Pergunta de entrevista da empresa Primer AI

Take Home Project 1: Geodata​ ​Processing Many​ ​of​ ​our​ ​projects​ ​focus​ ​on​ ​processing​ ​and​ ​analyzing​ ​documents​ ​on​ ​a​ ​regular​ ​basis,​ ​some​ ​public and​ ​some​ ​proprietary.​ ​​ ​Because​ ​NLP​ ​is​ ​hard,​ ​let’s​ ​simply​ ​worry​ ​about​ ​processing​ ​location​ ​data​ ​in​ ​a scalable​ ​way. Data​ ​Description The​ ​data​ ​we’re​ ​working​ ​with​ ​is​ ​open​ ​data​ ​from​ ​Geonames.org,​ ​specifically​ a​​ ​ ​compressed​ ​dataset of​ ​global​ ​cities​ ​with​ ​>1K​ ​population​.​ ​​ ​Although​ ​it’s​ ​small​ ​enough​ ​to​ ​be​ ​inspected,​ ​the​ ​.tsv​ ​data fields​ ​are​ ​described​ ​in​ ​plain-text​ ​form​ ​at​ ​​the​ ​bottom​ ​of​ ​the​ ​index​ ​page​.​ ​​ ​There’s​ ​about​ ​150K​ ​cities in​ ​total. Processing Most​ ​data​ ​we​ ​process​ ​is​ ​normalized​ ​to​ ​a​ ​particular​ ​form​ ​so​ ​we​ ​can​ ​make​ ​some​ ​generalizable assumptions​ ​about​ ​the​ ​information​ ​we​ ​have​ ​access​ ​to.​ ​​ ​For​ ​locations,​ ​we​ ​will​ ​make​ ​up​ ​a​ ​Primer Normalized​ ​Location​ ​format​ ​that​ ​includes​ ​the​ ​following​ ​information: ● Name​ ​(Latin-1​ ​compatible) ● Shape​ ​data​ ​(Binary) ● Latitude ● Longitude ● Country​ ​Code​ ​(ISO-3166) ● Administrative​ ​Level​ ​1 ● Administrative​ ​Level​ ​2 Not​ ​only​ ​should​ ​this​ ​data​ ​be​ ​persisted,​ ​but​ ​we​ ​will​ ​also​ ​search​ ​against​ ​this​ ​database​ ​as​ ​well, either​ ​in​ ​terms​ ​of​ ​a​ ​nearest​ ​neighbors​ ​search​ ​or​ ​full-text​ ​by​ ​name. Assignment Using​ ​the​ ​system​ ​as​ ​described​ ​above,​ ​design​ ​a​ ​pipeline​ ​to​ ​process,​ ​transform,​ ​and​ ​persist​ ​the cities​ ​file​ ​sourced​ ​in​ ​two​ ​particular​ ​ways: ● As​ ​is​ ​(Single​ ​file) ● As​ ​multiple​ ​files​ ​(e.g.​ ​Each​ ​line​ ​as​ ​an​ ​individual​ ​file,​ ​same​ ​format) Assume​ ​that​ ​the​ ​only​ ​transformation​ ​that​ ​you​ ​need​ ​to​ ​handle​ ​is​ ​the​ ​form​ ​given​ ​above. You​ ​should​ ​also​ ​write​ ​a​ ​PoC​ ​version​ ​showing​ ​the​ ​single-file​ ​scenario. The​ ​design​ ​should​ ​optimize​ ​for​ ​scalability,​ ​such​ ​that​ ​increasing​ ​the​ ​number​ ​of​ ​locations​ ​(e.g. using​ ​​all​ ​the​ ​GeoNames​ ​country​ ​data​)​ ​does​ ​not​ ​yield​ ​a​ ​linear​ ​increase​ ​in​ ​wall-clock​ ​processing time. The​ ​design​ ​must​ ​address​ ​the​ ​following: ● Resource​ ​requirements​ ​as​ ​the​ ​system​ ​scales ● Developer​ ​ease​ ​of​ ​use ● Any​ ​technology​ ​dependencies ● Any​ ​shortcomings​ ​or​ ​limitations​ ​of​ ​the​ ​system Optionally,​ ​address​ ​the​ ​following​ ​longer-term​ ​concerns: ● Reprocessing​ ​data,​ ​such​ ​as​ ​propagating​ ​a​ ​shape​ ​file​ ​format​ ​change ● Non-trivial​ ​increases​ ​in​ ​processing​ ​time​ ​for​ ​an​ ​individual​ ​city​ ​(i.e.​ ​new​ ​algorithms​ ​get introduced,​ ​additional​ ​fields​ ​are​ ​added) ● Monitoring​ ​and​ ​alerting ● Location​ ​data​ ​sourced​ ​from​ ​a​ ​database​ ​instead​ ​of​ ​individual​ ​files Include​ ​any​ ​assumptions​ ​about​ ​the​ ​application​ ​as​ ​needed​ ​for​ ​simplicity,​ ​although​ ​we​ ​are available​ ​to​ ​answer​ ​any​ ​question​ ​you​ ​may​ ​have​ ​about​ ​the​ ​system,​ ​assignment,​ ​or​ ​life​ ​in​ ​general. General​ ​Assessment​ ​Criteria Although​ ​we​ ​are​ ​primarily​ ​a​ ​Python​ ​company,​ ​any​ ​tools​ ​used​ ​do​ ​not​ ​have​ ​to​ ​be​ ​in​ ​Python,​ ​they only​ ​need​ ​to​ ​be​ ​delineated.​ ​Be​ ​sure​ ​to​ ​include​ ​the​ ​purpose​ ​for​ ​each​ ​tool​ ​as​ ​it's​ ​added. Make​ ​sure​ ​you​ ​hit​ ​all​ ​the​ ​requirements.​ ​​ ​Although​ ​some​ ​are​ ​coding,​ ​some​ ​can​ ​be​ ​strictly presentational.​ ​​ ​Some​ ​interesting​ ​and​ ​free​ ​tools​ ​for​ ​simple​ ​diagram​ ​drawing,​ ​if​ ​you​ ​don’t​ ​have one​ ​of​ ​your​ ​own,​ ​are​ ​Google​ ​Draw​ ​and​ ​yUML.me.