{"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\/hu\/blog\/kak-peremeshhat-vygruzhat-i-integrirovat-ochen-bolshie-dannye-dyoshevo-i-bystro-chto-takoe-pushdown-optimizatsiya","title":{"rendered":"Hogyan lehet nagy mennyis\u00e9g\u0171 adatot olcs\u00f3n \u00e9s gyorsan mozg\u00e1sba hozni, ki\u00fcr\u00edteni \u00e9s integr\u00e1lni? Mi az a pushdown-optimaliz\u00e1ci\u00f3?","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

B\u00e1rmely nagy adatkezel\u00e9s jelent\u0151s sz\u00e1m\u00edt\u00e1si kapacit\u00e1st ig\u00e9nyel. Az adatok norm\u00e1l \u00e1thelyez\u00e9se egy Hadoop adatb\u00e1zisb\u00f3l hetekig tarthat, vagy annyiba ker\u00fcl, mint egy rep\u00fcl\u0151g\u00e9p sz\u00e1rnya. Nem szeretne v\u00e1rni \u00e9s k\u00f6lts\u00e9gesen k\u00f6ltekezni? Egyens\u00falyozza a terhel\u00e9st k\u00fcl\u00f6nb\u00f6z\u0151 platformok k\u00f6z\u00f6tt. Az egyik m\u00f3dja a pushdown-optimaliz\u00e1l\u00e1s.<\/p>\n

<\/p>\n

Megk\u00e9rtem Oroszorsz\u00e1g vezet\u0151 Informatica term\u00e9kfejleszt\u00e9si \u00e9s adminisztr\u00e1ci\u00f3s edz\u0151j\u00e9t, Alexej Ananyevot, hogy mes\u00e9ljen a pushdown-optimaliz\u00e1l\u00e1s funkci\u00f3j\u00e1r\u00f3l az Informatica Big Data Management (BDM) rendszer\u00e9ben. Tanult valaha Informatica term\u00e9kek haszn\u00e1lat\u00e1r\u00f3l? Val\u00f3sz\u00edn\u0171leg Alexej mutatta be \u00d6nnek a PowerCenter alapjait, \u00e9s magyar\u00e1zta el, hogyan kell t\u00e9rk\u00e9pez\u00e9seket k\u00e9sz\u00edteni. <\/p>\n

<\/p>\n

Alexej Ananyev, a DIS Group k\u00e9pz\u00e9si oszt\u00e1ly\u00e1nak vezet\u0151je<\/strong><\/p>\n

<\/p>\n

Mi az a pushdown?<\/strong><\/p>\n

<\/p>\n

Sokan m\u00e1r ismerik az Informatica Big Data Management (BDM) rendszert. A term\u00e9k k\u00e9pes integr\u00e1lni a nagy adatokat k\u00fcl\u00f6nb\u00f6z\u0151 forr\u00e1sokb\u00f3l, \u00e1thelyezni azokat k\u00fcl\u00f6nb\u00f6z\u0151 rendszerek k\u00f6z\u00f6tt, k\u00f6nny\u0171 hozz\u00e1f\u00e9r\u00e9st biztos\u00edtani, profilozni \u0151ket \u00e9s m\u00e9g sok m\u00e1st.
\n\u00dcgyes kezekben a BDM csod\u00e1kra k\u00e9pes: a feladatok gyorsan \u00e9s minim\u00e1lis sz\u00e1m\u00edt\u00e1si er\u0151forr\u00e1ssal val\u00f3sulnak meg. <\/p>\n

<\/p>\n

\u00d6n is \u00edgy szeretn\u00e9? Tanulja meg a pushdown funkci\u00f3 haszn\u00e1lat\u00e1t a BDM-ben a sz\u00e1m\u00edt\u00e1si terhel\u00e9s k\u00fcl\u00f6nb\u00f6z\u0151 platformok k\u00f6z\u00f6tti eloszt\u00e1s\u00e1hoz. A pushdown technol\u00f3gia lehet\u0151v\u00e9 teszi, hogy a t\u00e9rk\u00e9pez\u00e9st szkriptt\u00e9 alak\u00edtsuk, \u00e9s v\u00e1lasszunk egy k\u00f6rnyezetet, amelyben ez a szkript fut. Az ilyen v\u00e1laszt\u00e1s lehet\u0151s\u00e9ge lehet\u0151v\u00e9 teszi k\u00fcl\u00f6nb\u00f6z\u0151 platformok er\u0151ss\u00e9geinek kombin\u00e1l\u00e1s\u00e1t \u00e9s maxim\u00e1lis teljes\u00edtm\u00e9ny el\u00e9r\u00e9s\u00e9t.<\/p>\n

<\/p>\n

A szkript futtat\u00e1si k\u00f6rnyezet\u00e9nek be\u00e1ll\u00edt\u00e1s\u00e1hoz ki kell v\u00e1lasztania a pushdown t\u00edpus\u00e1t. A szkript teljes m\u00e9rt\u00e9kben futtathat\u00f3 Hadoop-on vagy r\u00e9szben eloszthat\u00f3 a forr\u00e1s \u00e9s a fogad\u00f3 k\u00f6z\u00f6tt. N\u00e9gyf\u00e9le pushdown t\u00edpus l\u00e9tezik. A t\u00e9rk\u00e9pez\u00e9st nem kell szkriptt\u00e9 alak\u00edtani (nat\u00edv). A t\u00e9rk\u00e9pez\u00e9s maxim\u00e1lisan futtathat\u00f3 a forr\u00e1son (forr\u00e1s) vagy teljes eg\u00e9sz\u00e9ben a forr\u00e1son (teljes). A t\u00e9rk\u00e9pez\u00e9s \u00e1talak\u00edthat\u00f3 Hadoop szkriptt\u00e9 is (nincs).<\/p>\n

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

Pushdown-optimaliz\u00e1l\u00e1s<\/strong><\/p>\n

<\/p>\n

A felsorolt n\u00e9gy t\u00edpust k\u00fcl\u00f6nb\u00f6z\u0151 m\u00f3don lehet kombin\u00e1lni \u2013 optimaliz\u00e1lni a pushdown-t a rendszer konkr\u00e9t ig\u00e9nyeihez. P\u00e9ld\u00e1ul gyakran indokoltabb az adatokat az adatb\u00e1zisb\u00f3l kinyerni, saj\u00e1t k\u00e9pess\u00e9geit felhaszn\u00e1lva. Ezen adatok \u00e1talak\u00edt\u00e1s\u00e1t pedig Hadoop-ra b\u00edzni, hogy ne terhelj\u00fck t\u00fal mag\u00e1t az adatb\u00e1zist.<\/p>\n

<\/p>\n

N\u00e9zz\u00fck meg azt az esetet, amikor mind a forr\u00e1s, mind a fogad\u00f3 az adatb\u00e1zisban tal\u00e1lhat\u00f3, \u00e9s a v\u00e9grehajt\u00e1s platformj\u00e1t v\u00e1laszthatjuk: a be\u00e1ll\u00edt\u00e1sokt\u00f3l f\u00fcgg\u0151en ez lehet Informatica, egy adatb\u00e1zis szerver vagy Hadoop. Ez a p\u00e9lda lehet\u0151v\u00e9 teszi a mechanizmus technikai oldal\u00e1nak legpontosabb meg\u00e9rt\u00e9s\u00e9t. Term\u00e9szetesen a val\u00f3s \u00e9letben ilyen helyzet nem fordul el\u0151, de a funkci\u00f3 bemutat\u00e1s\u00e1ra ez a lehet\u0151 legjobban megfelel. <\/p>\n

<\/p>\n

Vegy\u00fck a lek\u00e9pez\u00e9st, amely k\u00e9t t\u00e1bl\u00e1t olvas egy egys\u00e9ges Oracle adatb\u00e1zisb\u00f3l. Az olvas\u00e1si eredm\u00e9nyek pedig legyenek r\u00f6gz\u00edtve ugyanezen adatb\u00e1zis egy t\u00e1bl\u00e1j\u00e1ba. A lek\u00e9pez\u00e9s s\u00e9m\u00e1ja a k\u00f6vetkez\u0151 lesz:<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Informatica BDM 10.2.1 form\u00e1j\u00e1ban ez \u00edgy n\u00e9z ki:<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Pushdown t\u00edpus \u2013 nat\u00edv<\/strong><\/p>\n

<\/p>\n

Ha a nat\u00edv pushdown t\u00edpus\u00e1t v\u00e1lasztjuk, akkor a lek\u00e9pez\u00e9s Informatica-n ker\u00fcl v\u00e9grehajt\u00e1sra. szerveren<\/a> Az adatok az Oracle szerverr\u0151l lesznek olvasva, \u00e1tker\u00fclnek az Informatica szerver\u00e9re, ott \u00e1talakulnak, majd \u00e1tker\u00fclnek a Hadoop-ra. M\u00e1s szavakkal, egy hagyom\u00e1nyos ETL folyamatot kapunk.<\/p>\n

<\/p>\n

Pushdown t\u00edpus \u2013 forr\u00e1s <\/strong><\/p>\n

<\/p>\n

A forr\u00e1s t\u00edpus\u00e1nak v\u00e1laszt\u00e1s\u00e1val lehet\u0151s\u00e9g\u00fcnk van a folyamatunkat elosztani szerverrel<\/a> az adatb\u00e1zisok (DB) \u00e9s a Hadoop k\u00f6z\u00f6tt. Ezzel a be\u00e1ll\u00edt\u00e1ssal v\u00e9grehajtott folyamat sor\u00e1n a t\u00e1bl\u00e1kb\u00f3l adatok lek\u00e9r\u00e9s\u00e9re ir\u00e1nyul\u00f3 lek\u00e9rdez\u00e9sek fognak indulni az adatb\u00e1zisba. A t\u00f6bbi l\u00e9p\u00e9s pedig Hadoop-on val\u00f3sul meg.
\nA v\u00e9grehajt\u00e1s s\u00e9m\u00e1ja a k\u00f6vetkez\u0151k\u00e9ppen fog kin\u00e9zni:<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Lent tal\u00e1lhat\u00f3 egy p\u00e9lda a v\u00e9grehajt\u00e1si k\u00f6rnyezet be\u00e1ll\u00edt\u00e1s\u00e1ra.<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Ebben az esetben a lek\u00e9pez\u00e9s k\u00e9t l\u00e9p\u00e9sben fog v\u00e9grehajt\u00e1sra ker\u00fclni. A be\u00e1ll\u00edt\u00e1saiban azt fogjuk l\u00e1tni, hogy scriptk\u00e9nt alakul, amely a forr\u00e1sra ker\u00fcl elk\u00fcld\u00e9sre. A t\u00e1bl\u00e1k egyes\u00edt\u00e9se \u00e9s az adatok \u00e1talak\u00edt\u00e1sa pedig egy fel\u00fcl\u00edrt lek\u00e9rdez\u00e9s form\u00e1j\u00e1ban fog megt\u00f6rt\u00e9nni a forr\u00e1son.
\nAz al\u00e1bbi k\u00e9pen a BDM optimaliz\u00e1lt lek\u00e9pez\u00e9s\u00e9t l\u00e1tjuk, mik\u00f6zben a forr\u00e1son egy fel\u00fcl\u00edrt lek\u00e9rdez\u00e9s tal\u00e1lhat\u00f3.<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Hadoop szerepe ebben a konfigur\u00e1ci\u00f3ban a adatfolyam kezel\u00e9s\u00e9re \u2013 azok ir\u00e1ny\u00edt\u00e1s\u00e1ra \u2013 korl\u00e1toz\u00f3dik. A lek\u00e9rdez\u00e9s eredm\u00e9nye a Hadoop-ra ker\u00fcl. Az olvas\u00e1s befejez\u00e9se ut\u00e1n a f\u00e1jl a Hadoop-b\u00f3l a fogad\u00f3hoz lesz r\u00f6gz\u00edtve.<\/p>\n

<\/p>\n

Pushdown t\u00edpus \u2013 teljes <\/strong><\/p>\n

<\/p>\n

A teljes pushdown t\u00edpus\u00e1nak v\u00e1laszt\u00e1s\u00e1val a lek\u00e9pez\u00e9s teljesen lek\u00e9rdez\u00e9ss\u00e9 alakul az adatb\u00e1zison. A lek\u00e9rdez\u00e9s eredm\u00e9nye Hadoop-ra ker\u00fcl. Ennek a folyamatnak a s\u00e9m\u00e1ja al\u00e1bb l\u00e1that\u00f3.<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

A be\u00e1ll\u00edt\u00e1s p\u00e9lda lent tal\u00e1lhat\u00f3.<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Ennek eredm\u00e9nyek\u00e9nt egy optimaliz\u00e1lt lek\u00e9pez\u00e9st kapunk, amely hasonl\u00edt az el\u0151z\u0151re. A k\u00fcl\u00f6nbs\u00e9g mind\u00f6ssze annyi, hogy a logika teljes m\u00e9rt\u00e9kben \u00e1tker\u00fcl a fogad\u00f3hoz, mint fel\u00fcl\u00edr\u00e1s form\u00e1j\u00e1ban. Az optimaliz\u00e1lt lek\u00e9pez\u00e9s p\u00e9ld\u00e1ja lent l\u00e1that\u00f3.<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Itt, ahogy az el\u0151z\u0151 esetben is, a Hadoop dirigens szerep\u00e9t t\u00f6lti be. De itt az adatforr\u00e1st teljes eg\u00e9sz\u00e9ben olvass\u00e1k be, majd a feldolgoz\u00e1s logik\u00e1ja a vev\u0151 oldalon val\u00f3sul meg.<\/p>\n

<\/p>\n

Pushdown t\u00edpus \u2013 null<\/strong><\/p>\n

<\/p>\n

A legutols\u00f3 lehet\u0151s\u00e9g egy pushdown t\u00edpus, amelynek keretein bel\u00fcl a t\u00e9rk\u00e9p\u00fcnk Hadoop szkriptt\u00e9 alakul.<\/p>\n

<\/p>\n

Az optimaliz\u00e1lt t\u00e9rk\u00e9p most \u00edgy fog kin\u00e9zni:<\/p>\n

<\/p>\n

\"Hogyan<\/p>\n

<\/p>\n

Itt az adatokat el\u0151sz\u00f6r f\u00e1jlokb\u00f3l olvass\u00e1k be a Hadoop rendszer\u00e9n. Ezut\u00e1n ezzel a rendszerrel egyes\u00edtik a k\u00e9t f\u00e1jlt. Ezt k\u00f6vet\u0151en az adatokat \u00e1talak\u00edtj\u00e1k \u00e9s bet\u00f6ltik az adatb\u00e1zisba.<\/p>\n

<\/p>\n

A pushdown optimaliz\u00e1ci\u00f3 elveinek meg\u00e9rt\u00e9s\u00e9vel nagyon hat\u00e9konyan szervezhetj\u00fck a nagy adatokkal v\u00e9gzett m\u0171veleteket. Nemr\u00e9giben egy nagyv\u00e1llalat mind\u00f6ssze n\u00e9h\u00e1ny h\u00e9t alatt ki tudta export\u00e1lni a Hadoop-b\u00f3l azokat a nagy adatokat, amelyeket addig \u00e9vekig gy\u0171jt\u00f6ttek.<\/p>\n

Forr\u00e1s: habr.com<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\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 […]<\/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\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Hogyan lehet olcs\u00f3n \u00e9s gyorsan \u00e1thelyezni, export\u00e1lni \u00e9s integr\u00e1lni nagyon nagy adatokat? 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