{"id":70862,"date":"2020-02-22T06:40:55","date_gmt":"2020-02-22T03:40:55","guid":{"rendered":"https:\/\/prohoster.info\/blog\/sber-ds-platforma-kotoraya-pozvolyaet-sozdavat-i-vnedryat-modeli-dazhe-bez-koda"},"modified":"2020-03-03T16:14:35","modified_gmt":"2020-03-03T13:14:35","slug":"sber-ds-platforma-kotoraya-pozvolyaet-sozdavat-i-vnedryat-modeli-dazhe-bez-koda","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/administrirovanie\/sber-ds-platforma-kotoraya-pozvolyaet-sozdavat-i-vnedryat-modeli-dazhe-bez-koda","title":{"rendered":"Sber.DS \u2014 platvorm, mis v\u00f5imaldab luua ja rakendada mudeleid isegi ilma koodita.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Igap\u00e4evaselt tekivad erineva suurusega ettev\u00f5tetes ideid ja kohtumisi, kuidas veel protsesse automatiseerida. Kuid lisaks sellele, et mudeli loomine v\u00f5ib v\u00f5tta palju aega, tuleb kulutada aega ka selle hindamisele ja kontrollimisele, et saadud tulemus ei oleks juhuslik. P\u00e4rast rakendamist tuleb igat mudelit j\u00e4lgida ja perioodiliselt kontrollida.<\/p>\n

<\/p>\n

Need on k\u00f5ik etapid, mis tuleb l\u00e4bida igas ettev\u00f5ttes, s\u00f5ltumata selle suurusest. Kui r\u00e4\u00e4gime Sberbankist ja selle suurusest, siis n\u00fcansside arv kasvab mitmekordselt. 2019. aasta l\u00f5puks kasutati Sberis juba \u00fcle 2000 mudeli. Mudeli lihtsalt v\u00e4ljat\u00f6\u00f6tamine ei piisa; vajalik on integreeruda t\u00f6\u00f6stuss\u00fcsteemidega, arendada andmete vitriine mudelite loomiseks ja tagada selle t\u00f6\u00f6 hindamine klastris.<\/p>\n

\"Sber.DS<\/a><\/noindex><\/p>\n

Meie meeskond arendab platvormi Sber.DS. See aitab lahendada masin\u00f5ppe \u00fclesandeid, kiirendab h\u00fcpoteeside kontrollimise protsessi, lihtsustab p\u00f5him\u00f5tteliselt arendamise ja valideerimise protsessi ning j\u00e4lgib mudeli t\u00f6\u00f6 tulemust PROMis.<\/p>\n

<\/p>\n

Kuna ma ei soovi teie ootusi petta, tahan ette \u00f6elda, et see postitus on sissejuhatav ning allpool r\u00e4\u00e4gime esmalt sellest, mis p\u00f5him\u00f5tteliselt platvormi Sber.DS aluseks on. Mudeli eluts\u00fcklist alates loomise kuni rakendamiseni r\u00e4\u00e4gime eraldi. <\/p>\n

\n<\/a><\/noindex><\/p>\n

Sber.DS koosneb mitmest komponendist, milleks on peamised raamatukogu, arenduss\u00fcsteem ja mudelite t\u00e4itmise s\u00fcsteem. <\/p>\n

\n\"Sber.DS
\n<\/p>\n

Raamatukogu juhib mudeli eluts\u00fcklit idee tekkimisest kuni rakendamiseni PROMis, j\u00e4lgimise seadistamiseni ja v\u00e4ljaarvamiseni kasutusest. Raamatukogu paljusid v\u00f5imalusi dikteerivad j\u00e4relvalt v\u00e4ljaandjad, n\u00e4iteks aruandlus ja koolitus- ja valideerimistulemuste s\u00e4ilitamine. Tegelikult on see meie mudelite registri register.<\/p>\n

<\/p>\n

Arenduss\u00fcsteem on m\u00f5eldud mudelite ja valideerimismeetodite visuaalseks arendamiseks. Arendatud mudelid l\u00e4bivad esialgse valideerimise ja edastatakse t\u00e4itmise s\u00fcsteemi oma \u00e4ritegevuse funktsioonide t\u00e4itmiseks. Samuti v\u00f5ib t\u00e4itmise s\u00fcsteemis mudel olla seadistatud monitooringuks, et perioodiliselt k\u00e4ivitada valideerimismeetodeid oma t\u00f6\u00f6 j\u00e4lgimiseks. <\/p>\n

<\/p>\n

S\u00fcsteemis on mitu t\u00fc\u00fcpi s\u00f5lmi. \u00dched on m\u00f5eldud \u00fchendamiseks erinevate andmeallikatega, teised aga l\u00e4hteandmete transformeerimiseks ja nende rikastamiseks (m\u00e4rgistamiseks). On palju s\u00f5lmi erinevate mudelite koostamiseks ja valideerimiseks. Arendaja saab laadida andmeid mis tahes allikatest, neid muuta, filtreerida, visualiseerida vaheandmeid ning jagada neid osadeks.<\/p>\n

<\/p>\n

Platvorm sisaldab ka juba valmis mooduleid, mida saab lohistada projektialale. K\u00f5ik toimingud tehakse visualiseeritud liidese kaudu. Tegelikult on v\u00f5imalik probleem lahendada ilma \u00fcheainsa koodirea kirjutamiseta.<\/p>\n

<\/p>\n

Kui sisseehitatud v\u00f5imalused ei ole piisavad, pakub s\u00fcsteem v\u00f5imalust kiiresti luua oma mooduleid. Oleme integreeritud arenduse re\u017eiimi teinud p\u00f5hjal Jupyter Kernel Gateway<\/a><\/noindex> neile, kes loovad uusi mooduleid \"nullist\".<\/p>\n

\n\"Sber.DS
\n<\/p>\n

Sber.DS arhitektuur p\u00f5hineb mikroteenustel. Mikroteenuste kohta on palju arvamusi. M\u00f5ned usuvad, et piisab monoliitse koodi jagamisest osadeks, kuid nad kasutavad ikkagi \u00fchte ja sama andmebaasi. Meil peab mikroteenus suhtlema teise mikroteenusega ainult REST API kaudu. Otsest andmebaasi juurdep\u00e4\u00e4su pole lubatud.<\/p>\n

<\/p>\n

P\u00fc\u00fcame v\u00e4ltida, et teenused muutuksid v\u00e4ga suurteks ja kohmakateks: \u00fcks eksemplar ei tohi kasutada rohkem kui 4\u20138 gigabaiti RAM-i ja peab v\u00f5imaldama horisontaalset skaleerimist, k\u00e4ivitades uusi eksemplare. Iga teenus suhtleb teistega ainult REST API kaudu (Open API<\/a><\/noindex>). Teenuse eest vastutav meeskond peab s\u00e4ilitama API tagurpidi \u00fchilduvuse viimase kliendini, kes seda kasutab.<\/p>\n

<\/p>\n

Rakenduse s\u00fcdamik on kirjutatud Java-s, kasutades Spring Frameworki. Lahendus oli algselt kavandatud kiireks juurutamiseks pilveinfrastruktuuris, mist\u00f5ttu on rakendus loodud konteinerite haldamise s\u00fcsteemi kasutades. Red Hat OpenShift<\/a><\/noindex> (Kubernetes<\/a><\/noindex>). Platvorm areneb pidevalt, lisades nii \u00e4ritegevuse funktsioone (uued \u00fchendajad, AutoML) kui ka tehnolooge t\u00f5husust. <\/p>\n

<\/p>\n

\u00dcks meie platvormi \u201espetsialiteete\u201c on see, et saame k\u00e4itada visuaalses liideses arendatud koodi Sberbanki mudelite igasugustes k\u00e4ituss\u00fcsteemides. Hetkel on neid juba kaks: \u00fcks Hadoopil, teine \u2014 OpenShiftis (Docker). Me ei kavatse sellega piirduda ja loome integreerimisv\u00f5imalusi koodi k\u00e4itamiseks igasugustes infrastruktuurides, sealhulgas kohapeal ja pilves. Mis puutub Sberbanki \u00f6kos\u00fcsteemi t\u00f5husasse integreerimisse, siis plaanime toetada ka olemasolevate k\u00e4ituskeskkondade kasutamist. Tulevikus saab lahendust paindlikult integreerida \u201ev\u00e4lja pakitud\u201c mis tahes organisatsiooni maastikku.<\/p>\n

<\/p>\n

Need to manage a Python solution running on Hadoop in a production environment know that it's not just about preparing and delivering a user-specific Python environment to each data node. The vast number of C\/C++ libraries for machine learning that utilize Python modules won't let you rest easy. It\u2019s essential to keep packages updated when adding new libraries or servers while maintaining backward compatibility with the existing model code.<\/p>\n

<\/p>\n

There are several approaches to achieve this. For instance, you can pre-prepare some commonly used libraries and integrate them into the production environment. In Cloudera's Hadoop distribution, this is typically done using parcel<\/a><\/noindex>. Additionally, the ability to run docker<\/a><\/noindex>-containers is now being introduced in Hadoop. In some straightforward cases, you can deliver the code together with the package python.eggs<\/a><\/noindex>.<\/p>\n

<\/p>\n

The bank takes the security of running third-party code very seriously, so we maximally utilize new kernel capabilities of Linux, where the process running in an isolated environment Linux namespace<\/a><\/noindex>, on v\u00f5imalik piirata n\u00e4iteks juurdep\u00e4\u00e4su v\u00f5rgule ja lokaalsetele ketastele, mis oluliselt v\u00e4hendab pahavara v\u00f5imalusi. Iga osakonna andmevaldkonnad on kaitstud ja ligip\u00e4\u00e4setavad ainult nende andmete omanikele. Platvorm garanteerib, et andmed \u00fchest valdkonnast saavad teise valdkonda liikuda ainult andmete avaldamise protsessi kaudu, mille k\u00e4igus kontrollitakse k\u00f5iki etappe alates juurdep\u00e4\u00e4sust allikatele kuni andmete j\u00f5udmiseni sihtvitriini.<\/p>\n

\n\"Sber.DS
\n<\/p>\n

Sel aastal plaanime l\u00f5petada MVP lansseerimise mudelitele, mis on kirjutatud Pythonis\/Ris\/Java Hadoopil. Oleme endale seadnud ambitsioonika eesm\u00e4rgi \u00f5ppida k\u00e4ivitama igasuguseid kohandatud keskkondi Hadoopil, et meie platvormi kasutajatel ei oleks kitsendusi.<\/p>\n

<\/p>\n

Lisaks selgus, et paljud DS-spetsialistid tunnevad h\u00e4sti matemaatikat ja statistikat, loovad lahedaid mudeleid, kuid ei tea suurte andmete transformatsioonist v\u00e4ga palju ning vajavad meie andmeinseneride abi koolitusvalimite ettevalmistamisel. Otsustasime aidata kolleege ja luua mugavad moodulid t\u00fc\u00fcpiliseks transformatsiooniks ja funktsioonide ettevalmistamiseks mudelite jaoks Spark-mootoril. See v\u00f5imaldab rohkem aega modelleerimisele p\u00fchendada ning ei pea ootama, kuni andmeinsenerid uut andmestikku ette valmistavad.<\/p>\n

<\/p>\n

Meie juures t\u00f6\u00f6tavad inimesed, kellel on teadmised erinevates valdkondades: Linux ja DevOps, Hadoop ja Spark, Java ja Spring, Scala ja Akka, OpenShift ja Kubernetes. J\u00e4rgmises osas r\u00e4\u00e4gime mudelite raamatukogust, kuidas mudel l\u00e4bib eluiga ettev\u00f5ttes, kuidas toimub valideerimine ja rakendamine.<\/p>\n

Allikas: habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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Kuid peale mudeli loomise kulutatud aja peaksime investeerima ka selle hindamisse ja kontrollimisse, et saadud tulemus ei oleks juhuslik. P\u00e4rast rakendamist tuleb igat mudelit j\u00e4lgida ja perioodiliselt kontrollida. Ja see","canonical_url":"https:\/\/prohoster.info\/et\/blog\/administrirovanie\/sber-ds-platforma-kotoraya-pozvolyaet-sozdavat-i-vnedryat-modeli-dazhe-bez-koda","robots":"max-image-preview:large","keywords":"","webmasterTools":{"miscellaneous":""},"schema":null,"og:locale":"et_EE","og:site_name":"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b","og:type":"article","og:title":"\ud83e\udd47Sber.DS \u2014 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u0430, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0441\u043e\u0437\u0434\u0430\u0432\u0430\u0442\u044c \u0438 \u0432\u043d\u0435\u0434\u0440\u044f\u0442\u044c \u043c\u043e\u0434\u0435\u043b\u0438 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