[{"@context":"https:\/\/schema.org\/","@type":"BlogPosting","@id":"https:\/\/blog.terabox.com\/insights\/blinkdb-stratified-sampling-msdf-font-rendering#BlogPosting","mainEntityOfPage":"https:\/\/blog.terabox.com\/insights\/blinkdb-stratified-sampling-msdf-font-rendering","headline":"BlinkDB &#038; MSDF: Optimizing Big Data Sampling and Graphics","name":"BlinkDB &#038; MSDF: Optimizing Big Data Sampling and Graphics","description":"\ud83d\udcfa Today&#8217;s recommended deep-dive video: https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8 Speeding Up the Infinite: From Big Data Sampling to Pixel-Perfect FontsThe Sampling Superpower in ObservabilityPrecision through StratificationThe Architecture of Digital TypeBeyond the Blur: Multi-Channel Distance FieldsKey TakeawaysQ&amp;A Speeding Up the Infinite: From Big Data... ","datePublished":"2026-08-14","dateModified":"2026-08-14","author":{"@type":"Person","@id":"https:\/\/blog.terabox.com\/author\/flextech-admin\/#Person","name":"flextech-admin","url":"https:\/\/blog.terabox.com\/author\/flextech-admin\/","image":{"@type":"ImageObject","@id":"https:\/\/secure.gravatar.com\/avatar\/ad516503a11cd5ca435acc9bb6523536?s=150&#038;d=mm&#038;r=gforcedefault=1","url":"https:\/\/secure.gravatar.com\/avatar\/ad516503a11cd5ca435acc9bb6523536?s=150&#038;d=mm&#038;r=gforcedefault=1","height":96,"width":96}},"publisher":{"@type":"Organization","name":"terabox","logo":{"@type":"ImageObject","@id":"http:\/\/blog.terabox.com\/wp-content\/uploads\/2021\/11\/logo\u4ea7\u54c1\u540d-\u7ad6\u7248.png","url":"http:\/\/blog.terabox.com\/wp-content\/uploads\/2021\/11\/logo\u4ea7\u54c1\u540d-\u7ad6\u7248.png","width":900,"height":900}},"image":{"@type":"ImageObject","@id":"https:\/\/img.youtube.com\/vi\/-O0-HEZAwg8\/maxresdefault.jpg","url":"https:\/\/img.youtube.com\/vi\/-O0-HEZAwg8\/maxresdefault.jpg","height":"","width":""},"url":"https:\/\/blog.terabox.com\/insights\/blinkdb-stratified-sampling-msdf-font-rendering","video":{"@context":"http:\/\/schema.org\/","@type":"VideoObject","@id":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8#VideoObject","contentUrl":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8","name":"Shape Decomposition for Multi-channel Distance Fields by Zach Tellman [PWL SF]","description":"Papers We Love San Francisco 10\/2018\n\n---\nMini\nRamon Nogueira on BlinkDB: Queries with Bounded Errors and\nBounded Response Times on Very Large Data - https:\/\/sameeragarwal.github.io\/blinkdb_eurosys13.pdf\n\nRamon's Bio\nRamon is a software engineer with a passion for making large systems easier to understand and operate. He currently works at Google on OpenCensus: an open source metrics and distributed tracing library for microservices. Previous hits include iCloud storage APIs at Apple, and startups in London and Johannesburg\n\nMain Talk\nZach Tellman on Shape Decomposition for Multi-channel Distance Fields - https:\/\/dspace.cvut.cz\/bitstream\/handle\/10467\/62770\/F8-DP-2015-Chlumsky-Viktor-thesis.pdf\n\nZach's Bio\nZach consults on the design of distributed systems and APIs. He has written \"Elements of Clojure\", a book which tries to put words to what most experienced engineers already know, and is working on a tool for exploratory data processing.","thumbnailUrl":["https:\/\/i.ytimg.com\/vi\/-O0-HEZAwg8\/default.jpg","https:\/\/i.ytimg.com\/vi\/-O0-HEZAwg8\/mqdefault.jpg","https:\/\/i.ytimg.com\/vi\/-O0-HEZAwg8\/hqdefault.jpg","https:\/\/i.ytimg.com\/vi\/-O0-HEZAwg8\/sddefault.jpg","https:\/\/i.ytimg.com\/vi\/-O0-HEZAwg8\/maxresdefault.jpg"],"uploadDate":"2018-11-14T03:14:21+00:00","duration":"PT40M4S","embedUrl":"https:\/\/www.youtube.com\/embed\/-O0-HEZAwg8","publisher":{"@type":"Organization","@id":"https:\/\/www.youtube.com\/channel\/UCoj4eQh_dZR37lL78ymC6XA#Organization","url":"https:\/\/www.youtube.com\/channel\/UCoj4eQh_dZR37lL78ymC6XA","name":"PapersWeLove","description":"What was the last paper within the realm of computing you read and loved? What did it inspire you to build or tinker with? Come share the ideas in an awesome academic\/research paper with fellow engineers, programmers, and paper-readers. Lead a session and show off code that you wrote that implements these ideas or just give us the lowdown about the paper (because of HARD MATH!). Otherwise, just come, listen, and discuss.\n\nWe're curating a repository for papers and places-to-find papers at https:\/\/github.com\/papers-we-love\/papers-we-love. You can contribute by adding PR's for papers, code, and\/or links to other repositories.","logo":{"url":"https:\/\/yt3.ggpht.com\/ytc\/AIdro_nszZvpaLpFV8Jw3PvZegFrXWcxdXo37uBJtDT7sGJ1aA=s800-c-k-c0x00ffffff-no-rj","width":800,"height":800,"@type":"ImageObject","@id":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8#VideoObject_publisher_logo_ImageObject"}},"potentialAction":{"@type":"SeekToAction","@id":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8#VideoObject_potentialAction","target":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8&t={seek_to_second_number}","startOffset-input":"required name=seek_to_second_number"},"interactionStatistic":[[{"@type":"InteractionCounter","@id":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8#VideoObject_interactionStatistic_WatchAction","interactionType":{"@type":"WatchAction"},"userInteractionCount":5356}],{"@type":"InteractionCounter","@id":"https:\/\/www.youtube.com\/watch?v=-O0-HEZAwg8#VideoObject_interactionStatistic_LikeAction","interactionType":{"@type":"LikeAction"},"userInteractionCount":159}]},"about":["Insights","\u300eEnglish\u300f"],"wordCount":1177,"keywords":["big data"]},{"@context":"https:\/\/schema.org\/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Insights","item":"https:\/\/blog.terabox.com\/insights\/#breadcrumbitem"},{"@type":"ListItem","position":2,"name":"BlinkDB &#038; MSDF: Optimizing Big Data Sampling and Graphics","item":"https:\/\/blog.terabox.com\/insights\/blinkdb-stratified-sampling-msdf-font-rendering#breadcrumbitem"}]}]