[{"data":1,"prerenderedAt":262},["ShallowReactive",2],{"project-3204012":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":29,"sentiment":30,"stance_mix":31,"scored_comments":36,"aspects":37,"strip":44,"post_text":47,"what":48,"said":79,"maker_in_thread":165,"shape":177,"grid":179,"attempts":224,"same_week":225,"maker_shows":189,"maker_hidden":254,"reader_version":255,"card":256},"3204012","Mortar (Mortar Data)","1M Song Dataset dev in 10 mins","title","Show HN: 1M Song Dataset dev in 10 mins","http:\u002F\u002Fmortardata.com\u002Fmillion-song-dataset-in-10-minutes","mortardata.com","kky",1320617092,2011,77,22,152,1097,14,"notable","data","big data processing","web_app",[24,25,26,27,28],"hadoop","big data","pig","mapreduce","million song dataset","curious",0.069,{"positive":32,"neutral":33,"mixed":34,"critical":35},1,8,4,0,13,{"docs":38,"idea":39,"performance":40,"pricing":41,"design":42,"execution":43},{"positive":35,"critical":35},{"positive":32,"critical":35},{"positive":35,"critical":35},{"positive":35,"critical":35},{"positive":35,"critical":35},{"positive":35,"critical":35},[45,35,45,45,46,35,35,35,35,45,45,35,45,45,35,45,35,45,45,45,35,45],3,5,null,{"problem":49,"audience":47,"pricing":47,"motivation":47,"time_to_build":47,"stack":57,"openness":77,"stage":78,"team_size":77},{"value":50,"source":51,"evidence":52},"Running big data analysis on Hadoop is hard and costly to set up.","commenter",[53],{"id":54,"by":55,"text":56},"3204946","simon_weber","\"Hawk is Heroku for Hadoop: an on-demand, easy-to-use cloud service for big data. With Hawk any company will be able to extract the value from their big data without the large…",[58,62,66,70],{"value":59,"source":51,"evidence":60},"Pig",[61],{"id":54,"by":55,"text":56},{"value":63,"source":51,"evidence":64},"Python",[65],{"id":54,"by":55,"text":56},{"value":67,"source":51,"evidence":68},"Hadoop",[69],{"id":54,"by":55,"text":56},{"value":71,"source":72,"evidence":73},"Amazon EC2","maker",[74],{"id":75,"by":11,"text":76},"3205005","We actually built on EC2, not Elastic MapReduce. Invoices come from Mortar only -- that way when we can achieve bulk AWS savings, we can keep our cost lower. I'm glad it looks…","unknown","beta",{"praise":80,"objections":100,"requests":123,"questions":141,"alternatives":159},[81,96],{"value":82,"source":51,"evidence":83},"Demo video looks impressive and useful",[84,88,92],{"id":85,"by":86,"text":87},"3204476","deepkut","I really think your website should be more indicative of what MD does. I had to look it up elsewhere. Regardless, very cool video.",{"id":89,"by":90,"text":91},"3204628","ajdavis","Very cool demo, this looks like an amazing tool (and I don't even know much about Hadoop!). One question -- it looks like you're skipping over the time it takes for the…",{"id":93,"by":94,"text":95},"3204849","res0nat0r","This looks pretty awesome. So is this just using Elastic Mapreduce on the backend? Can you use your existing AWS credentials for this with a Hawk surcharge on top? This looks…",{"value":97,"source":51,"evidence":98},"Easy to use for big data without knowing Hadoop",[99],{"id":89,"by":90,"text":91},[101,113],{"value":102,"source":51,"evidence":103},"Main website does not explain what the product does",[104,105,109],{"id":85,"by":86,"text":87},{"id":106,"by":107,"text":108},"3204913","angryasian","I wish the site would write up an explanation, rather than providing a video. Could someone who watched summarize ?",{"id":110,"by":111,"text":112},"3207979","fasouto","+10 for the product, seems really nice. But I don't like the main site, it's not very informative I'm doing something similar for my master thesis, a pig console embedded in js…",{"value":114,"source":51,"evidence":115},"Video text is hard to read at small size",[116,120],{"id":117,"by":118,"text":119},"3204709","latch","FWIW, looks great. Took me a while to hit the maximize button on the videos...for a while I thought \"man, they really didn't do a good job, I can't read any of the text\"",{"id":121,"by":90,"text":122},"3206758","I had the same thought at first -- next time, make sure the text is bold enough to be legible at 320x240. Once I maximized the vid it looked great, of course.",[124,134],{"value":125,"source":51,"evidence":126},"Control over node types, not just number of nodes",[127,131],{"id":128,"by":129,"text":130},"3205026","revertts","Do I get any control over node types, or is \"number of nodes\" the only knob I can turn?",{"id":132,"by":11,"text":133},"3205046","Right now, just \"number of nodes\". But that's definitely something we'll be adding soon.",{"value":135,"source":51,"evidence":136},"Integration with existing Hadoop cluster",[137],{"id":138,"by":139,"text":140},"3205409","vitalyg","Very cool tool. Can the tool be integrated with my existing Hadoop cluster or do I need to transfer all the data to MH?",[142,149,153],{"value":143,"source":51,"evidence":144},"How does it compare to AWS Elastic MapReduce with Pig?",[145],{"id":146,"by":147,"text":148},"3205479","nashequilibrium","How does your offering compare to AWS elsatsic MapReduce using Pig?",{"value":150,"source":51,"evidence":151},"How long does illustrate take on the million song dataset?",[152],{"id":89,"by":90,"text":91},{"value":154,"source":51,"evidence":155},"How is it different from SQL?",[156],{"id":157,"by":158,"text":154},"3204862","dennisgorelik",[160],{"value":161,"source":51,"evidence":162},"AWS Elastic MapReduce",[163,164],{"id":146,"by":147,"text":148},{"id":93,"by":94,"text":95},{"comments":166,"answered":45,"key":167},7,[168,171,174],{"id":169,"text":170},"3204598","Thank you, I appreciate the feedback.",{"id":172,"text":173},"3204587","Thank you! There is a link to request an invite at mortardata.com -- if you'd like access, let us know. We just got a lot of invitation requests from this post, but we'll invite…",{"id":175,"text":176},"3204641","And also, if you haven't seen musicmachinery.com, do check it out.",{"commenters":18,"max_depth":34,"maker_replies":166,"first_comment_mins":178,"lifespan_hours":15},170,[180,182,184,186,187,192,193,195,198,200,202,204,206,207,210,211,213,215,216,218,220,221],[85,35,45,181,86,35],"project\u002Fmixed\u002Fdocs",[169,35,35,183,11,32],"maker\u002Fneutral\u002Fnone",[106,32,45,185,107,35],"project\u002Fneutral\u002Fdocs",[54,32,45,185,55,35],[188,189,46,190,191,35],"3204522",2,"project\u002Fpositive\u002Fidea","jacabado",[172,189,35,183,11,32],[175,189,35,194,11,32],"other\u002Fneutral\u002Fnone",[196,189,35,194,197,35],"3204711","bbq",[199,189,35,194,191,35],"3204777",[146,45,45,201,147,35],"project\u002Fneutral\u002Fnone",[89,34,45,203,90,35],"project\u002Fneutral\u002Fperformance",[205,34,35,203,11,32],"3204652",[110,46,45,181,111,35],[93,208,45,209,94,35],6,"project\u002Fneutral\u002Fpricing",[75,208,35,209,11,32],[117,166,45,212,118,35],"project\u002Fmixed\u002Fdesign",[214,166,35,183,11,32],"3204762",[121,166,45,212,90,35],[138,33,45,217,139,35],"project\u002Fneutral\u002Fexecution",[128,219,45,217,129,35],9,[132,219,35,217,11,32],[157,222,45,223,158,35],10,"project\u002Fneutral\u002Fidea",[],[226,231,236,240,245,250],{"id":227,"name":228,"points":229,"category":230},"3207736","Enqueue",301,"creative",{"id":232,"name":233,"points":234,"category":235},"3196766","Scroll Reddit",240,"consumer_social",{"id":237,"name":238,"points":239,"category":230},"3215460","MapCrunch",93,{"id":241,"name":242,"points":243,"category":244},"3205779","Met",79,"productivity",{"id":246,"name":247,"points":248,"category":249},"3208319","cupboard",47,"dev_tools",{"id":251,"name":252,"points":253,"category":230},"3216728","Top forty",32,false,"v2",{"id":257,"name":5,"line":6,"ai":254,"cat":20,"year":13,"points":14,"comments":15,"rec":29,"s":258,"top":18,"kw":259,"maker":11,"domain":10,"tier":19,"attempts":35,"strip":260,"url":9,"mix":261,"praise":82,"objection":102,"sub":21},3204012,0.07,[24,25,26,27,28],"3033500003303303033303",[32,33,34,35],1793990876382]