[{"data":1,"prerenderedAt":154},["ShallowReactive",2],{"project-11242022":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":38,"post_text":28,"what":41,"said":58,"maker_in_thread":95,"shape":99,"grid":102,"attempts":116,"same_week":117,"maker_shows":146,"maker_hidden":147,"reader_version":148,"card":149},"11242022","Skizze","High-throughput probabilistic data structure service","title","Show HN: Skizze – High-throughput probabilistic data structure service","https:\u002F\u002Fgithub.com\u002Fskizzehq\u002Fskizze","github.com","seiflotfy",1457387434,2016,53,6,699,2264,31,"notable","data","probabilistic data structures","api",[21,24,25,26],"bloom filter","hyperloglog","streaming statistics","quiet",null,{"positive":30,"neutral":31,"mixed":30,"critical":32},1,2,0,4,{"docs":35,"idea":36,"design":37},{"positive":32,"critical":32},{"positive":30,"critical":32},{"positive":32,"critical":32},[39,40,32,39,39,32],3,5,{"problem":42,"audience":28,"pricing":28,"motivation":28,"time_to_build":28,"stack":56,"openness":57,"stage":57,"team_size":57},{"value":43,"source":44,"evidence":45},"Approximate membership, cardinality, frequency and top-k queries over high-volume streams with less memory","inferred",[46,50,53],{"id":47,"by":48,"text":49},"11243661","krat0sprakhar","Looks useful. However, how does the bloom filter and HLL implementation compare to the ones available in Redis?",{"id":51,"by":11,"text":52},"11244769","Redis provides a bitset that can be used as a bloom filter. You'd end up having to hash k times on a client side, while also calculating the ideal size of the bitset for the…",{"id":54,"by":11,"text":55},"11245716","Sure thing. So imagine you have a domain with a expected cardinality (which you pass) of 1 million and a threshold of 10k. What will happen is every time you insert an event it…",[],"unknown",{"praise":59,"objections":69,"requests":76,"questions":81,"alternatives":90},[60],{"value":61,"source":62,"evidence":63},"Useful idea, especially the streaming metrics feature","commenter",[64,68],{"id":65,"by":66,"text":67},"11245457","alixaxel","Great work on putting this together! Amazing idea really. I'm specially looking forward for the streaming metrics\u002Fstatistics feature. PS: Could you go into a bit more into the…",{"id":47,"by":48,"text":49},[70],{"value":71,"source":62,"evidence":72},"Unclear how threshold and memory usage relate to error rate",[73],{"id":74,"by":66,"text":75},"11246950","I get the multiplexing and I think that's a great concept. One other thing that you might also want to consider (to reduce unneeded interaction with the server) is allow…",[77],{"value":78,"source":62,"evidence":79},"Support specifying counts per key, e.g. weighted heavy hitters",[80],{"id":74,"by":66,"text":75},[82,86],{"value":83,"source":62,"evidence":84},"How does it compare to the Bloom filter and HLL in Redis",[85],{"id":47,"by":48,"text":49},{"value":87,"source":62,"evidence":88},"Memory requirements and threshold specification per domain",[89],{"id":65,"by":66,"text":67},[91],{"value":92,"source":62,"evidence":93},"Redis bitset-based Bloom filter and HyperLogLog",[94],{"id":47,"by":48,"text":49},{"comments":31,"answered":31,"key":96},[97,98],{"id":54,"text":55},{"id":51,"text":52},{"commenters":33,"max_depth":39,"maker_replies":31,"first_comment_mins":100,"lifespan_hours":101},441,20,[103,107,109,111,113,115],[104,32,39,105,106,32],"11244532","maker\u002Fneutral\u002Fdocs","njpatel",[65,30,40,108,66,32],"project\u002Fpositive\u002Fidea",[54,30,32,110,11,30],"project\u002Fneutral\u002Fdesign",[74,30,39,112,66,32],"project\u002Fmixed\u002Fdesign",[47,31,39,114,48,32],"project\u002Fneutral\u002Fnone",[51,31,32,110,11,30],[],[118,123,128,132,137,142],{"id":119,"name":120,"points":121,"category":122},"11238099","status page",248,"infrastructure",{"id":124,"name":125,"points":126,"category":127},"11218844","Flat",207,"creative",{"id":129,"name":130,"points":131,"category":122},"11224608","Sway",163,{"id":133,"name":134,"points":135,"category":136},"11228443","CodeCoach",131,"dev_tools",{"id":138,"name":139,"points":140,"category":141},"11256364","Hacksplaining",128,"learning_science",{"id":143,"name":144,"points":145,"category":136},"11252253","Marginotes",111,12,false,"v2",{"id":150,"name":5,"line":6,"ai":147,"cat":20,"year":13,"points":14,"comments":15,"rec":27,"s":28,"top":18,"kw":151,"maker":11,"domain":10,"tier":19,"attempts":32,"strip":152,"url":9,"mix":153,"praise":61,"objection":71,"sub":21},11242022,[21,24,25,26],"350330",[30,31,30,32],1794036541844]