{"id":30268,"date":"2019-10-31T21:34:35","date_gmt":"2019-10-31T18:34:35","guid":{"rendered":"https:\/\/prohoster.info\/blog\/kak-peremeshhat-vygruzhat-i-integrirovat-ochen-bolshie-dannye-dyoshevo-i-bystro-chto-takoe-pushdown-optimizatsiya\/"},"modified":"2019-10-31T21:34:35","modified_gmt":"2019-10-31T18:34:35","slug":"kak-peremeshhat-vygruzhat-i-integrirovat-ochen-bolshie-dannye-dyoshevo-i-bystro-chto-takoe-pushdown-optimizatsiya","status":"publish","type":"post","link":"https:\/\/prohoster.info\/hr\/blog\/kak-peremeshhat-vygruzhat-i-integrirovat-ochen-bolshie-dannye-dyoshevo-i-bystro-chto-takoe-pushdown-optimizatsiya","title":{"rendered":"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Svaka operacija s velikim podacima zahtijeva velike ra\u010dunalne resurse. Uobi\u010dajeno premje\u0161tanje podataka iz baze na Hadoop mo\u017ee trajati tjednima ili ko\u0161tati koliko i krilo aviona. Ne \u017eelite \u010dekati i tro\u0161iti? Uravnote\u017eite optere\u0107enje na razli\u010ditim platformama. Jedan od na\u010dina je pushdown-optimizacija.<\/p>\n<p><\/p>\n<p>Zamolio sam vode\u0107eg trenera u Rusiji za razvoj i administraciju proizvoda Informatica, Alekseja Ananjeva, da nam objasni funkciju pushdown-optimizacije u Informatica Big Data Management (BDM). Jeste li ikada u\u010dili raditi s proizvodima Informatica? Vjerojatno vam je ba\u0161 Aleksej govorio osnove PowerCentra i obja\u0161njavao kako graditi mape. <\/p>\n<p><\/p>\n<p><strong>Aleksej Ananjev, vo\u0111a sektora za obuku u DIS Grupi<\/strong><\/p>\n<p><\/p>\n<p><strong>\u0160to je pushdown?<\/strong><\/p>\n<p><\/p>\n<p>Mnogi od vas su ve\u0107 upoznati s Informatica Big Data Management (BDM). Proizvod mo\u017ee integrirati velike podatke iz razli\u010ditih izvora, premje\u0161tati ih izme\u0111u razli\u010ditih sustava, omogu\u0107uje lagan pristup, profilira ih i jo\u0161 mnogo toga.<br \/>\nU spretnim rukama BDM mo\u017ee \u010diniti \u010duda: zadaci \u0107e se izvoditi brzo i s minimalnim ra\u010dunalnim resursima. <\/p>\n<p><\/p>\n<p>\u017delite li i vi to? Nau\u010dite koristiti funkciju pushdown u BDM za raspodjelu ra\u010dunalnog optere\u0107enja izme\u0111u razli\u010ditih platformi. Tehnologija pushdown omogu\u0107uje pretvaranje mape u skriptu i odabir okru\u017eenja u kojem \u0107e ta skripta biti pokrenuta. Mogu\u0107nost odabira omogu\u0107uje kombiniranje prednosti razli\u010ditih platformi i postizanje njihove maksimalne u\u010dinkovitosti.<\/p>\n<p><\/p>\n<p>Za postavljanje okru\u017eenja za izvo\u0111enje skripte potrebno je odabrati tip pushdown. Skripta se mo\u017ee potpuno izvr\u0161iti na Hadoopu ili djelomi\u010dno rasporediti izme\u0111u izvora i odredi\u0161ta. Postoje 4 mogu\u0107a tipa pushdown. Mapu se ne mora pretvarati u skriptu (native). Mapu se mo\u017ee izvr\u0161iti maksimalno na izvoru (source) ili potpuno na izvoru (full). Tako\u0111er, mapu se mo\u017ee pretvoriti u Hadoop skriptu (none).<\/p>\n<p><noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<p><strong>Pushdown-optimizacija<\/strong><\/p>\n<p><\/p>\n<p>Navedenih 4 tipa mo\u017ee se razli\u010dito kombinirati \u2013 optimizirati pushdown prema konkretnim potrebama sustava. Na primjer, \u010desto je korisnije izvu\u0107i podatke iz baze podataka, koriste\u0107i njezine vlastite mogu\u0107nosti. A obraditi podatke \u2013 snagom Hadoopa, kako ne bi optere\u0107ivali samu bazu.<\/p>\n<p><\/p>\n<p>Razmotrimo slu\u010daj kada su i izvor i prijemnik u bazi podataka, a platformu za izvr\u0161avanje transformacija mo\u017eemo odabrati: ovisno o postavkama to \u0107e biti Informatica, server baze podataka ili Hadoop. Ovaj primjer \u0107e omogu\u0107iti najpreciznije razumijevanje tehni\u010dke strane rada ovog mehanizma. Naravno, u stvarnom \u017eivotu ovakva situacija se ne javlja, ali za demonstraciju funkcionalnosti ona je najprikladnija. <\/p>\n<p><\/p>\n<p>Uzmimo mapiranje za \u010ditanje dviju tablica u jedinstvenoj bazi podataka Oracle. A rezultati \u010ditanja neka se zapisuju u tablicu u istoj bazi. Shema mapiranja \u0107e biti sljede\u0107a:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/e5bdacf6d7b0c3dbffd56c4876515520.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>U obliku mapiranja na Informatica BDM 10.2.1 to izgleda ovako:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/5e7e1d81f0eac539aaec1c21717341e7.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p><strong>Tip pushdown \u2013 native<\/strong><\/p>\n<p><\/p>\n<p>Ako odaberemo tip pushdown native, mapiranje \u0107e se izvesti na <a class=\"wpil_keyword_link\" href=\"https:\/\/prohoster.info\/hr\/server\/dts-dronten\/\"   title=\"serveru\" data-wpil-keyword-link=\"linked\"  data-wpil-monitor-id=\"2457\">serveru<\/a> Informatica. Podaci \u0107e biti pro\u010ditani sa servera Oracle, preba\u010deni na server Informatica, transformirani tamo i poslani u Hadoop. Drugim rije\u010dima, dobit \u0107emo uobi\u010dajeni ETL proces.<\/p>\n<p><\/p>\n<p><strong>Tip pushdown \u2013 source <\/strong><\/p>\n<p><\/p>\n<p>Pri odabiru tipa source dobivamo mogu\u0107nost raspodjele na\u0161eg procesa izme\u0111u <a class=\"wpil_keyword_link\" href=\"https:\/\/prohoster.info\/hr\/server\/dts-prohoster\/\"   title=\"serverom\" data-wpil-keyword-link=\"linked\"  data-wpil-monitor-id=\"2959\">serverom<\/a> baza podataka (BDB) i Hadoop. Pri izvr\u0161avanju procesa s ovom postavkom, u bazu \u0107e stizati upiti za dohvat podataka iz tablica. A ostatak \u0107e se izvr\u0161avati u obliku koraka na Hadoop.<br \/>\nShema izvr\u0161enja \u0107e izgledati ovako:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/8b3b071ea0580394b222da033effceee.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Ispod je primjer postavki okru\u017eenja za izvr\u0161avanje.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/da7434ae71f4b2265f61fd31e182897e.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>U ovom slu\u010daju, mapiranje \u0107e se izvr\u0161avati u dva koraka. U njegovim postavkama \u0107emo vidjeti da se pretvorio u skriptu koja \u0107e biti poslana na izvor. Pri tome \u0107e se spajanje tablica i transformacija podataka izvr\u0161iti u obliku redefiniranog upita na izvoru.<br \/>\nNa slici ispod vidimo optimizirano mapiranje na BDM, a na izvoru redefinirani upit.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/c0e7534b06d2e09785ad8a6c5df15f6f.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Uloga Hadoop-a u ovoj konfiguraciji svodi se na upravljanje protokom podataka \u2013 dirigovanje njima. Rezultat upita \u0107e biti poslan u Hadoop. Nakon zavr\u0161etka \u010ditanja, datoteka iz Hadoop-a bit \u0107e zapisana u prijemnik.<\/p>\n<p><\/p>\n<p><strong>Tip pushdown \u2013 full <\/strong><\/p>\n<p><\/p>\n<p>Pri odabiru tipa full, mapiranje se potpuno pretvara u upit na BDB. A rezultat upita bit \u0107e poslan na Hadoop. Shema takvog procesa prikazana je ispod.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/bfbb3f593a7053a0157d481d9b3bce83.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Primjer postavke prikazan je ispod.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/31c70c7fb10996d5a506c6a4618f5f2f.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Kao rezultat dobit \u0107emo optimizirano mapiranje sli\u010dno prethodnom. Razlika je samo u tome \u0161to \u0107e se cijela logika premjestiti na prijemnik u obliku redefiniranja njegove umetanja. Primjer optimiziranog mapiranja prikazan je ispod.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/edabf7ab6eba768849d096a4319e5126.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Ovdje, kao i u prethodnom slu\u010daju, Hadoop igra ulogu dirigenta. Me\u0111utim, ovdje se cijeli izvor \u010dita, a zatim se na razini prijemnika izvr\u0161ava logika obrade podataka.<\/p>\n<p><\/p>\n<p><strong>Tip pushdown \u2013 null<\/strong><\/p>\n<p><\/p>\n<p>I posljednja opcija \u2013 tip pushdown, u okviru kojeg \u0107e se na\u0161e mapiranje pretvoriti u skriptu na Hadoopu.<\/p>\n<p><\/p>\n<p>Optimizirano mapiranje sada \u0107e izgledati ovako:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Kako premjestiti, izvesti i integrirati vrlo velike podatke jeftino i brzo? \u0160to je pushdown-optimizacija?\" src=\"\/wp-content\/uploads\/2019\/03\/deb8311403d4e95c2fef06d3b5c94e64.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Ovdje \u0107e se podaci iz izvornih datoteka najprije pro\u010ditati na Hadoopu. Zatim \u0107e se tim istim sredstvima ta dva fajla spojiti. Nakon toga, podaci \u0107e se transformirati i u\u010ditati u bazu podataka.<\/p>\n<p><\/p>\n<p>Razumijevanjem principa optimizacije pushdown, mnoge procese rada s velikim podacima mogu\u0107e je vrlo efikasno organizirati. Tako je nedavno jedna velika kompanija u samo nekoliko tjedana iz Hadoop skladi\u0161ta iznijela velike podatke koje je prethodno prikupljala nekoliko godina.<\/p>\n<p>Izvor: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/post\/445240\/\">habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041b\u044e\u0431\u0430\u044f \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u044f \u0441 \u0431\u043e\u043b\u044c\u0448\u0438\u043c\u0438 \u0434\u0430\u043d\u043d\u044b\u043c\u0438 \u0442\u0440\u0435\u0431\u0443\u0435\u0442 \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u043c\u043e\u0449\u043d\u043e\u0441\u0442\u0435\u0439. \u041e\u0431\u044b\u0447\u043d\u043e\u0435 \u043f\u0435\u0440\u0435\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0438\u0437 \u0431\u0430\u0437\u044b \u043d\u0430 Hadoop \u043c\u043e\u0436\u0435\u0442 \u0434\u043b\u0438\u0442\u044c\u0441\u044f \u043d\u0435\u0434\u0435\u043b\u044f\u043c\u0438 \u0438\u043b\u0438 \u0441\u0442\u043e\u0438\u0442\u044c, \u043a\u0430\u043a \u043a\u0440\u044b\u043b\u043e \u0441\u0430\u043c\u043e\u043b\u0451\u0442\u0430. \u041d\u0435 \u0445\u043e\u0442\u0438\u0442\u0435 \u0436\u0434\u0430\u0442\u044c \u0438 \u0442\u0440\u0430\u0442\u0438\u0442\u044c\u0441\u044f? \u0421\u0431\u0430\u043b\u0430\u043d\u0441\u0438\u0440\u0443\u0439\u0442\u0435 \u043d\u0430\u0433\u0440\u0443\u0437\u043a\u0443 \u043d\u0430 \u0440\u0430\u0437\u043d\u044b\u0435 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b. \u041e\u0434\u0438\u043d \u0438\u0437 \u0441\u043f\u043e\u0441\u043e\u0431\u043e\u0432 \u2013 pushdown-\u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0430\u0446\u0438\u044f. \u042f \u043f\u043e\u043f\u0440\u043e\u0441\u0438\u043b \u0432\u0435\u0434\u0443\u0449\u0435\u0433\u043e \u0432 \u0420\u043e\u0441\u0441\u0438\u0438 \u0442\u0440\u0435\u043d\u0435\u0440\u0430 \u043f\u043e \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0435 \u0438 \u0430\u0434\u043c\u0438\u043d\u0438\u0441\u0442\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044e \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u043e\u0432 Informatica \u0410\u043b\u0435\u043a\u0441\u0435\u044f \u0410\u043d\u0430\u043d\u044c\u0435\u0432\u0430 \u0440\u0430\u0441\u0441\u043a\u0430\u0437\u0430\u0442\u044c \u043e [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-30268","post","type-post","status-publish","format-standard","hentry","category-blog"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.4 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041b\u044e\u0431\u0430\u044f \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u044f \u0441 \u0431\u043e\u043b\u044c\u0448\u0438\u043c\u0438 \u0434\u0430\u043d\u043d\u044b\u043c\u0438 \u0442\u0440\u0435\u0431\u0443\u0435\u0442 \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u0432\u044b\u0447\u0438\u0441\u043b\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u043c\u043e\u0449\u043d\u043e\u0441\u0442\u0435\u0439. \u041e\u0431\u044b\u0447\u043d\u043e\u0435 \u043f\u0435\u0440\u0435\u043c\u0435\u0449\u0435\u043d\u0438\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0438\u0437 \u0431\u0430\u0437\u044b \u043d\u0430 Hadoop \u043c\u043e\u0436\u0435\u0442 \u0434\u043b\u0438\u0442\u044c\u0441\u044f \u043d\u0435\u0434\u0435\u043b\u044f\u043c\u0438 \u0438\u043b\u0438 \u0441\u0442\u043e\u0438\u0442\u044c, \u043a\u0430\u043a \u043a\u0440\u044b\u043b\u043e \u0441\u0430\u043c\u043e\u043b\u0451\u0442\u0430.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link rel=\"canonical\" href=\"https:\/\/prohoster.info\/hr\/blog\/kak-peremeshhat-vygruzhat-i-integrirovat-ochen-bolshie-dannye-dyoshevo-i-bystro-chto-takoe-pushdown-optimizatsiya\" \/>\n\t\t<meta name=\"generator\" content=\"All in One SEO (AIOSEO) 5.0.4\" \/>\n\t\t<meta property=\"og:locale\" content=\"hr_HR\" \/>\n\t\t<meta property=\"og:site_name\" content=\"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\" \/>\n\t\t<meta property=\"og:type\" content=\"article\" \/>\n\t\t<meta property=\"og:title\" content=\"\ud83e\udd47\u041a\u0430\u043a \u043f\u0435\u0440\u0435\u043c\u0435\u0449\u0430\u0442\u044c, \u0432\u044b\u0433\u0440\u0443\u0436\u0430\u0442\u044c \u0438 \u0438\u043d\u0442\u0435\u0433\u0440\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043e\u0447\u0435\u043d\u044c \u0431\u043e\u043b\u044c\u0448\u0438\u0435 \u0434\u0430\u043d\u043d\u044b\u0435 \u0434\u0451\u0448\u0435\u0432\u043e \u0438 \u0431\u044b\u0441\u0442\u0440\u043e? 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