read it on their blog IIRC and never even got the full details - that there's still a third ID column. Thanks for the link.
That's pretty neat!
I did something similar. I build a tool[1] to import the Project Arctic Shift dumps[2] of reddit into sqlite. It was mostly an exercise to experiment with Rust and SQLite (HN's two favorite topics). If you don't build a FTS5 index and import without WAL (--unsafe-mode), import of every reddit comment and submission takes a bit over 24 hours and produces a ~10TB DB.
SQLite offers a lot of cool json features that would let you store the raw json and operate on that, but I eschewed them in favor of parsing only once at load time. THat also lets me normalize the data a bit.
I find that building the DB is pretty "fast", but queries run much faster if I immediately vacuum the DB after building it. The vacuum operation is actually slower than the original import, taking a few days to finish.
[1] https://github.com/Paul-E/Pushshift-Importer
[2] https://github.com/ArthurHeitmann/arctic_shift/blob/master/d...
You could check out SQLite's auto_vacuum which reclaims space without rebuilding the entire db https://sqlite.org/pragma.html#pragma_auto_vacuum
I haven't tested that, so I'm not sure if it would work. The import only inserts rows, it doesn't delete, so I don't think that is the cause of fragmentation. I suspect this line in the vacuum docs:
> The VACUUM command may change the ROWIDs of entries in any tables that do not have an explicit INTEGER PRIMARY KEY.
means SQLite does something to organize by rowid and that this is doing most of the work.
Reddit post/comment IDs are 1:1 with integers, though expressed in a different base that is more friendly to URLs. I map decoded post/comment IDs to INTEGER PRIMARY KEYs on their respective tables. I suspect the vacuum operation sorts the tables by their reddit post ID and something about this sorting improves tables scans, which in turn helps building indices quickly after standing up the DB.
Holy cow, I didn't know getting reddit was that straightforward. I am building public readonly-SQL+vector databases optimized for exploring high-quality public commons with Claude Code (https://exopriors.com/scry), I so cannot wait until some funding source comes in and I can upgrade to a $1500/month Hetzner server and pay the ~$1k to embed all that.
That repo is throwing up a 404 for me.
Question - did you consider tradeoffs between duckdb (or other columnar stores) and SQLite?
No, I just went straight to sqlite. What is duckdb?
One interesting feature of DuckDB is that it can run queries against HTTP ranges of a static file hosted via HTTPS, and there's an official WebAssembly build of it that can do that same trick.
So you can dump e.g. all of Hacker News in a single multi-GB Parquet file somewhere and build a client-side JavaScript application that can run queries against that without having to fetch the whole thing.
You can run searches on https://lil.law.harvard.edu/data-gov-archive/ and watch the network panel to see DuckDB in action.
In that case, then using duckdb might be even more performant than using what we’re doing here.
It would be an interesting experiment to add the duckdb hackend
DuckDB is an open-source column-oriented Relational Database Management System (RDBMS). It's designed to provide high performance on complex queries against large databases in embedded configuration.
It has transparent compression built-in and has support for natural language queries. https://buckenhofer.com/2025/11/agentic-ai-with-duckdb-and-s...
"DICT FSST (Dictionary FSST) represents a hybrid compression technique that combines the benefits of Dictionary Encoding with the string-level compression capabilities of FSST. This approach was implemented and integrated into DuckDB as part of ongoing efforts to optimize string storage and processing performance." https://homepages.cwi.nl/~boncz/msc/2025-YanLannaAlexandre.p...
It is very similar to SQLite in that it can run in-process and store its data as a file.
It's different in that it is tailored to analytics, among other things storage is columnar, and it can run off some common data analytics file formats.
"What is duckdb?"
duckdb is a 45M dynamically-linked binary (amd64)
sqlite3 1.7M static binary (amd64)
DuckDB is a 6yr-old project
SQLite is a 25yr-old project
I like SQLite
Maybe it got nuked by MS? The rest of their repo's are up.
Hey jacquesm! No, I just forgot to make it public.
BUT I did try to push the entire 10GB of shards to GitHub (no LFS, no thanks, money), and after the 20 minutes compressing objects etc, "remote hang up unexpectedly"
To be expected I guess. I did not think GH Pages would be able to do this. So have been repeating:
on changes and first time CF Pages user here, much impressed!Pretty neat project. I never thought you could do this in the first place, very much inspiring. I've made a little project that stores all of its data locally but still runs in the browser to protect against take downs and because I don't think you should store your precious data online more than you have to, eventually it all rots away. Your project takes this to the next level.
Thanks, bud, that means a lot! Would like to see your versions of the data stored offline idea, it's very cool.
pianojacq.com
It's super simple, really, far less impressive than what you've built there.
While I suspect DuckDB would compress better, given the ubiquity of SQLite, it seems a fine standard choice.
the data is dominated by big unique TEXT columns, unsure how that can much compress better when grouped - but would be interesting to know
I was thinking more the numeric columns which have pre-built compression mechanisms to handle incrementing columns or long runs of identical values. For sure less total data than the text, but my prior is that the two should perform equivalently on the text, so the better compression on numbers should let duckdb pull ahead.
I had to run a test for myself, and using sqlite2duckdb (no research, first search hit), and using randomly picked shard 1636, the sqlite.gz was 4.9MB, but the duckdb.gz was 3.7MB.
The uncompressed sizes favor sqlite, which does not make sense to me, so not sure if duckdb keeps around more statistics information. Uncompressed sqlite 12.9MB, duckdb 15.5MB
Not the author here. I’m not sure about DuckDB, but SQLite allows you to simply use a file as a database and for archiving, it’s really helpful. One file, that’s it.
DuckDB does as well. A super simplified explanation of duckdb is that it’s sqlite but columnar, and so is better for analytics of large datasets.
The schema is this: items(id INTEGER PRIMARY KEY, type TEXT, time INTEGER, by TEXT, title TEXT, text TEXT, url TEXT
Doesn't scream columnar database to me.
At a glance, that is missing (at least) a `parent` or `parent_id` attribute which items in HN can have (and you kind of need if you want to render comments), see http://hn.algolia.com/api/v1/items/46436741
Edges are a separate table
i forgot to set repo to public. Fixed now
I tried "select * from items limit 10" and it is slowly iterating through the shards without returning. I got up to 60 shards before I stopped. Selecting just one shard makes that query return instantly. As mentioned elsewhere I think duckdb can work faster by only reading the part of a parquet file it needs over http.
I was getting an error that the users and user_domains tables aren't available, but you just need to change the shard filter to the user stats shard.
Doesn't `LIMIT` just limit the amount of rows returned, rather than the amount read & processed?
That depends on the query. SQLite tries to use LIMIT to restrict the amount of reading that it does. It is often successful at that. But some queries, by their very nature, logically require reading the whole input in order to compute the correct answer, regardless of whether or not there is a LIMIT clause.
That's what it does, but if I'm not mistaken (at least in my experience with MariaDB) it'll also return immediately once it ran up to the limit and not try to process further rows. If you have an expensive subquery in the SELECT (...) AS `column_name`, it won't run that for every row before returning the first 10 (when using LIMIT 10) unless you ORDERed BY that column_name. Other components like the WHERE clause might also require that it reads every row before finding the ten matches. So mostly yes but not necessarily
The limit clause isn't official/standard ansi sql, so it's up to the rdbms to implement. Your assumption is true for bigquery (infamously) but not true for things like snowflake, duckdb, etc.
That's odd. If it was a VFS, that's not what I'd expect would happen. Maybe it's not a VFS?
What is a VFS?
https://sqlite.org/vfs.html
While designed for OS portability, you can use it to convince SQLite to read from something other than a file on disk.
threw some heatmaps together of post volume and average score by day and time (15min intervals)
story volume (all time): https://ibb.co/pBTTRznP
average score (all time): https://ibb.co/KcvVjx8p
story volume (since 2020): https://ibb.co/cKC5d7Pp
average score (since 2020): https://ibb.co/WpN20kfh
added median too.
median score (all time): https://ibb.co/gZV5QVMG
median score (since 2020): https://ibb.co/Gfv8T7k8
This is fascinating, I love this! What do you create these heat maps with? Did you use the BigQuery data or download from the site?
thanks! i downloaded them and used python to make these
So cool! Would it be impossible fro me to use them on the Archive stats page (https://hackerbook.dosaygo.com/?view=archive) ? If you're okay with that any links/credit line details?
Totally cool if not, just super interesting!
yes, please, that'd be cool! you can link my site grimridge.net if you'd like. here are the numbers so you can plot graphs that fit the site's style:
mean (all time): https://katb.in/yutupojerux
mean (since 2020): https://katb.in/omoyibisava
median (all time): https://katb.in/kilopofivet
median (since 2020): https://katb.in/ukefetuyuhi
Added in the latest: https://hackerbook.dosaygo.com/?view=archive
Ok i will put them in the next update! Thank you
can confirm, i'm usually very generous with upvotes on sundays at noon
Looks like the repo was taken down (404).
That's too bad, I'd like to see the inner-working with a subset of data, even with placeholders for the posts and comments.
That was fast. I was looking into recent HN datasets, and they are impossible find.
Complete and continuously updated: https://play.clickhouse.com/play?user=play#U0VMRUNUIG1heCh0a...
If the last story on HN was at December 26, that is.
Continuously updated != instantly updated
Continuously would suggest to me that the data is never far out of date, and a few days might be considered far in this case.
Perhaps “regularly updated” would be less contentious wordage?
It's available on BigQuery and is updated frequently enough(daily I think).
But why would they take it down?
Sorry i just forgot to set it to public! It’s there now
Similar in spirit to a recent tool I recently posted Show HN on, https://exopriors.com/scry. You can use Claude Code to SQL+vector query HackerNews and many other high quality public commons sites, exceptionally well-indexed and usually 5+ minute query timeout limits, so you can run seriously large research queries, to rapidly refine your worldview (particular because you can do easily to EXHAUSTIVE exploration).
This looks cool but can you make a "Google Search Box" page where I don't have to sign in but can use it? It's just a bit of friction and I feel unbothered to overcome it. It's not personal to you - it's just how I feel about anything that looks unknown and interesting I just want to try, not have to sign up. For now. You know?
I like your concept of indexing high quality sources for RAG. For many queries we might not need the usual search engines.
The query tab looks quite complex with all these content shards: https://hackerbook.dosaygo.com/?view=query
I have a much simpler database: https://play.clickhouse.com/play?user=play#U0VMRUNUIHRpbWUsI...
Does your database also runs offline/locally in the browser? Seems to be the reason for the large number of shards.
You can run it locally, but it is a client-server architecture, which means that something has to run behind the browser.
Is this updated regularly? 404 on GitHub as the other comment.
With all due respect it would be great if there is an official HN public dump available (and not requiring stuff such as BigQuery which is expensive).
The BQ dataset is only ~17GB and the free tier of BQ lets you query 1TB per month. If you're not doing select * on every query you should be able to do a lot with that.
What a reminder on how text is so much more efficient than video, its crazy! Could you imagine the same amount of knowledge (or dribble) but in video form? I wonder how large that would be.
That's what's so sad about youtube. 20 minute videos to encode a hundred words of usable content to get you to click on a link. The inefficiency is just staggering.
Youtube can be excellent for explanations. A picture's worth a thousand words, and you can fit a lot of decent pictures in a 20 minute video. The signal-to-noise can be high, of course.
Unfortunately even the videos that do contain helpful imagery are still dominated by huge sections of low entropy.
For example, one of the most useful applications of video over text is appliance or automotive repair, but the ideal format would be an article interspersed with short video sections, not a video with a talking head and some ~static shaky cam taking up most of the time as the individual drones on about mostly unrelated topics or unimportant details yet you can’t skip past it in case there is something actually pertinent covered in that time.
Ay, there's the rub. Professional video makes tend to be pushed into making videos for a more general audience, and niche topics are left to first-timers who haven't developed video-making skills and (tend to) go on and on.
I've produced a few videos, and I was shocked at how difficult it was to be clear. I have the same problem with writing, but at least it's restricted in a way video making isn't. There's so many ways to make a video about something, and most of them are wrong!
Average high quality 1080p60 video has bitrate of 5Mbps, which is equivalent to 120k English words per second. With average English speech being 150wpm, we end up with text being 50 thousand times more space efficient.
Converting 22GB of uncompressed text into video essay lands us at ~1PB or 1000TB.
Cheers to you for doing the math, I hope 2026 is excellent for you!
Right? 20 years, probably 10s millions of human hours of interactions, and it’s only as much as a couple DVDs.
one could use a video llm to generate the video, diagrams or the stills automatically based on the text. except when it's boardgames playthroughs or programming i just transcribe to text, summarise and read youtube video's.
How do you read youtube videos? Very curious as I have been wanting to watch PDF's scroll by slowly on a large TV. I am interested in the workflow of getting a pdf/document into a scrolling video format. These days NotebookLM may be an option but I am curious if there is something custom. If I can get it into video form (mp4) then I can even deliver it via plex.
I use yt-dlp to download the transcript, and if it's not available i can get the audio file and run it through parakeet locally. Then I have the plain text, which could be read out loud (kind of defeating the purpose), but perhaps at triple speed with a computer voice that's still understandble at that speed. I could also summarize it with an llm. With pandoc or typst I can convert to single column or mult column pdf to print or watch on tv or my smart glasses. If I strip the vowels and make the font smaller I can fit more!
One could convert the Markdown/PDF to a very long image first with pandoc+wkhtml, then use ffmpeg to crop and move the viewport slowly over the image, this scrolls at 20 pixels per second for 30s - with the mpv player one could change speed dynamically through keys.
ffmpeg -loop 1 -i long_image.png -vf "crop=iw:ih/10:0:t*20" -t 30 -pix_fmt yuv420p output.mp4
Alternatively one could use a Rapid Serial Visual Presentation / Speedreading / Spritz technique to output to mp4 or use dedicated rsvp program where one can change speed.
One could also output to a braille 'screen'.
Scrolling mp4 text on the the TV or Laptop to read is a good idea for my mother and her macula degeneration, or perhaps I should make use of an easier to see/read magnification browser plugin tool.
Can be nice to pull a raw transcript and have it formatted as HTML (formatting/punctuation fixes applied).
Best locally of course to avoid “I burned a lake for this?” guilt.
yes, yt-dlp can download the transcript, and if it's not available i can get the audio file and run it through parakeet locally.
Wonder if you could turn this into a .zim file for offline browsing with an offline browser like Kiwix, etc. [0]
I've been taking frequent "offline-only-day" breaks to consolidate whatever I've been learning, and Kiwix has been a great tool for reference (offline Wikipedia, StackOverflow and whatnot).
[0] https://kiwix.org/en/the-new-kiwix-library-is-available/
Oh that's a cool idea. If you want to take a crack at writing the script, the repo is open!
Oh this should TOTALLY be available to those who are scrolling through sources on the Kiwix app!
Site does not load on Firefox console error says 'Uncaught (in promise) TypeError: can't access property "wasm", sqlite3 is null'
Guess its common knowledge that SharedArrayBuffer (SQLite wasm) does not work with FF due to Cross-Origin Attacks (i just found out ;).
Once the initial chunk of data loads the rest load almost instantly on Chrome. Can you please fix the GitHub link (current 404) would like to peak at the code. Thank you!
Damn. Will try to fix for FF.
edit: I just tested with FF latest, seems to be working.
Strange now the first few days load (getting a new error) 'Ignoring inability to install OPFS sqlite3_vfs: Cannot install OPFS: Missing SharedArrayBuffer and/or Atomics. The server must emit the COOP/COEP response headers to enable those. See https://sqlite.org/wasm/doc/trunk/persistence.md#coop-coep'
But when go back to the 26th none of the shards will load, error out.
Using Windows 11, FF 146.0.1
Since you tested it seems its just a me problem and thanks for fixing the GitHub link
No I've seen that error too, on Safari. I think it's related to the wasm being sent with wrong headers. CF pages _headers file should be ensuring correctness. Can you try busting your cache (or wait for a new Dec 29 Data dump version coming in a couple minutes), or from incognito to see if that fixes the issue? It's possible an earlier version had stale headers or sth. Idk.
link no workie: https://github.com/DOSAYGO-STUDIO/HackerBook
Fixed now. Forgot to make public. I also added a script:
To let you download the entire site over HTTPS so you don't need to "build it" by running the pipeline.That way it's truly offline.
Absolutely love this!! I have been analyzing a lot of HN data lately [1] so I backtested my hypothesis on your dataset and ran some stats: https://philippdubach.com/standalone/hackerbook-stats/
[1]https://news.ycombinator.com/item?id=46434575
That is so cool! I love that this passion fun project inspired and helped your paper. So cool!
The link seems to be down, was it taken down?
Probably just forgot to make it public.
Awesome work.
Minor bug/suggestion: right-aligned text inputs (eg the username input on the “me” page) aren’t ideal since they are often obscured by input helpers (autocomplete or form fill helper icons).
Is it a thing that the design is almost unusable on a mobile phone? The tech making this possible is beyond cool, but it's just presented in such a brutal way for phone users, even though fixing it would be super simple.
Really? Let me know how I can help. What would you like to see fixed?
Just following the ordinary guidelines when doing responsive designs, like increasing the text size and sizes of buttons and inputs, so my fat fingers don't missklick every other try. HN has gotten better, but is still below average, hence why I thought it was some kind of aesthetic choice.
I tried to keep to HN look. But I’m not a mobile design expert. I will give it a once over see if i can make it better for you
Is there a public dump of the data anywhere that this is based upon, or have they scraped it themselves?
Such as DB might be entertaining to play with, and the threadedness of comments would be useful for beginners to practise efficient recursive queries (more so than the StackExchange dumps, for instance).
While not a dump per se, there is an API where you can get HN data programmatically, no scraping needed.
https://github.com/HackerNews/API
Yes, you can see the download HN bash script in the repository now that simply extract the data to your local machine from BigQuery and saves it as a series of gzip JSON files
Ah, the repo was 404ing for me last time I checked (seems fine now) so I couldn't inspect that. I'll have a play later.
It's really a shame that comment scores are hidden forever. Would the admins consider publishing them after stories are old enough that voting is closed? It would be great to have them for archives and search indices and projects like this.
I wrote to hn@ and asked for this as a feature request:
"1. Delayed Karma Display. I understand why comment karma was hidden. I don't see the harm in un-hiding karma after some time. If not 24 hours, then 72-168 hours. This would help me read through threads with 1300 comments."
This was last January. While I asked for a few more features, it is the only one that seems essential as HN grows with massive threads.
Fear not. I have a collaborative project designed to address this.
They're referring to scores on individual COMMENTS - this information isn't available via the HN Firebase API.
The only way you could theoretically extract everyone's comment scores (at least the top level ones) would be like this if you're a complete madman:
1. Wait 48 hours so the article is effectively dead
2. Post a new comment using an account called ThePresident
3. Create a swarm of a thousand shill user accounts called Voter1, Voter2, etc.
4. Use a single account at a time and upvote ThePresident
5. Recheck the page to see if ThePresident has moved above a user(s) post
6. Record the score for that user and assign it to the tracked story's history
7. Repeat from (4)
I know that! I have a collaborative project to make it sort of available.
But the idea I have is not like that at all - it's much nicer on everyone's ethics. Stay tuned! :)
1 hour passed and it's already nuked?
Thank you btw
Did anyone get a copy of this before it was pulled? If GitHub is not keen, could it be uploaded to HuggingFace or some other service which hosts large assets?
I have always known I could scrape HN, but I would much rather take a neat little package.
This is pretty neat! The calendar didn't work well for me. I could only seem to navigate by month. And when I selected the earliest day (after much tapping), nothing seemed to be updated.
Nonetheless, random access history is cool.
Cna you let me know? I'm sure there's some weirdness lurking there and I want to smooth it out. Calendar is essential.
Neat. I keep wanting to build something like this for GitHub audit logs, but at ~5 tb, probably a little much
Nice. I wonder if there’s any way to quickly get a view for a whole year.
You mean like stuff ranked per year?
Edit: Good idea! I implemented a "year" selector so all main views (front/show/ask/jobs) will be from that entire year rather than just a single day.
Apparently the comment counts are only the top-level comments?
It would be nice for the thread pages to show a comment count.
Yes, because comments in a thread can span shards. It’s just a bit too heavy to add comment counts of an entire thread. So I give a low bound ha ha
Suddenly occurs to me that it would be neat to pair a small LLM (3-7B) with an HN dataset
Does the SQLite version of this already exist somewhere? The github link on the footer of the page fails for me.
Link appears broken
confirmed - I wonder what happened?
This would be awesome as a cross platform app.
Good idea. HN.exe
How do I download it? That repo is a 404.
22gb for mostly text? tried loading the site, it's pretty slow. curious how the query performance is with this much data in sqlite
Beautiful !
2026 prayer: for all you AI junkies—please don’t pollute H/N with your dirty AI gaming.
Don’t bot posts, comments, or upvote/downvote just to maximize karma. Please.
We can’t identify anymore who’s a bot and who’s human. I just want to hang out with real humans here.
Hahaha, now you can be prepared for the apocalypse when the internet disappears. ;)
How much space is needed? ...for the data .... Im wondering if it would work on a tablet? ....
~9GB gzipped.
FYI I did NOT see the size info in the title. Impossible to edit / delete my comment now ........
Alas, HN does not belong to us, and the existence of projects like this are subject to the whims of the legal owners of HN.
From the terms of use [0]:
"""
Commercial Use: Unless otherwise expressly authorized herein or in the Site, you agree not to display, distribute, license, perform, publish, reproduce, duplicate, copy, create derivative works from, modify, sell, resell, exploit, transfer or upload for any commercial purposes, any portion of the Site, use of the Site, or access to the Site. The buying, exchanging, selling and/or promotion (commercial or otherwise) of upvotes, comments, submissions, accounts (or any aspect of your account or any other account), karma, and/or content is strictly prohibited, constitutes a material breach of these Terms of Use, and could result in legal liability.
"""
[0] https://www.ycombinator.com/legal/#tou
But is this really a commercial use? There doesn’t seem to be any intention of monetising this so I guess it doesn’t as specify commercial?