{"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\/sk\/blog\/kak-peremeshhat-vygruzhat-i-integrirovat-ochen-bolshie-dannye-dyoshevo-i-bystro-chto-takoe-pushdown-optimizatsiya","title":{"rendered":"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Ka\u017ed\u00e1 oper\u00e1cia s ve\u013ek\u00fdmi d\u00e1tami si vy\u017eaduje zna\u010dn\u00e9 v\u00fdpo\u010dtov\u00e9 kapacity. Be\u017en\u00fd presun d\u00e1t z datab\u00e1zy na Hadoop m\u00f4\u017ee trva\u0165 t\u00fd\u017edne alebo st\u00e1\u0165 ako kr\u00eddlo lietadla. Nechcete \u010daka\u0165 a m\u00ed\u0148a\u0165? Vyv\u00e1\u017ete z\u00e1\u0165a\u017e na r\u00f4zne platformy. Jeden zo sp\u00f4sobov je optimaliz\u00e1cia pushdown.<\/p>\n<p><\/p>\n<p>Po\u017eiadal som popredn\u00e9ho tr\u00e9nera v Rusku v oblasti v\u00fdvoja a spr\u00e1vy produktov Informatica Alexeja Ananjeva, aby n\u00e1m povedal o funkcii optimaliz\u00e1cie pushdown v Informatica Big Data Management (BDM). Kedy ste sa u\u010dili pracova\u0165 s produktmi Informatica? Pravdepodobne pr\u00e1ve Alexej v\u00e1m vysvet\u013eoval z\u00e1klady PowerCenter a ako vytv\u00e1ra\u0165 mapovania. <\/p>\n<p><\/p>\n<p><strong>Alexej Ananj\u0435\u0432, ved\u00faci sekcie \u0161kolen\u00ed DIS Group<\/strong><\/p>\n<p><\/p>\n<p><strong>\u010co je to pushdown?<\/strong><\/p>\n<p><\/p>\n<p>Mnoh\u00ed z v\u00e1s s\u00fa u\u017e obozn\u00e1men\u00ed s Informatica Big Data Management (BDM). Tento produkt dok\u00e1\u017ee integrova\u0165 ve\u013ek\u00e9 d\u00e1ta z r\u00f4znych zdrojov, pren\u00e1\u0161a\u0165 ich medzi r\u00f4znymi syst\u00e9mami, zabezpe\u010di\u0165 k nim jednoduch\u00fd pr\u00edstup, profilova\u0165 ich a mnoho in\u00e9ho.<br \/>\nV zru\u010dn\u00fdch ruk\u00e1ch m\u00f4\u017ee BDM robi\u0165 z\u00e1zraky: \u00falohy sa bud\u00fa vykon\u00e1va\u0165 r\u00fdchlo a s minim\u00e1lnymi v\u00fdpo\u010dtov\u00fdmi zdrojmi. <\/p>\n<p><\/p>\n<p>Chcete to tie\u017e? Nau\u010dte sa vyu\u017e\u00edva\u0165 funkciu pushdown v BDM na rozdelenie v\u00fdpo\u010dtovej z\u00e1\u0165a\u017ee medzi r\u00f4znymi platformami. Technol\u00f3gia pushdown umo\u017e\u0148uje premeni\u0165 mapovanie na skript a zvoli\u0165 prostredie, v ktorom sa tento skript spust\u00ed. Mo\u017enos\u0165 tak\u00e9ho v\u00fdberu umo\u017e\u0148uje kombinova\u0165 siln\u00e9 str\u00e1nky r\u00f4znych platforiem a dosiahnu\u0165 ich maxim\u00e1lnu v\u00fdkonnos\u0165.<\/p>\n<p><\/p>\n<p>Na nastavenie prostredia vykon\u00e1vania skriptu je potrebn\u00e9 zvoli\u0165 typ pushdown. Skript mo\u017eno kompletn\u00e9 spusti\u0165 na Hadoop alebo \u010diasto\u010dne rozdeli\u0165 medzi zdrojom a prij\u00edma\u010dom. Existuj\u00fa 4 mo\u017en\u00e9 typy pushdown. Mapovanie nemus\u00ed by\u0165 premenen\u00e9 na skript (native). Mapovanie m\u00f4\u017ee by\u0165 vykonan\u00e9 maxim\u00e1lne na zdroji (source) alebo \u00faplne na zdroji (full). Rovnako m\u00f4\u017ee by\u0165 mapovanie premenen\u00e9 na skript Hadoop (none).<\/p>\n<p><noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<p><strong>Optimaliz\u00e1cia pushdown<\/strong><\/p>\n<p><\/p>\n<p>T\u00fdchto 4 typy je mo\u017en\u00e9 r\u00f4zne kombinova\u0165 \u2013 optimalizova\u0165 pushdown na konkr\u00e9tne potreby syst\u00e9mu. Napr\u00edklad, \u010dasto je rozumnej\u0161ie extrahova\u0165 d\u00e1ta z datab\u00e1zy vyu\u017eit\u00edm jej vlastn\u00fdch mo\u017enost\u00ed. A transformova\u0165 d\u00e1ta s pomocou Hadoopu, aby sme nezah\u0155\u0148ali samotn\u00fa datab\u00e1zu.<\/p>\n<p><\/p>\n<p>Pozrime sa na situ\u00e1ciu, ke\u010f s\u00fa zdroj aj prij\u00edma\u010d v DB a platformu na vykon\u00e1vanie transform\u00e1ci\u00ed mo\u017eno vybra\u0165: v z\u00e1vislosti od nastaven\u00ed to bude Informatica, server DB alebo Hadoop. Tak\u00fdto pr\u00edklad umo\u017en\u00ed najpresnej\u0161ie pochopi\u0165 technick\u00fa str\u00e1nku fungovania tohto mechanizmu. Samozrejme, v skuto\u010dnom \u017eivote sa tak\u00e1 situ\u00e1cia nevyskytuje, ale na demon\u0161tr\u00e1ciu funk\u010dnosti je to najvhodnej\u0161ie. <\/p>\n<p><\/p>\n<p>Vezmeme mapovanie na \u010d\u00edtanie dvoch tabuliek v jednej datab\u00e1ze Oracle. A v\u00fdsledky \u010d\u00edtania nech bud\u00fa zap\u00edsan\u00e9 do tabu\u013eky v tej istej datab\u00e1ze. Sch\u00e9ma mapovania bude tak\u00e1to:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/e5bdacf6d7b0c3dbffd56c4876515520.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>V podobe mapovania na Informatica BDM 10.2.1 to vyzer\u00e1 nasledovne:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/5e7e1d81f0eac539aaec1c21717341e7.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p><strong>Typ pushdown \u2013 native<\/strong><\/p>\n<p><\/p>\n<p>Ak vyberieme typ pushdown native, mapovanie sa vykon\u00e1 na <a class=\"wpil_keyword_link\" href=\"https:\/\/prohoster.info\/sk\/server\/dts-dronten\/\"   title=\"serveri\" data-wpil-keyword-link=\"linked\"  data-wpil-monitor-id=\"2457\">serveri<\/a> Informatica. \u00dadaje bud\u00fa pre\u010d\u00edtan\u00e9 zo servera Oracle, prenesen\u00e9 na server Informatica, transformovan\u00e9 tam a odoslan\u00e9 do Hadoop. In\u00fdmi slovami, dostaneme be\u017en\u00fd ETL proces.<\/p>\n<p><\/p>\n<p><strong>Typ pushdown \u2013 source <\/strong><\/p>\n<p><\/p>\n<p>Pri v\u00fdbere typu source dostaneme mo\u017enos\u0165 rozlo\u017ei\u0165 n\u00e1\u0161 proces medzi <a class=\"wpil_keyword_link\" href=\"https:\/\/prohoster.info\/sk\/server\/dts-prohoster\/\"   title=\"serverom\" data-wpil-keyword-link=\"linked\"  data-wpil-monitor-id=\"2959\">serverom<\/a> datab\u00e1zy (DB) a Hadoop. Pri vykon\u00e1van\u00ed procesu s t\u00fdmto nastaven\u00edm sa do datab\u00e1zy odo\u0161l\u00fa dotazy na v\u00fdber \u00fadajov z tabuliek. A zvy\u0161ok sa bude vykon\u00e1va\u0165 v podobe krokov na Hadoop.<br \/>\nSch\u00e9ma vykon\u00e1vania bude vyzera\u0165 takto:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/8b3b071ea0580394b222da033effceee.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Ni\u017e\u0161ie je pr\u00edklad nastavenia prostredia vykon\u00e1vania.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/da7434ae71f4b2265f61fd31e182897e.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>V tomto pr\u00edpade sa mapovanie vykon\u00e1 v dvoch krokoch. V jeho nastaveniach uvid\u00edme, \u017ee sa premenil na skript, ktor\u00fd bude odoslan\u00fd na zdroj. Zl\u00fa\u010denie tabuliek a transform\u00e1cia \u00fadajov sa vykon\u00e1 v podobe predefinovan\u00e9ho dotazu na zdroji.<br \/>\nNa obr\u00e1zku ni\u017e\u0161ie vid\u00edme optimalizovan\u00e9 mapovanie na BDM a na zdroji \u2013 predefinovan\u00fd dotaz.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/c0e7534b06d2e09785ad8a6c5df15f6f.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>\u00daloha Hadoop v tejto konfigur\u00e1cii spo\u010d\u00edva v spr\u00e1ve toku \u00fadajov \u2013 dirigovan\u00ed nimi. V\u00fdsledok dotazu bude odoslan\u00fd do Hadoop. Po dokon\u010den\u00ed \u010d\u00edtania sa s\u00fabor z Hadoop zap\u00ed\u0161e do prij\u00edma\u010da.<\/p>\n<p><\/p>\n<p><strong>Typ pushdown \u2013 full <\/strong><\/p>\n<p><\/p>\n<p>Pri v\u00fdbere typu full sa mapovanie \u00faplne pretransformuje na dotaz na DB. A v\u00fdsledok dotazu bude odoslan\u00fd do Hadoop. Sch\u00e9ma tak\u00e9hoto procesu je uveden\u00e1 ni\u017e\u0161ie.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/bfbb3f593a7053a0157d481d9b3bce83.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Pr\u00edklad nastavenia je zobrazen\u00fd ni\u017e\u0161ie.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/31c70c7fb10996d5a506c6a4618f5f2f.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>V d\u00f4sledku toho dostaneme optimalizovan\u00e9 mapovanie podobn\u00e9 predch\u00e1dzaj\u00facemu. Rozdiel je len v tom, \u017ee cel\u00e1 logika sa prenesie na prij\u00edma\u010d v podobe predefinovania jeho vlo\u017eenia. Pr\u00edklad optimalizovan\u00e9ho mapovania je zobrazen\u00fd ni\u017e\u0161ie.<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/edabf7ab6eba768849d096a4319e5126.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Tu, podobne ako v predch\u00e1dzaj\u00facom pr\u00edpade, Hadoop zohr\u00e1va \u00falohu dirigenta. Tentokr\u00e1t sa \u010d\u00edtanie zdroja vykon\u00e1va kompletne, a potom sa na \u00farovni prij\u00edma\u010da vykon\u00e1va logika spracovania d\u00e1t.<\/p>\n<p><\/p>\n<p><strong>Typ pushdown \u2013 null<\/strong><\/p>\n<p><\/p>\n<p>A posledn\u00e1 varianta \u2013 typ pushdown, v r\u00e1mci ktor\u00e9ho sa n\u00e1\u0161 mapping premen\u00ed na skript na Hadoop.<\/p>\n<p><\/p>\n<p>Optimalizovan\u00fd mapping teraz vyzer\u00e1 takto:<\/p>\n<p><\/p>\n<p><img decoding=\"async\" alt=\"Ako pres\u00fava\u0165, exportova\u0165 a integrova\u0165 ve\u013emi ve\u013ek\u00e9 d\u00e1ta lacno a r\u00fdchlo? \u010co je to pushdown optimaliz\u00e1cia?\" src=\"\/wp-content\/uploads\/2019\/03\/deb8311403d4e95c2fef06d3b5c94e64.jpg\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<p><\/p>\n<p>Tu bud\u00fa d\u00e1ta z v\u00fdnimo\u010dn\u00fdch s\u00faborov najprv pre\u010d\u00edtan\u00e9 na Hadoop. Potom bud\u00fa aj tieto dva s\u00fabory zl\u00fa\u010den\u00e9 t\u00fdmi ist\u00fdmi prostriedkami. Po tom bud\u00fa d\u00e1ta transformovan\u00e9 a nahran\u00e9 do DB.<\/p>\n<p><\/p>\n<p>Pochopen\u00edm princ\u00edpov pushdown optimaliz\u00e1cie je mo\u017en\u00e9 ve\u013emi efekt\u00edvne organizova\u0165 mno\u017estvo procesov pr\u00e1ce s ve\u013ek\u00fdmi d\u00e1tami. Takto ned\u00e1vno jedna ve\u013ek\u00e1 spolo\u010dnos\u0165 za p\u00e1r t\u00fd\u017ed\u0148ov nahrala z \u00falo\u017eiska do Hadoop ve\u013ek\u00e9 d\u00e1ta, ktor\u00e9 predt\u00fdm zhroma\u017e\u010fovala nieko\u013eko rokov.<\/p>\n<p>Zdroj: <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? 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