{"id":91048,"date":"2020-08-08T01:42:02","date_gmt":"2020-08-07T23:42:02","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/ne-stoit-polzovatsya-offset-i-limit-v-zaprosah-s-razbieniem-na-straniczy"},"modified":"2020-08-08T01:42:02","modified_gmt":"2020-08-07T23:42:02","slug":"ne-stoit-polzovatsya-offset-i-limit-v-zaprosah-s-razbieniem-na-straniczy","status":"publish","type":"post","link":"https:\/\/prohoster.info\/et\/blog\/administrirovanie\/ne-stoit-polzovatsya-offset-i-limit-v-zaprosah-s-razbieniem-na-straniczy","title":{"rendered":"\u00c4rge kasutage OFFSET ja LIMIT lehe jagamise p\u00e4ringutes.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Need p\u00e4evad on m\u00f6\u00f6das, mil ei olnud vaja andmebaaside j\u00f5udluse optimeerimise p\u00e4rast muretseda. Aeg ei seisa paigal. Iga uus tehnoloogiaettev\u00f5tja soovib luua j\u00e4rgmist Facebooki, p\u00fc\u00fcdledes samas koguda k\u00f5iki andmeid, mis on nende k\u00e4eulatuses. Need andmed on ettev\u00f5tetele vajalikud, et paremini koolitada mudeleid, mis aitavad raha teenida. Sellistes tingimustes peavad arendajad looma selliseid API-sid, mis v\u00f5imaldavad kiiresti ja usaldusv\u00e4\u00e4rselt t\u00f6\u00f6tada tohutute andmemahtudega.<\/p>\n

\"\u00c4rge<\/a><\/noindex>
\n<\/a><\/noindex>
\nKui olete m\u00f5nda aega tegelenud rakenduste v\u00f5i andmebaaside serveripoolsete osade projekteerimisega, siis olete t\u00f5en\u00e4oliselt kirjutanud koodi lehe jagamise p\u00e4ringute t\u00e4itmiseks. N\u00e4iteks \u2014 sellise:<\/p>\n

SELECT * FROM table_name LIMIT 10 OFFSET 40\n<\/code><\/pre>\n
\nKas see on t\u00f5si?<\/p>\n
Kuid kui te olete lehe jagamist teinud just nii, pean kahetsema, et olete seda teinud kaugel k\u00f5ige t\u00f5husamal viisil.<\/p>\n
Kas soovite mulle vastu vaielda? Saate<\/a><\/noindex> ei<\/a><\/noindex> kulutada<\/a><\/noindex> aega<\/a><\/noindex>. Slack<\/a><\/noindex>, Shopify<\/a><\/noindex> ja Mixmax<\/a><\/noindex> kasutavad juba tehnikaid, millest ma t\u00e4na r\u00e4\u00e4kida tahan.<\/p>\n
Nimetage v\u00e4hemalt \u00fcks tagapoolt arendaja, kes pole kunagi kasutanud OFFSET<\/code> ja LIMIT<\/code> lehtede jagamise p\u00e4ringute t\u00e4itmiseks. MVP-s (Minimum Viable Product, minimaalne eluj\u00f5uline toode) ja projektides, kus kasutatakse v\u00e4ikeseid andmemahtusid, on see l\u00e4henemine t\u00e4iesti rakendatav. See, nii \u00f6elda, \"lihtsalt t\u00f6\u00f6tab\".<\/p>\n
Aga kui on vaja nullist luua usaldusv\u00e4\u00e4rseid ja t\u00f5husaid s\u00fcsteeme, tuleks ette m\u00f5elda andmebaaside p\u00e4ringute t\u00e4itmise efektiivsusele, mida sellistes s\u00fcsteemides kasutatakse.<\/p>\n
T\u00e4na r\u00e4\u00e4gime probleemidest, mis kaasnevad laialdaselt kasutatavate (kahjuks) lehtede jagamise p\u00e4ringute t\u00e4itmise mehhanismide rakendustega, ja sellest, kuidas saavutada k\u00f5rge j\u00f5udlus selliste p\u00e4ringute t\u00e4itmisel.<\/p>\n
Mis on valesti OFFSET-i ja LIMIT-iga?<\/h2>\n
\nNagu juba mainitud, OFFSET<\/code> ja LIMIT<\/code> n\u00e4itavad nad end suurep\u00e4raselt projektides, kus ei pea t\u00f6\u00f6tama suurte andmemahtudega.<\/p>\n
Probleem tekib siis, kui andmebaas kasvab nii suureks, et ei mahu enam serveri m\u00e4llu. Samas tuleb selle andmebaasiga t\u00f6\u00f6tades kasutada lehek\u00fcljep\u00f5hiseid p\u00e4ringuid.<\/p>\n
Selle probleemi ilmnemiseks peab tekkima olukord, kus andmebaasi halduss\u00fcsteem peab iga lehek\u00fcljep\u00f5hise p\u00e4ringu t\u00e4itmisel p\u00f6\u00f6rduma ebaefektiivse t\u00e4istabeli skaneerimise (Full Table Scan) poole (samal ajal v\u00f5ivad toimuda andmete lisamine ja kustutamine, ja vanad andmed ei ole meile vajalikud!).<\/p>\n
Mis on \"t\u00e4ielik tabeli skaneerimine\" (v\u00f5i \"j\u00e4rjekorraga tabeli vaatamine\", Sequential Scan)? See on toiming, mille k\u00e4igus andmebaasiserver loeb j\u00e4rjestikuuliselt l\u00e4bi iga tabeli rea, st andmed, mis seal sisaldub, ning kontrollib neid m\u00e4\u00e4ratud tingimuse j\u00e4rgi. On teada, et see skaneerimist\u00fc\u00fcp on aeglaseim. Probleem on selles, et selle teostamise k\u00e4igus tehakse palju sisendi\/v\u00e4ljundi operatsioone, mis h\u00f5lmavad serveri ketas\u00fcsteemi. Situatsiooni halvendavad viivitused, mis kaasnevad kettal salvestatud andmetega t\u00f6\u00f6tamisel, ning see, et andmete edastamine kettalt m\u00e4lu on ressursimahukas toiming.<\/p>\n
N\u00e4iteks, teil on kirjed 100000000 kasutajast ja teete p\u00e4ringu konstruktsiooniga OFFSET 50000000<\/code>. See t\u00e4hendab, et andmebaasiserver peab laadima k\u00f5ik need kirjed (ja need pole ju meile isegi vajalikud!), paigutama need m\u00e4lu ning seej\u00e4rel v\u00f5tma, \u00fctleme, 20 tulemust, millest on teatatud LIMIT<\/code>.<\/p>\n
Oletagem, et see v\u00f5ib v\u00e4lja n\u00e4ha nii: \"vali read 50000 kuni 50020 100000-st\". See t\u00e4hendab, et s\u00fcsteem peab p\u00e4ringu t\u00e4itmiseks esmalt laadima 50000 rida. Kas n\u00e4ete, kui palju tarbetut t\u00f6\u00f6d tal tuleb teha?<\/p>\n
Kui te ei usu, vaadake n\u00e4idet, mille ma l\u00f5in v\u00f5imaluste abil db-fiddle.com<\/a><\/noindex>.\u00a0<\/p>\n
\"\u00c4rge
\nN\u00e4ide db-fiddle.com lehelt<\/i><\/p>\n
Vasakul, v\u00e4ljadel Schema SQL<\/code>, on kood, mis sisestab andmebaasi 100000 rida, ja paremal, v\u00e4ljadel Query SQL<\/code>, on esitatud kaks p\u00e4ringut. Esimene, aeglane, n\u00e4eb v\u00e4lja selline:<\/p>\n
SELECT *\nFROM `docs`\nLIMIT 10 OFFSET 85000;\n<\/code><\/pre>\n
\nTeine, mis on t\u00f5hus lahendus sama \u00fclesande jaoks, on selline:<\/p>\n
SELECT *\nFROM `docs`\nWHERE id > 85000\nLIMIT 10;\n<\/code><\/pre>\n
\nNende p\u00e4ringute t\u00e4itmiseks piisab, kui vajutada nuppu Run<\/code> lehe \u00fclaosas. P\u00e4rast seda v\u00f5rrelgem p\u00e4ringute t\u00e4itmise aega. Selgub, et ebaefektiivse p\u00e4ringu t\u00e4itmiseks kulub v\u00e4hemalt 30 korda rohkem aega kui teise t\u00e4itmiseks (iga k\u00e4ivitamise korral v\u00f5ib see aeg varieeruda, n\u00e4iteks s\u00fcsteem v\u00f5ib teatada, et esimese p\u00e4ringu t\u00e4itmiseks kulus 37 ms, teine aga 1 ms).<\/p>\n
Ja kui andmeid on rohkem, halveneb see veelgi (kui soovite selles veenduda, vaadake minu an example<\/a><\/noindex> 10 miljoni realise andmestiku n\u00e4idet).<\/p>\n
See, mida me just arutasime, peaks andma teile mingisuguse arusaama sellest, kuidas andmebaasi p\u00e4ringud tegelikult t\u00f6\u00f6tavad.<\/p>\n
Pidage meeles, et mida suurem on v\u00e4\u00e4rtus OFFSET<\/code> \u2014 seda kauem v\u00f5tab p\u00e4ringu t\u00e4itmine aega.<\/p>\n
Mida kasutada kombinatsiooni OFFSET ja LIMIT asemel?<\/h2>\n
\nKombinatsiooni asemel OFFSET<\/code> ja LIMIT<\/code> on m\u00f5istlik kasutada j\u00e4rgnevat struktuuri:<\/p>\n
SELECT * FROM table_name WHERE id > 10 LIMIT 20\n<\/code><\/pre>\n
\nSee on lehekestamine, mis p\u00f5hineb kursori kasutamisel.<\/p>\n
Selle asemel, et s\u00e4ilitada praeguseid OFFSET<\/code> ja LIMIT<\/code> ja edastada neid iga p\u00e4ringuga, tuleb salvestada viimane saadud p\u00f5hiv\u00f5ti (tavaliselt see on ID<\/code>) ja LIMIT<\/code>, mille tulemusena saadakse p\u00e4ringud, mis meenutavad \u00fclaltoodud.<\/p>\n
Miks? Asja on selles, et kui te m\u00e4rkite selgelt viimase loetud rea identifikaatori, siis te annate oma andmebaasi haldustarkvarale teada, kust alustada vajalike andmete otsimist. Otsing toimub t\u00f5husalt t\u00e4nu v\u00f5tme kasutamisele, s\u00fcsteem ei pea h\u00e4irima, et otsida ridu, mis j\u00e4\u00e4vad v\u00e4ljapoole n\u00e4idatud vahemikku.<\/p>\n
Vaadakem j\u00e4rgmisi erinevate p\u00e4ringute j\u00f5udluse v\u00f5rdlusi. Siin on ebaefektiivne p\u00e4ring.<\/p>\n
\"\u00c4rge
\nAeglane p\u00e4ring<\/i><\/p>\n
Ja siin on selle p\u00e4ringu optimeeritud versioon.<\/p>\n
\"\u00c4rge
\nKiire p\u00e4ring<\/i><\/p>\n
M\u00f5lemad p\u00e4ringud tagastavad t\u00e4pselt sama andmehulga. Kuid esimese t\u00e4itmiseks kulub 12,80 sekundit, teise jaoks aga 0,01 sekundit. Tunnete erinevust?<\/p>\n
V\u00f5imalikud probleemid<\/h2>\n
\nEffektiivse p\u00e4ringute t\u00e4itmise meetodi tagamiseks peab tabelis olema veerg (v\u00f5i veerud), mis sisaldavad unikaalseid ja j\u00e4rjestatud indekseid, nagu t\u00e4isarvuline identifikaator. M\u00f5ningatel spetsiifilistel juhtudel v\u00f5ib see m\u00e4\u00e4rata, kas selliseid p\u00e4ringuid on v\u00f5imalik kasutada andmebaasi t\u00f6\u00f6 kiirusel parandamiseks.<\/p>\n
Loomulikult, p\u00e4ringute koostamisel tuleb arvesse v\u00f5tta tabelite arhitektuuri erip\u00e4ra ning valida mehhanismid, mis n\u00e4itavad end olemasolevates tabelites parimat. seda<\/a><\/noindex> artiklit.<\/p>\n
Kui seisame silmitsi primaarv\u00f5tme puudumise probleemiga, n\u00e4iteks kui meil on tabel, kus on \"palju-palju\", siis traditsiooniline l\u00e4henemine, mis eeldab rakendamist OFFSET<\/code> ja LIMIT<\/code>, sobib meile kindlasti. Kuid selle rakendamine v\u00f5ib tuua kaasa potentsiaalselt aeglaste p\u00e4ringute t\u00e4itmise. Sellisel juhul soovitaksin kasutada automaatselt suurenemist toetavat primaarv\u00f5tit, isegi kui see on vajalik ainult lehek\u00fcljel tehtavate p\u00e4ringute t\u00e4itmiseks.<\/p>\n
Kui teema huvitab \u2014 siin on<\/a><\/noindex>, siin on<\/a><\/noindex> ja siin on<\/a><\/noindex> \u2014 m\u00f5ned kasulikud materjalid.<\/p>\n
Kokkuv\u00f5te<\/h2>\n
\nPeamine j\u00e4reldus, mille me teha saame, on see, et olenemata andmebaasi suurusest tuleb alati anal\u00fc\u00fcsida p\u00e4ringute t\u00e4itmise kiirus. T\u00e4nap\u00e4eval on lahenduste skaleeritavus \u00e4\u00e4rmiselt oluline, ja kui alustada s\u00fcsteemi projekteerimist \u00f5igesti, v\u00f5ib see tulevikus vabastada arendaja paljusid probleemidest.<\/p>\n
Kuidas te anal\u00fc\u00fcsite ja optimeerite andmebaaside p\u00e4ringuid?<\/b><\/p>\n
\"\u00c4rge<\/a><\/noindex>
\n
Allikas: habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"
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Aeg ei seisa paigal. Iga uus k\u00f5rgtehnoloogiate ettev\u00f5tja soovib luua j\u00e4rjekordse Facebooki, p\u00fc\u00fcdes samal ajal koguda k\u00f5iki andmeid, millele ta ulatuda suudab. Need andmed on ettev\u00f5ttele vajalikud kvaliteetsemate mudelite \u00f5petamiseks, mis aitavad raha teenida. 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