[{"data":1,"prerenderedAt":346},["ShallowReactive",2],{"project-20101381":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":27,"sentiment":28,"stance_mix":29,"scored_comments":33,"aspects":34,"strip":41,"post_text":43,"what":44,"said":88,"maker_in_thread":176,"shape":178,"grid":183,"attempts":309,"same_week":310,"maker_shows":30,"maker_hidden":339,"reader_version":340,"card":341},"20101381","mlsql","Translate English to SQL","title","Show HN: Translate English to SQL","https:\u002F\u002Fgithub.com\u002Fpaulfitz\u002Fmlsql","github.com","paulfitz",1559707462,2019,209,45,184,2195,9,"notable","ai","natural language to sql","other",[21,24,25,26],"text to sql","sql","neural network","curious",-0.2,{"positive":30,"neutral":31,"mixed":32,"critical":18},3,17,0,29,{"idea":35,"execution":38,"performance":39,"docs":40},{"positive":36,"critical":37},2,5,{"positive":32,"critical":36},{"positive":32,"critical":36},{"positive":32,"critical":32},[42,30,32,42,30,30,32,42,32,32,42,30,30,30,30,37,32,30,32,32,32,30,30,42,30,42,32,42,32,32,32,42,37,32,42,32,30,30,30,37],1,null,{"problem":45,"audience":53,"pricing":43,"motivation":43,"time_to_build":43,"stack":63,"openness":86,"stage":87,"team_size":87},{"value":46,"source":47,"evidence":48},"Turning natural language questions into SQL queries.","commenter",[49],{"id":50,"by":51,"text":52},"20105054","Myrmornis","It's not intended to replace your code :) It's intended to turn normal peoples' words into code.",{"value":54,"source":47,"evidence":55},"People who don't know SQL, such as product managers and non-programmers.",[56,59],{"id":57,"by":51,"text":58},"20105043","It's not for programmers; think more of Siri\u002FAlexa translating to SQL. (I'm with you, I hate natural language interfaces too, but there we are.)",{"id":60,"by":61,"text":62},"20102392","monkeydust","From a product managers pov this looks very interesting - is there a demo environment available somewhere to play with this?",[64,75,79],{"value":65,"source":47,"evidence":66},"PyTorch",[67,71],{"id":68,"by":69,"text":70},"20101793","____Sash---701_","Looks like PyTorch",{"id":72,"by":73,"text":74},"20102142","newaccoutnas","PyTorch accorging to https:\u002F\u002Fgithub.com\u002Fpaulfitz\u002Fsqlova#requirements Also CoreNLP",{"value":76,"source":47,"evidence":77},"CoreNLP",[78],{"id":72,"by":73,"text":74},{"value":80,"source":47,"evidence":81},"Docker",[82],{"id":83,"by":84,"text":85},"20102431","amolo","Nice. Very interesting. But 4 gigs just to get I running. That's probably more than the DB I'm trying to query.","open_source","unknown",{"praise":89,"objections":105,"requests":132,"questions":141,"alternatives":157},[90],{"value":91,"source":47,"evidence":92},"Interesting open source example of natural language to SQL work.",[93,97,101],{"id":94,"by":95,"text":96},"20103359","michaelmior","It's great to see a nice open source example of work in this area. It would be helpful if there were also some examples of where the model fails either by not being able to…",{"id":98,"by":99,"text":100},"20101777","o10449366","Very interesting. I did a similar project for my machine learning class in grad school. I'm curious what kind of architecture\u002Fmodel framework you used for this.",{"id":102,"by":103,"text":104},"20101939","c8g","does it only work with a question that returns a single answer or it can be used to build something like…",[106,114,125],{"value":107,"source":47,"evidence":108},"Requires too many resources (4 GB Docker image).",[109,110],{"id":83,"by":84,"text":85},{"id":111,"by":112,"text":113},"20103972","jtbayly","Yes, I don’t know anything about how\u002Fwhat this is running, but I immediately can’t use it based on requirements. Too bad.",{"value":115,"source":47,"evidence":116},"Natural language is too imprecise compared to explicit SQL.",[117,121],{"id":118,"by":119,"text":120},"20103245","rezeroed","I might be too much of a control freak to give up the explicit precision of SQL.",{"id":122,"by":123,"text":124},"20103968","sheeshkebab","I think anyone who uses sql would find this tool (and a lot of similar abstractions) too imprecise, verbose, and error prone. What's the longest bridge in mariland - or was it…",{"value":126,"source":47,"evidence":127},"Complex real-world queries are hard to express in English.",[128],{"id":129,"by":130,"text":131},"20106709","ohadron","I feel that SQL queries that people will need help with are not the SQL 101 examples shown here. Looking at the queries I write as a product manager, I wouldn't have the…",[133,137],{"value":134,"source":47,"evidence":135},"Show examples of where the model fails.",[136],{"id":94,"by":95,"text":96},{"value":138,"source":47,"evidence":139},"Provide a demo environment.",[140],{"id":60,"by":61,"text":62},[142,146],{"value":143,"source":47,"evidence":144},"What architecture or model framework was used?",[145],{"id":98,"by":99,"text":100},{"value":147,"source":47,"evidence":148},"How does it handle case-sensitive string matching?",[149,153],{"id":150,"by":151,"text":152},"20104174","LunaSea","The example is probably wrong or not working since the English questions uses \"throgs neck\" in lower case instead of the captialized \"Throgs Neck\" version. Those are two…",{"id":154,"by":155,"text":156},"20104224","laurent123456","Aren't the queries case insensitive by default?",[158,165,172],{"value":159,"source":47,"evidence":160},"Microsoft SQL Server English Query",[161],{"id":162,"by":163,"text":164},"20103602","BrentOzar","Ah, this brings back fun memories. Over a decade ago, Microsoft SQL Server had English Query to do the same thing. Developers had to define all the words & relationships that…",{"value":166,"source":47,"evidence":167},"SQLova (naver\u002Fsqlova)",[168],{"id":169,"by":170,"text":171},"20103949","mynegation","This is a wrapper for a pretrained model. Probably a better github link would be https:\u002F\u002Fgithub.com\u002Fnaver\u002Fsqlova\u002F",{"value":173,"source":47,"evidence":174},"ThoughtSpot",[175],{"id":102,"by":103,"text":104},{"comments":32,"answered":32,"key":177},[],{"commenters":179,"max_depth":180,"maker_replies":32,"first_comment_mins":181,"lifespan_hours":182},39,4,96,69,[184,186,190,193,196,198,201,205,208,212,215,217,218,222,225,228,230,233,234,237,238,242,245,248,249,252,255,257,258,260,264,267,269,272,275,279,283,285,288,289,291,296,299,301,305],[162,32,42,185,163,32],"project\u002Fcritical\u002Fidea",[187,32,30,188,189,32],"20120091","project\u002Fneutral\u002Fexecution","johnsonjo",[191,42,32,192,51,32],"20105021","other\u002Fneutral\u002Fidea",[194,36,42,185,195,32],"20105418","drinane",[169,30,30,197,170,32],"project\u002Fneutral\u002Fidea",[199,180,30,188,200,32],"20102857","kowdermeister",[202,37,32,203,204,32],"20105891","other\u002Fneutral\u002Fnone","mitchtbaum",[83,206,42,207,84,32],6,"project\u002Fcritical\u002Fperformance",[209,206,32,210,211,32],"20103086","commenter\u002Fneutral\u002Fperformance","z3t4",[213,206,32,210,214,32],"20104695","sfoley",[216,206,32,203,211,32],"20115893",[111,206,42,207,112,32],[219,206,30,220,221,32],"20105126","project\u002Fneutral\u002Fperformance","libria",[223,206,30,220,224,32],"20106003","y4mi",[226,206,30,220,227,32],"20114534","hadsed",[102,229,30,197,103,32],7,[98,231,37,232,99,32],8,"project\u002Fpositive\u002Fidea",[68,231,30,188,69,32],[235,231,32,236,69,32],"20101819","commenter\u002Fneutral\u002Fnone",[72,231,30,188,73,32],[239,18,32,240,241,32],"20104475","other\u002Fcritical\u002Fidea","viach",[243,18,32,236,244,32],"20105039","regular_person",[246,18,32,236,247,32],"20105487","TazeTSchnitzel",[57,18,30,197,51,32],[250,18,30,197,251,32],"20105312","rgoulter",[94,253,30,254,95,32],10,"project\u002Fneutral\u002Fdocs",[118,256,42,185,119,32],11,[50,256,30,197,51,32],[129,259,42,185,130,32],12,[261,259,32,262,263,32],"20115319","commenter\u002Fneutral\u002Fidea","gatherhunterer",[150,265,42,266,151,32],13,"project\u002Fcritical\u002Fexecution",[154,265,32,268,155,32],"commenter\u002Fneutral\u002Fexecution",[270,265,32,268,271,32],"20108175","zainhoda",[273,265,32,268,274,32],"20115460","novaleaf",[276,277,42,266,278,32],"20102827",14,"nothrabannosir",[280,277,30,281,282,32],"20103551","maker\u002Fneutral\u002Fdocs","herohamp",[60,284,37,232,61,32],15,[286,284,32,236,287,32],"20103473","mritchie712",[122,284,42,185,123,32],[290,284,32,262,287,32],"20104064",[292,293,30,294,295,32],"20103323",16,"project\u002Fneutral\u002Fnone","exdsq",[297,293,30,294,298,32],"20103419","FiberBundle",[300,293,30,254,287,32],"20103490",[302,31,37,303,304,32],"20129995","project\u002Fpositive\u002Fnone","duxup",[306,307,32,203,308,32],"20105976",18,"quizotic",[],[311,316,321,325,330,335],{"id":312,"name":313,"points":314,"category":315},"20105567","Bloom",747,"web_saas",{"id":317,"name":318,"points":319,"category":320},"20094866","html_wysiwyg",633,"dev_tools",{"id":322,"name":323,"points":324,"category":320},"20060549","medium-to-own-blog",494,{"id":326,"name":327,"points":328,"category":329},"20081488","ZeroHTTPd",472,"learning_science",{"id":331,"name":332,"points":333,"category":334},"20049075","notational-fzf-vim",171,"productivity",{"id":336,"name":337,"points":338,"category":334},"20077177","Nullboard",145,false,"v2",{"id":342,"name":5,"line":6,"ai":339,"cat":20,"year":13,"points":14,"comments":15,"rec":27,"s":28,"top":18,"kw":343,"maker":11,"domain":10,"tier":19,"attempts":32,"strip":344,"url":9,"mix":345,"praise":91,"objection":107,"sub":21},20101381,[21,24,25,26],"1301330100133335030003313101000150103335",[30,31,32,18],1793990990198]