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url string |
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https://cec.aau.ac.ae/ar/units/admission-and-registration/contact-us |
https://cbdreviewerp.web.app/wesep/318.html |
https://cfy.ksu.edu.sa/ar/node/1044 |
https://crystalfoto.pl/%D8%A5%D8%B9%D8%A7%D8%AF%D8%A9/%D8%AA%D8%AF%D9%88%D9%8A%D8%B1/%D8%B3%D8%AD%D9%82/%D9%81%D9%8A/%D8%B9%D9%85%D9%84%D9%8A%D8%A9/%D8%A7%D9%84%D8%B7%D8%AD%D9%86/23230.html |
https://cbdreviewphq.web.app/zyvih/cbd-699.html |
https://decoration.7olm.org/t82-topic |
https://defense-arab.com/vb/members/36498/ratings?reaction_category_id=1 |
https://chilchil.asia/Jul-29/4978.html |
https://dinasoor.tech/tag/%D9%88%D8%B1%D8%AF-%D8%A8%D9%8A%D8%B1%D9%81%D9%83%D8%AA-%D8%A8%D8%B1%D9%86%D8%A7%D9%85%D8%AC-%D9%85%D8%B9%D8%A7%D9%84%D8%AC%D8%A9-%D9%86%D8%B5%D9%88%D8%B5/ |
https://chilchil.asia/Jul-17/24146.html |
https://darek-bus.pl/27455/32RXhi1/%D9%83%D8%B3%D8%A7%D8%B1%D8%A9_%D8%A7%D9%84%D8%AD%D8%AC%D8%B1_%D8%A7%D9%84%D8%AC%D9%8A%D8%B1%D9%8A_%D8%A7%D9%84%D9%85%D8%AA%D9%86%D9%82%D9%84%D8%A9_%D8%A7%D9%84%D8%A3%D8%B1%D8%A8%D8%B9%D8%A7%D8%A1_%D9%84%D9%84%D8%A8%D9%8A%D8%B9_%D9%81%D9%8A_%D8%AC%D9%86%D9%88%D8%A8_%D8%A3%D9%81%D8%B1%... |
https://diwanegypt.com/product/%D8%AA%D9%88%D9%82%D9%81-%D8%B9%D9%86-%D8%A7%D8%B1%D8%B6%D8%A7%D8%A1-%D8%A7%D9%84%D8%A7%D8%AE%D8%B1%D9%8A%D9%86/ |
https://ela5bar.com/2021/09/18/%D8%A7%D9%84%D8%A8%D8%B1%D9%84%D9%85%D8%A7%D9%86-%D8%A7%D9%84%D8%B9%D8%B1%D8%A8%D9%8A-%D9%8A%D8%A4%D9%83%D8%AF-%D8%B6%D8%B1%D9%88%D8%B1%D8%A9-%D8%A7%D9%84%D8%AA%D9%83%D8%A7%D8%AA%D9%81-%D8%A7%D9%84/ |
https://elibrary.mara.gov.om/mktbat-mezab/alkhzantt-alaamtt/ktab/?id=2906 |
https://elibrary.mara.gov.om/mktbat-mezab/alkhzantt-alaamtt/ktab/?id=3176 |
https://elibrary.mara.gov.om/mktbat-mezab/alkhzantt-alaamtt/ktab/?id=3473 |
https://elfagr.org/4072012 |
https://eljarida.com/news/5243 |
https://fawasildesign.com/zZWKRo |
https://forum.rjeem.com/f13-35.html |
https://elryad.com/ar/milo-portfolio/%D8%AA%D8%B5%D9%85%D9%8A%D9%85-%D9%85%D9%88%D9%82%D8%B9-%D8%A7%D8%AF%D9%88%D8%A7%D8%AA-%D8%B5%D8%AD%D9%8A%D8%A9/ |
https://g0ld0.com/product/xerjoff-join-the-club-don-u-edp-100-ml/ |
https://education-ksa.com/forumdisplay.php?s=79843aeaa5325499e650923c013453df&f=19 |
https://humum.net/?p=28316 |
https://halageorgia.com/%D9%82%D9%86%D8%A8%D9%84%D9%87-%D9%85%D9%88%D9%82%D9%88%D8%AA%D9%87-%D9%81%D9%8A-%D8%A8%D8%A7%D8%AA%D9%88%D9%85%D9%8A-%D8%A7%D9%84%D9%85%D9%81%D8%B1%D9%82%D8%B9%D8%A7%D8%AA-%D8%AA%D8%B9%D9%84%D9%86/ |
https://historiaeconomica.es/Barite-6152-JWBGJ2.html |
https://hadarat.net/post/12167/%D8%AD%D9%85%D9%80-%D9%80%D8%A7%D8%B3-%D9%85%D8%AA%D9%85%D8%A7%D8%B3%D9%83%D8%A9-%D9%88%D9%81%D8%AA%D8%AD-%D9%85%D9%86%D9%82%D8%B3%D9%85%D8%A9 |
https://imazighen.univanet.com/private.php?s=d555dd3f5d41a71916508a8af3e446c5 |
https://iamblond.ru/%D9%81%D9%8A%D9%84%D9%85%20%D9%83%D8%B1%D8%AA%D9%88%D9%86%20%D8%B9%D9%84%D8%A7%D8%A1%20%D8%A7%D9%84%D8%AF%D9%8A%D9%86%20%D9%88%D8%B9%D9%88%D8%AF%D8%A9%20%D8%AC%D8%B9%D9%81%D8%B1%20%D9%85%D8%AF%D8%A8%D9%84%D8%AC%20%D8%B9%D8%B1%D8%A8%D9%8A |
https://jadehiran.com/archives/tag/%D9%85%D8%AD%D9%85%D8%AF-%D8%B9%D9%84%D9%8A-%D9%86%D8%AC%D9%81%D9%8A |
https://istefada.com/%D8%AA%D9%86%D8%B2%D9%8A%D9%84-%D9%88%D8%AA%D8%AD%D9%85%D9%8A%D9%84-%D9%83%D8%AA%D8%A7%D9%90%D8%A8-%D9%85%D9%86-%D9%8A%D8%A3%D9%83%D9%84-%D9%85%D9%84%D8%AD%D9%89-%D8%AA%D9%8A%D8%A7%D9%85%D8%A7%D8%AA/ |
https://jaidpub.org/ |
https://ida2at.org/news/2021/08/29/21022/------ |
https://jpfmjazan.com/%D9%83%D9%85_%D8%AA%D8%A7%D8%B1%D9%8A%D8%AE_%D8%A7%D9%84%D9%8A%D9%88%D9%85_%D8%A7%D9%84%D9%88%D8%B7%D9%86%D9%8A_%D8%A7%D9%84%D8%B3%D8%B9%D9%88%D8%AF%D9%8A_%D8%A8%D8%A7%D9%84%D9%87%D8%AC%D8%B1%D9%8A/ |
https://jelle-shop.com/%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD-%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD/c598890513 |
https://janoubia.com/2019/03/23/%D9%88%D8%B2%D8%A7%D8%B1%D8%A9-%D8%A7%D9%84%D9%85%D8%A7%D9%84-%D8%B1%D8%AF%D8%A7-%D8%B9%D9%84%D9%89-%D9%85%D8%A4%D8%B3%D8%B3%D8%A9-%D8%A7%D9%84%D9%83%D9%87%D8%B1%D8%A8%D8%A7%D8%A1-%D9%81%D8%AA%D8%AD/ |
ERROR: type should be string, got "https://kulalsalafiyeen.com/vb/tags.php?s=022fd3b13c5f639cdd03c648179e4e2f&tag=%C7%E1%DA%CB%ED%E3%ED%E4" |
https://jan-violations.com/news/%D9%85%D9%82%D8%AA%D9%84-%D8%B9%D9%8A%D8%B3%D9%89-%D8%AD%D9%85%D9%8A%D8%AF%D9%8A-%D9%88%D8%A5%D8%B5%D8%A7%D8%A8%D8%A9-%D8%AE%D8%A7%D9%84%D8%AF-%D8%A7%D9%84%D8%A3%D8%B9%D8%B1%D8%A7%D8%AC-%D9%88/ |
https://kuwaityiat.net/blog/category/%D8%BA%D8%B3%D8%A7%D9%84%D8%A7%D8%AA/ |
https://kulalsalafiyeen.com/vb/misc.php?s=2045804357a6cdef3f5279149db3c246&do=bbcode |
https://kuwaityiat.net/blog/tag/%D8%B5%D9%8A%D8%A7%D9%86%D8%A9-%D8%AA%D9%83%D9%8A%D9%8A%D9%81-%D9%85%D8%B1%D9%83%D8%B2%D9%8A-%D8%A7%D9%84%D8%AF%D8%B9%D9%8A%D8%A9/ |
https://locateinkuwait.com/%D8%A3%D8%B9%D9%84%D8%A7%D9%86%D8%A7%D8%AA/%D9%85%D9%87%D9%86-%D9%88%D9%85%D9%82%D8%A7%D9%88%D9%84%D8%A7%D8%AA/194-%D9%84%D9%84%D8%A8%D9%8A%D8%B9-%D8%B4%D9%82%D8%A9-%D8%AA%D9%85%D9%84%D9%8A%D9%83-%D8%AD%D8%AF%D8%A7%D8%A6%D9%82-%D8%A7%D9%84%D9%82%D8%A8%D8%A9-%D8%B4-%D8%A8%D9%88%D8%B1-%D8%B3%D8... |
https://m.iium.edu.my/ar/news/talk-organized-by-iium-siber-sejahtera-and-bank-negara-malaysia-on-financial-crime-awareness |
https://makhtota.ksu.edu.sa/makhtota/2741/8 |
https://makhtota.ksu.edu.sa/makhtota/2545/6 |
https://maintenance-company-emirates.com/tag/%D9%85%D8%B5%D8%A7%D9%86%D8%B9-%D8%AD%D8%AC%D8%B1-%D8%B7%D8%A8%D9%8A%D8%B9%D9%8A/ |
https://dev1.kataeb.org/%D8%B9%D8%A8%D8%AF%D8%A7%D9%84%D9%84%D9%87-%D8%A7%D9%86%D9%81%D8%AA%D8%A7%D8%AD-%D8%A7%D9%84%D8%AF%D9%88%D9%84-%D8%A7%D9%84%D8%B9%D8%B1%D8%A8%D9%8A%D8%A9-%D8%B9%D9%84%D9%89-%D9%84%D8%A8%D9%86%D8%A7%D9%86-%D9%84%D9%8A%D8%B3-%D9%82%D8%B1%D9%8A%D8%A8%D8%A7/2021/10/14/%D9%85%D8%AD%D9%84%D9%8A%D8%A7%... |
https://lingolets.com/arabic-to-english/%D8%A3%D8%AC%D8%B1%D9%89 |
https://maktabeti.com/tag/%D8%B1%D8%A7%D8%AA%D8%A8/ |
https://mart.ps/325-leather-watches |
https://midad.com/recitation/201375/%D8%B3%D9%88%D8%B1%D8%A9-%D8%A7%D9%84%D8%B9%D9%86%D9%83%D8%A8%D9%88%D8%AA |
https://mediacenter.ps/archives/tag/%D8%A7%D9%84%D8%B1%D8%A7%D8%AD%D9%84-%D8%A8%D9%88%D8%B1%D9%82%D9%8A%D8%A8%D8%A9 |
https://media.sn4hr.org/blog/2019/04/30/59569/ |
https://madany.ahlamontada.com/t6893-topic |
https://mawdea.com/28606/%D8%B1%D8%B3%D8%A7%D8%A6%D9%84-%D8%B1%D9%88%D9%85%D8%A7%D9%86%D8%B3%D9%8A%D8%A9-%D9%85%D8%B3%D8%A7%D8%A6%D9%8A%D8%A9-%D9%84%D8%AD%D8%A8%D9%8A%D8%A8%D8%AA%D9%8A/ |
https://misralbalad.com/%D8%B9%D8%B7%D9%84-%D9%85%D9%81%D8%A7%D8%AC%D8%A6-%D8%A8%D9%80-%D9%81%D9%8A%D8%B3-%D8%A8%D9%88%D9%83-%D9%88%D9%88%D8%A7%D8%AA%D8%B3%D8%A7%D8%A8-%D9%88%D8%A7%D9%86%D8%B3%D8%AA%D8%AC%D8%B1%D8%A7%D9%85/ |
https://misralbalad.com/338585-2/ |
https://mirosaintgermainenlaye.fr/%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD-%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD/23935/%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD.html |
https://mnoaat.com/%D9%88%D8%B5%D9%81%D8%A7%D8%AA-%D8%B7%D8%A8%D8%AE/1868/%D8%B7%D8%B1%D9%8A%D9%82%D8%A9-%D8%B9%D9%85%D9%84-%D8%A7%D9%84%D9%83%D8%B4%D8%B1%D9%89/ |
https://nala4u.com/2021/02/20/%D9%87%D8%AF%D9%86%D8%A9-%D9%85%D8%B9-%D8%A7%D9%84%D8%B0%D8%A7%D8%AA/ |
https://new.yallashootkora.com/2021/04/21-4-2021_4.html |
https://news.un.org/ar/tags/technical-migrate/date/2015-03 |
https://oudah.net/%D9%81%D9%8A%D8%AA%D9%86%D8%A7%D9%85%D9%8A-%D8%AC%D8%A8%D9%84%D9%8A-%D8%B3%D9%88%D8%A8%D8%B1/p358777781 |
https://poetsgate.com/poem.php?pm=211553&name=%D8%B9%D9%84%D8%A7%D8%A1%20%D8%A7%D9%84%D8%A3%D8%AF%D9%8A%D8%A8&Title=%D9%85%D9%86%20%D9%82%D8%A7%D9%84%20%D8%A7%D9%86%D9%8A%20%D8%B0%D8%A7%D8%AA%20%D9%8A%D9%88%D9%85%20%D8%A7%D8%B9%D8%B4%D9%82 |
https://obsdarwin.nl/Jun-03/33883.html |
https://projectssolutions.onepeterson.com/ar/industries/agriculture |
https://optionsjehi.web.app/badini34274qyz/dyp.html |
https://optionsjehi.web.app/gruska18329rapu/xuva.html |
https://ramadan2021.alarab.com/v107715-_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD_29_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD_HD_292020 |
https://recas.ru/ar/universities-of-russia/sports-universities/582-far-eastern-state-academy-of-physical-culture |
https://rewayat.club/novel/elite-cultivater |
https://ramadan2021.alarab.com/v112487-_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD_129_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD_%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF%BF%BD%EF... |
https://osp-kwiatowe.pl/02_Dec_2006_2625.html |
https://salleeshop.com/product/dress-pimkie/ |
https://saudishift.com/media/736219985465783376 |
https://sa.made-in-china.com/co_rainbowtraco/product_PDA-LCD-Display-for-Mio-136-138-139-268-269-336-339-558-NL2432HC22-23B_hehooeirg.html |
https://sollywood.com.sa/2018/05/06/a-215/ |
https://st-takla.org/General-Knowledge-Articles/07-Calendars/1200-1299/year-1277.html |
https://sanews.pythonanywhere.com/post/954/ |
https://st-takla.org/Saints/Coptic-Orthodox-Saints-Biography/Coptic-Saints-Story_774.html |
https://ssrcaw.org/ar/show.art.asp?t=2&aid=731994 |
https://st-takla.org/books/fr-tadros-malaty/patristic-social-line/wars.html |
https://ralqalam.com/article/%D9%85%D9%8E%D8%AB%D9%8E%D9%84%D9%8F-%D8%A7%D9%84%D9%83%D9%84%D9%85%D8%A9-%D8%A7%D9%84%D8%B7%D9%8A%D8%A8%D8%A9-%D9%88%D8%A7%D9%84%D9%83%D9%84%D9%85%D8%A9-%D8%A7%D9%84%D8%AE%D8%A8%D9%8A%D8%AB%D8%A9-%D9%81%D9%8A-%D8%B3%D9%88%D8%B1%D8%A9-%D8%A5%D8%A8%D8%B1%D8%A7%D9%87%D9%8A%D9%85 |
https://stars-apps.com/ |
https://taqadoumi.net/2020/07/11/%D8%B9%D8%A7%D8%AC%D9%84-%D8%B1%D8%A6%D9%8A%D8%B3-%D9%84%D8%AC%D9%86%D8%A9-%D8%A7%D9%84%D8%B9%D8%AF%D9%84-%D9%8A%D8%B1%D8%AF-%D8%B9%D9%84%D9%89-%D8%AA%D8%B5%D8%B1%D9%8A%D8%AD%D8%A7%D8%AA-%D8%A8/ |
https://sudanewsnow.com/159075/ |
https://st-takla.org/books/pope-sheounda-iii/resurrection/message.html |
https://studiosday.web.app/ide-10-ja.html |
https://torath.gov.ae/module/branches/all/3 |
https://tv.sayidaty.net/node/11996/%D8%A3%D8%B2%D9%8A%D8%A7%D8%A1/%D8%A7%D9%84%D8%A8%D9%84%D9%88%D8%BA%D8%B1-%D9%83%D8%B1%D9%8A%D8%B3%D8%AA%D9%8A%D9%86%D8%A7-%D9%83%D8%B1%D9%85-%D8%B1%D9%85%D9%8A%D8%A7-%D8%AA%D9%81%D8%AA%D8%AD-%D8%A3%D8%A8%D9%88%D8%A7%D8%A8-%D8%AE%D8%B2%D8%A7%D9%86%D8%AA%D9%87%D8%A7-%D9%88%D8%AA%D9%83%... |
https://thezunguness.co.za/%D8%B5%D9%88%D8%B1/%D9%85%D8%AD%D8%A7%D9%85%D9%84/%D9%83%D8%B3%D8%A7%D8%B1%D8%A9/%D8%A7%D9%84%D9%81%D9%83/39749.html |
https://sudanewsnow.com/157293/ |
https://theaqd.com/%D8%B5%D9%8A%D8%BA%D8%A9-%D8%A7%D9%84%D8%B9%D9%82%D8%AF-%D9%81%D9%8A-%D8%A7%D9%84%D8%B9%D9%84%D8%A7%D9%82%D8%A7%D8%AA-%D8%A7%D9%84%D8%AA%D8%B9%D8%A7%D9%82%D8%AF%D9%8A%D8%A9/ |
https://topbinibrh.web.app/bumpaus11151xek/rywa.html |
https://wafaamagazine.org/archives/11300 |
https://www.adsgal.com/author/evodak-konaklama/?type=ads |
https://www.adsgal.com/search-results/?cat_id=102 |
https://www.adtv.ae/video/27679972/Miss-Understand |
https://video.marebpress.net/articles.php?id=42319 |
https://www.218tv.net/%D8%AA%D8%A3%D9%8A%D9%8A%D8%AF-%D9%8A%D9%88%D9%86%D8%A7%D9%86%D9%8A-%D9%84%D9%85%D8%B9%D8%A7%D8%B1%D8%B6%D8%A9-%D8%A7%D9%84%D9%86%D9%88%D8%A7%D8%A8-%D8%B9%D9%84%D9%89-%D9%85%D8%B0%D9%83%D8%B1/ |
URL Atlas
257,548,097,528 URLs from 105 web corpora, each kept as its own separately-loadable config, plus the raw source dumps two of them were extracted from. 4.35 TiB across 52,244 files.
This is the input side of a URL-compression corpus: every source reduced to its URL column and nothing else. It is deliberately not deduplicated or merged — sources are kept intact and overlapping so you can measure what each one contributes, pick the subset you want, and dedup on your own terms.
Quick start
Nothing here is small, so always name a config — there is no default, which is the point:
from datasets import load_dataset
ds = load_dataset("ks46/url-atlas", "wiki-urls", split="train", streaming=True)
next(iter(ds)) # {'url': 'https://...'}
Grab one source without the datasets library:
hf download ks46/url-atlas --repo-type dataset \
--include 'data/hackernews-urls/*' --local-dir ./url-atlas
Query it in place with DuckDB:
SELECT url FROM read_parquet(
'hf://datasets/ks46/url-atlas/data/finemath_urls_4plus/*.parquet') LIMIT 10;
What is in here
| URLs | sources | |
|---|---|---|
| Original extractions (not published anywhere else) | 5,647,739,601 | 6 |
| Common Crawl columnar-index sweep | 123,873,807,225 | 47 |
| Public corpora projected to their URL column | 128,026,550,702 | 52 |
| total | 257,548,097,528 | 105 |
Layout
data/<source>/*.parquet one nullable `url` string column, zstd
raw/wiki/*.sql.gz 890 Wikimedia `externallinks` SQL dumps
raw/hackernews/*.parquet 49,268,259 Hacker News items, full schema
source-notes/<source>.md provenance and preprocessing, one file per source
raw/ is the unprocessed source for two of the extractions, kept so the
extraction is reproducible and auditable rather than something you have to take
on faith. raw/wiki is the input to data/wiki-urls; raw/hackernews is the
input to data/hackernews-urls and is a config in its own right
(hackernews-raw) since it carries titles, scores, timestamps and comment text.
The original extractions
These exist nowhere else and are the reason this is a dataset rather than a mirror:
| source | URLs | files | on disk | derived from |
|---|---|---|---|---|
reddit-submissions |
3,210,035,355 | 5783 | 37.6 GiB | open-index/arctic |
reddit-comments |
1,341,471,971 | 26031 | 15.6 GiB | open-index/arctic |
wiki-urls |
982,404,166 | 1039 | 10.1 GiB | — |
reddit-wenknow |
80,696,485 | 797 | 1.3 GiB | wenknow/reddit_dataset_888 |
archive-text-urls |
24,049,508 | 119 | 0.1 GiB | Navanjana/ARCHIVE-TEXT-URLS |
hackernews-urls |
9,082,116 | 2 | 0.1 GiB | — |
wiki-urls— every outbound link in 1,087 Wikimedia wikis, not just English, parsed from theexternallinksSQL dumps. Since MediaWiki 1.41 that table stores a reversed-domain index plus path rather than the URL an editor typed, so these are canonical reconstructions: host lowercased, userinfo gone.reddit-comments/reddit-submissions— URLs scraped out of comment markdown and out of submissions (the posted link plus links in the self-text). 1.05 TiB of comment bodies reduce to the links inside them.hackernews-urls— submitted links plus URLs found in comment HTML.archive-text-urls— URLs scraped from plain-text archives.
Extraction is regex-based and three details do most of the damage if you get
them wrong, so they are worth stating: balanced parentheses are kept (drop
them and /wiki/Mercury_(element) silently becomes the real-but-different
/wiki/Mercury; 8.4% of Wikipedia URLs contain parens); HTML entities are
decoded before trailing punctuation is trimmed (trim first and &
leaves & welded on); and a closing bracket is removed only when the URL
contains no opener.
The Common Crawl sweep
47 crawls of Common Crawl's columnar index, read directly rather than via a derived corpus. Novelty is concentrated in recent crawls — 2014 contributes 19–25% new URLs against the rest of this dataset while 2025 contributes 62–65%, because the derived corpora below were built from historical snapshots and none of them covers 2025.
| source | URLs | files | on disk | derived from |
|---|---|---|---|---|
cc-2014-42 |
3,722,131,678 | 300 | 14.3 GiB | Common Crawl columnar index CC-MAIN-2014-42 |
cc-2014-23 |
3,608,720,876 | 300 | 17.6 GiB | Common Crawl columnar index CC-MAIN-2014-23 |
cc-2022-21 |
3,449,824,215 | 300 | 35.4 GiB | Common Crawl columnar index CC-MAIN-2022-21 |
cc-2023-40 |
3,445,015,037 | 300 | 36.5 GiB | Common Crawl columnar index CC-MAIN-2023-40 |
cc-2022-49 |
3,381,612,888 | 300 | 35.0 GiB | Common Crawl columnar index CC-MAIN-2022-49 |
cc-2023-50 |
3,354,042,124 | 300 | 35.6 GiB | Common Crawl columnar index CC-MAIN-2023-50 |
cc-2018-30 |
3,263,958,200 | 300 | 31.4 GiB | Common Crawl columnar index CC-MAIN-2018-30 |
cc-2018-13 |
3,232,738,018 | 300 | 31.0 GiB | Common Crawl columnar index CC-MAIN-2018-13 |
cc-2023-06 |
3,189,578,207 | 300 | 33.4 GiB | Common Crawl columnar index CC-MAIN-2023-06 |
cc-2022-40 |
3,176,763,048 | 300 | 33.1 GiB | Common Crawl columnar index CC-MAIN-2022-40 |
cc-2017-04 |
3,146,467,312 | 300 | 25.5 GiB | Common Crawl columnar index CC-MAIN-2017-04 |
cc-2021-17 |
3,134,424,806 | 300 | 31.8 GiB | Common Crawl columnar index CC-MAIN-2021-17 |
cc-2023-14 |
3,118,633,413 | 300 | 32.8 GiB | Common Crawl columnar index CC-MAIN-2023-14 |
cc-2022-27 |
3,109,609,672 | 300 | 32.3 GiB | Common Crawl columnar index CC-MAIN-2022-27 |
cc-2024-10 |
3,106,525,566 | 300 | 33.7 GiB | Common Crawl columnar index CC-MAIN-2024-10 |
cc-2018-26 |
3,069,414,247 | 300 | 29.1 GiB | Common Crawl columnar index CC-MAIN-2018-26 |
cc-2018-43 |
3,041,784,523 | 300 | 29.3 GiB | Common Crawl columnar index CC-MAIN-2018-43 |
cc-2025-05 |
3,031,278,337 | 300 | 33.2 GiB | Common Crawl columnar index CC-MAIN-2025-05 |
cc-2017-22 |
2,967,174,165 | 300 | 25.9 GiB | Common Crawl columnar index CC-MAIN-2017-22 |
cc-2017-17 |
2,942,879,945 | 300 | 25.2 GiB | Common Crawl columnar index CC-MAIN-2017-17 |
cc-2017-51 |
2,914,004,423 | 300 | 27.5 GiB | Common Crawl columnar index CC-MAIN-2017-51 |
cc-2024-26 |
2,798,047,026 | 300 | 31.0 GiB | Common Crawl columnar index CC-MAIN-2024-26 |
cc-2024-18 |
2,786,800,057 | 300 | 30.7 GiB | Common Crawl columnar index CC-MAIN-2024-18 |
cc-2021-10 |
2,736,749,883 | 300 | 28.1 GiB | Common Crawl columnar index CC-MAIN-2021-10 |
cc-2020-45 |
2,731,063,243 | 300 | 27.5 GiB | Common Crawl columnar index CC-MAIN-2020-45 |
cc-2018-34 |
2,686,323,358 | 300 | 26.1 GiB | Common Crawl columnar index CC-MAIN-2018-34 |
cc-2025-08 |
2,679,706,056 | 300 | 29.8 GiB | Common Crawl columnar index CC-MAIN-2025-08 |
cc-2014-15 |
2,641,371,316 | 300 | 14.3 GiB | Common Crawl columnar index CC-MAIN-2014-15 |
cc-2024-51 |
2,635,362,356 | 300 | 29.4 GiB | Common Crawl columnar index CC-MAIN-2024-51 |
cc-2021-21 |
2,632,142,465 | 300 | 27.2 GiB | Common Crawl columnar index CC-MAIN-2021-21 |
cc-2025-43 |
2,616,796,857 | 300 | 29.8 GiB | Common Crawl columnar index CC-MAIN-2025-43 |
cc-2022-33 |
2,588,690,250 | 300 | 27.5 GiB | Common Crawl columnar index CC-MAIN-2022-33 |
cc-2019-39 |
2,561,062,912 | 300 | 25.9 GiB | Common Crawl columnar index CC-MAIN-2019-39 |
cc-2021-25 |
2,457,631,756 | 300 | 26.1 GiB | Common Crawl columnar index CC-MAIN-2021-25 |
cc-2020-34 |
2,449,834,239 | 300 | 24.5 GiB | Common Crawl columnar index CC-MAIN-2020-34 |
cc-2025-38 |
2,385,964,209 | 300 | 27.4 GiB | Common Crawl columnar index CC-MAIN-2025-38 |
cc-2025-47 |
2,294,472,912 | 300 | 26.3 GiB | Common Crawl columnar index CC-MAIN-2025-47 |
commoncrawl |
2,149,001,456 | 300 | 25.4 GiB | Common Crawl columnar index CC-MAIN-2026-30 |
cc-2015-18 |
2,115,818,059 | 300 | 14.5 GiB | Common Crawl columnar index CC-MAIN-2015-18 |
ccrawl-urls |
2,098,491,742 | 300 | 24.8 GiB | open-index/ccrawl-urls |
cc-2026-12 |
1,974,845,234 | 300 | 23.0 GiB | Common Crawl columnar index CC-MAIN-2026-12 |
cc-2015-35 |
1,848,022,475 | 300 | 12.8 GiB | Common Crawl columnar index CC-MAIN-2015-35 |
cc-2015-48 |
1,824,170,527 | 300 | 12.6 GiB | Common Crawl columnar index CC-MAIN-2015-48 |
cc-2016-22 |
1,466,220,798 | 300 | 10.9 GiB | Common Crawl columnar index CC-MAIN-2016-22 |
cc-2016-26 |
1,236,815,660 | 300 | 8.8 GiB | Common Crawl columnar index CC-MAIN-2016-26 |
cc-filtered-urls |
67,479,353 | 606 | 0.4 GiB | xinyangli/cc-filtered-urls |
common-crawl-sample_urls |
4,342,326 | 1 | 0.1 GiB | nhagar/common-crawl-sample_urls |
Public corpora, projected to their URL column
Mostly built on nhagar's *_urls extracts,
which publish url + domain; we keep url and drop domain. These overlap
each other heavily by construction — every Common-Crawl-derived corpus shares a
backbone — which is why they are kept separate instead of merged.
| source | URLs | files | on disk | derived from |
|---|---|---|---|---|
fineweb |
24,505,935,751 | 101 | 617.8 GiB | nhagar/fineweb_urls |
hplt2.0-cleaned |
10,558,904,807 | 59 | 228.5 GiB | nhagar/hplt2.0_cleaned_urls |
colossal-oscar-1.0 |
10,332,304,603 | 52 | 250.6 GiB | nhagar/colossal-oscar-1.0_urls |
c4-multilingual |
8,522,562,521 | 1104 | 244.1 GiB | nhagar/c4_urls_multilingual |
culturax |
7,184,124,703 | 36 | 182.3 GiB | nhagar/culturax_urls |
madlad-400-noisy |
6,801,149,222 | 25 | 193.8 GiB | nhagar/madlad-400_urls_noisy |
redpajama-data-v2 |
6,079,335,069 | 35 | 149.7 GiB | nhagar/redpajama-data-v2_urls |
txt360_urls |
5,651,306,105 | 97 | 141.6 GiB | nhagar/txt360_urls |
dolma-v1.5 |
4,921,549,644 | 32 | 127.0 GiB | nhagar/dolma_urls_v1.5 |
hplt-v1.2 |
4,651,480,080 | 7 | 60.6 GiB | nhagar/hplt-v1.2_urls |
fineweb-2 |
4,567,627,672 | 18 | 109.8 GiB | nhagar/fineweb-2_urls |
zyda-2 |
4,506,333,003 | 866 | 111.6 GiB | nhagar/zyda-2_urls |
dolma-v1.6 |
3,731,835,146 | 30 | 92.4 GiB | nhagar/dolma_urls_v1.6 |
madlad-400-clean |
3,507,642,707 | 14 | 96.2 GiB | nhagar/madlad-400_urls_clean |
dclm-baseline-1.0 |
2,949,254,346 | 15 | 72.3 GiB | nhagar/dclm-baseline-1.0-parquet_urls |
olmoe-mix-0924_urls |
2,948,096,911 | 15 | 73.5 GiB | nhagar/olmoe-mix-0924_urls |
dolma_urls_v1.7 |
2,673,664,597 | 18 | 66.7 GiB | nhagar/dolma_urls_v1.7 |
redpajama-data-1t_urls |
1,469,452,453 | 11 | 37.8 GiB | nhagar/redpajama-data-1t_urls |
oscar-2301_urls |
1,401,594,726 | 8 | 35.2 GiB | nhagar/oscar-2301_urls |
lucie-training-dataset_urls |
1,281,707,164 | 12 | 32.2 GiB | nhagar/lucie-training-dataset_urls |
oscar-2109_urls |
1,239,027,220 | 1 | 31.0 GiB | nhagar/oscar-2109_urls |
culturay_urls |
1,220,338,131 | 7 | 18.2 GiB | nhagar/culturay_urls |
zyda_urls |
1,174,929,887 | 105 | 29.9 GiB | nhagar/zyda_urls |
oscar-2201_urls |
992,957,761 | 6 | 25.8 GiB | nhagar/oscar-2201_urls |
falcon-refinedweb_urls |
968,000,015 | 95 | 25.0 GiB | nhagar/falcon-refinedweb_urls |
onlysports_dataset_urls |
863,989,915 | 4 | 22.9 GiB | nhagar/onlysports_dataset_urls |
glotcc-v1_urls |
684,697,321 | 5 | 16.5 GiB | nhagar/glotcc-v1_urls |
c4_urls_en.noblocklist |
393,391,519 | 197 | 10.1 GiB | nhagar/c4_urls_en.noblocklist |
fineweb2-hq_urls |
380,138,261 | 13 | 9.1 GiB | nhagar/fineweb2-hq_urls |
c4_en_urls |
365,233,500 | 61 | 9.4 GiB | nhagar/c4_en_urls |
moscar_urls |
303,229,385 | 2 | 7.1 GiB | nhagar/moscar_urls |
c4_urls_en.noclean |
189,396,098 | 95 | 5.2 GiB | nhagar/c4_urls_en.noclean |
varta-urls |
177,768,440 | 66 | 4.6 GiB | rahular/varta-urls |
mc4-es-sampled_urls |
150,000,000 | 1 | 4.2 GiB | nhagar/mc4-es-sampled_urls |
obelics_urls |
141,047,697 | 1 | 4.1 GiB | nhagar/obelics_urls |
fulg_urls |
114,679,939 | 1 | 2.5 GiB | nhagar/fulg_urls |
clean_mc4_it_urls |
101,631,883 | 1 | 2.8 GiB | nhagar/clean_mc4_it_urls |
culturax-mini-nonshuffled_urls |
71,841,248 | 1 | 1.8 GiB | nhagar/culturax-mini-nonshuffled_urls |
mc4_nl_cleaned_urls |
64,545,895 | 1 | 1.6 GiB | nhagar/mc4_nl_cleaned_urls |
catalog_urls |
34,314,510 | 1 | 0.6 GiB | nhagar/catalog_urls |
101_billion_arabic_words_dataset_urls |
33,059,988 | 1 | 0.9 GiB | nhagar/101_billion_arabic_words_dataset_urls |
infimm-webmath-40b_urls |
23,739,397 | 1 | 0.5 GiB | nhagar/infimm-webmath-40b_urls |
finemath_urls_3plus |
21,405,610 | 1 | 0.5 GiB | nhagar/finemath_urls_3plus |
mc4_fi_cleaned_urls |
18,160,122 | 1 | 0.4 GiB | nhagar/mc4_fi_cleaned_urls |
c4_urls_realnewslike |
13,799,838 | 7 | 0.4 GiB | nhagar/c4_urls_realnewslike |
crawlpt_dedup_urls |
10,888,966 | 1 | 0.3 GiB | nhagar/crawlpt_dedup_urls |
finemath_urls_4plus |
6,699,493 | 1 | 0.1 GiB | nhagar/finemath_urls_4plus |
open-web-math_urls |
6,315,233 | 1 | 0.1 GiB | nhagar/open-web-math_urls |
georgian-corpus_urls |
5,333,536 | 1 | 0.1 GiB | nhagar/georgian-corpus_urls |
legal-mc4_urls |
4,934,201 | 1 | 0.1 GiB | nhagar/legal-mc4_urls |
c4-chinese-zhtw_urls |
2,967,556 | 1 | 0.1 GiB | nhagar/c4-chinese-zhtw_urls |
mixturevitae-fineweb-permissive-multilingual-2m_urls |
2,226,907 | 1 | 0.0 GiB | nhagar/mixturevitae-fineweb-permissive-multilingual-2m_urls |
Format, and two honest caveats
Every file under data/ is a single nullable url string column compressed
with zstd. Row counts above are from a footer scan of all 52,244
files taken the day this was published, not from the upstream READMEs.
1. Two Parquet flavours, and no guaranteed row order. Write settings changed
partway through staging and existing files were deliberately not rewritten.
About half the sources are Parquet 2.6 with DELTA_LENGTH_BYTE_ARRAY; the rest
are Parquet 1.0 with PLAIN, which costs roughly twice the bytes for the same
URLs. Both read identically — read_parquet('data/x/*.parquet') does not care.
Row order is not guaranteed — do not rely on it. Files were originally
written ORDER BY surt(url), url, but a later in-place repair pass rewrote
values (decoding & to &) after they had been sorted, and changing the
string changes its SURT key. Checked against the reference SURT implementation,
most sources are now partially out of order; rows containing & are about three
times over-represented among the out-of-order ones, which is the fingerprint of
that repair. Sources that never needed the repair are largely still ordered. If
you need an ordering, impose it yourself — one
ORDER BY surt(url), url does it.
This also costs bytes: measured on 6.7M URLs, unsorted is 146–147 MB against 74 MB sorted, so these files carry roughly twice the bytes a sorted copy would. They are published as-is rather than rewritten, so that what you download is byte-identical to what the build actually read.
2. Nothing is deduplicated, within or across sources. The counts above are
pre-dedup and the sources genuinely overlap. On a 1/1024 consistent-hash sample
of the whole corpus the unique fraction came out at 27.4%. Treat the total
as "URLs staged", not "distinct URLs". Three pairs that were byte-identical
republications (cultura/culturax, falcon/falcon-refinedweb,
c4_urls_en/c4_en_urls) were already removed before publication, reclaiming
218.6 GiB with no information lost.
Where files are sorted, the key is ORDER BY surt(url), url using a
byte-exact port of internetarchive/surt,
so shards can be compared against each other and joined against Common Crawl's
url_surtkey. The secondary sort on url matters because surt() is not
injective — http/https and trailing-slash variants collapse to one key.
Licensing and attribution
This collection is a derivative work and carries no single license. Each
config inherits the terms of the corpus it was extracted from — see the
derived from column above and source-notes/<source>.md for the exact
upstream, then follow that upstream's license. Notable cases: the Common Crawl
index is under Common Crawl's
terms of use; Wikimedia dumps are
CC BY-SA / GFDL; most nhagar *_urls extracts inherit ODC-By from C4, FineWeb
and friends.
URLs are addresses, not content: nothing here reproduces the text of any page. Some URLs will nonetheless point at content that is offensive, illegal in your jurisdiction, or personally identifying, and some will be dead. There is no safety filtering of any kind.
Provenance
Each source is fetched whole (the Hugging Face Xet client sustains ~359 MB/s on
large files, where ranged column reads run below 50 MB/s and get rate-limited),
projected to its url column with DuckDB, and the source file deleted — about
7.5 TiB pulled over the wire becomes the 4.35 TiB kept here.
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