{"id":476741,"date":"2023-08-09T07:35:16","date_gmt":"2023-08-09T07:35:16","guid":{"rendered":""},"modified":"2023-09-05T11:13:20","modified_gmt":"2023-09-05T11:13:20","slug":"database-sharding","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/database-sharding\/","title":{"rendered":"Veritaban\u0131 par\u00e7alama"},"content":{"rendered":"

Veritaban\u0131 par\u00e7alama, b\u00fcy\u00fck \u00f6l\u00e7ekli veritabanlar\u0131n\u0131n performans\u0131n\u0131, \u00f6l\u00e7eklenebilirli\u011fini ve g\u00fcvenilirli\u011fini art\u0131rman\u0131n etkili bir y\u00f6ntemidir. Bu teknik, daha b\u00fcy\u00fck veritabanlar\u0131n\u0131 birden fazla sunucuya yay\u0131lm\u0131\u015f daha k\u00fc\u00e7\u00fck, daha h\u0131zl\u0131 ve daha y\u00f6netilebilir par\u00e7alara veya "par\u00e7alara" ay\u0131r\u0131r.<\/p>\n

Veritaban\u0131 Par\u00e7alaman\u0131n Do\u011fu\u015fu ve Evrimi<\/h2>\n

Veritaban\u0131 par\u00e7alama kavram\u0131, b\u00fcy\u00fck veri ve y\u00fcksek h\u0131zl\u0131 internet \u00e7a\u011f\u0131nda b\u00fcy\u00fck miktarlarda veriyi y\u00f6netmenin zorluklar\u0131ndan ortaya \u00e7\u0131kt\u0131. 2000'li y\u0131llar\u0131n ba\u015f\u0131nda web tabanl\u0131 uygulamalar ve hizmetler h\u0131zla geni\u015fledik\u00e7e, geleneksel ili\u015fkisel veritabanlar\u0131 muazzam veri hacimleriyle ba\u015fa \u00e7\u0131kmakta zorland\u0131.<\/p>\n

Veritaban\u0131 par\u00e7alamadan ilk olarak Google'\u0131n BigTable'\u0131 ve Amazon'un Dynamo'su ba\u011flam\u0131nda bahsedildi. Bu veritaban\u0131 sistemleri, daha iyi performans ve \u00f6l\u00e7eklenebilirlik i\u00e7in b\u00fcy\u00fck veri k\u00fcmelerini bir\u00e7ok sunucuya da\u011f\u0131tmak \u00fczere tasarlanm\u0131\u015ft\u0131r. Zamanla, MySQL ve PostgreSQL dahil olmak \u00fczere \u00e7e\u015fitli veritaban\u0131 y\u00f6netim sistemleri, kendi par\u00e7alama s\u00fcr\u00fcmlerini sunarak tekni\u011fi geli\u015ftirdi ve b\u00fcy\u00fck veritabanlar\u0131n\u0131n y\u00f6netiminde standart bir uygulama haline getirdi.<\/p>\n

Veritaban\u0131 Par\u00e7alama: Konuyu Geni\u015fletmek<\/h2>\n

Veritaban\u0131 par\u00e7alama, verilerin yatay b\u00f6l\u00fcmlere veya par\u00e7alara b\u00f6l\u00fcnd\u00fc\u011f\u00fc ve bu par\u00e7alar\u0131n ayr\u0131 veritaban\u0131 sunucular\u0131na da\u011f\u0131t\u0131ld\u0131\u011f\u0131 bir veritaban\u0131 b\u00f6l\u00fcmleme t\u00fcr\u00fcd\u00fcr. Her par\u00e7a, daha b\u00fcy\u00fck veritaban\u0131n\u0131n bir par\u00e7as\u0131n\u0131 olu\u015fturur ve di\u011ferlerinden ba\u011f\u0131ms\u0131z olarak \u00e7al\u0131\u015f\u0131r. Bu, her bir par\u00e7aya di\u011ferlerinden ayr\u0131 olarak eri\u015filebilece\u011fi, y\u00f6netilebilece\u011fi ve yap\u0131land\u0131r\u0131labilece\u011fi anlam\u0131na gelir; bu da veritaban\u0131 sisteminin genel performans\u0131n\u0131 art\u0131r\u0131r.<\/p>\n

Bu teknik \u00f6zellikle b\u00fcy\u00fck veri k\u00fcmeleriyle, y\u00fcksek i\u015flem oranlar\u0131yla veya her ikisiyle birden u\u011fra\u015fmak zorunda olan uygulamalar i\u00e7in faydal\u0131d\u0131r. Par\u00e7alama, verileri birden fazla sunucuya da\u011f\u0131tarak herhangi bir sunucunun darbo\u011faz olu\u015fturmas\u0131n\u0131 \u00f6nler, b\u00f6ylece performans\u0131 art\u0131r\u0131r ve veritaban\u0131 sisteminin \u00f6l\u00e7eklenebilirli\u011fini sa\u011flar.<\/p>\n

Veritaban\u0131 Par\u00e7alaman\u0131n \u0130\u00e7 \u00c7al\u0131\u015fmalar\u0131<\/h2>\n

Par\u00e7alama, verileri belirli bir par\u00e7alama anahtar\u0131na g\u00f6re da\u011f\u0131tarak \u00e7al\u0131\u015f\u0131r. Bu anahtar, m\u00fc\u015fterinin co\u011frafi konumu, kullan\u0131c\u0131n\u0131n kimli\u011fi veya verilerin olduk\u00e7a e\u015fit da\u011f\u0131l\u0131m\u0131n\u0131 sa\u011flayan ba\u015fka bir parametre gibi bir \u00f6zellik olabilir.<\/p>\n

Bir sorgu y\u00fcr\u00fct\u00fcld\u00fc\u011f\u00fcnde, veritaban\u0131 y\u00f6netim sistemi, par\u00e7alama anahtar\u0131n\u0131 kullanarak ilgili verileri i\u00e7eren par\u00e7ay\u0131 tan\u0131mlar. Daha sonra veri taban\u0131n\u0131n tamam\u0131n\u0131 arama ihtiyac\u0131n\u0131 atlayarak verileri do\u011frudan s\u00f6z konusu par\u00e7adan al\u0131r. Bu, veri alma h\u0131z\u0131n\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131r\u0131r ve genel sistem performans\u0131n\u0131 art\u0131r\u0131r.<\/p>\n

Ancak bir par\u00e7alama stratejisini dikkatli bir \u015fekilde tasarlamak \u00e7ok \u00f6nemlidir. Uygun olmayan bir par\u00e7alama anahtar\u0131, dengesiz veri da\u011f\u0131t\u0131m\u0131na yol a\u00e7arak baz\u0131 sunucular\u0131n a\u015f\u0131r\u0131 y\u00fcklenmesine, di\u011ferlerinin ise yetersiz kullan\u0131lmas\u0131na neden olabilir.<\/p>\n

Veritaban\u0131 Par\u00e7alaman\u0131n Temel \u00d6zellikleri<\/h2>\n
    \n
  1. \u00d6l\u00e7eklenebilirlik<\/strong>: Par\u00e7alama, veritaban\u0131 y\u00fck\u00fcn\u00fc birden fazla sunucuya da\u011f\u0131tarak \u00f6l\u00e7eklenebilirli\u011fi art\u0131r\u0131r.<\/li>\n
  2. Verim<\/strong>: Par\u00e7alama, sorgular\u0131n veritaban\u0131n\u0131n tamam\u0131 yerine tek bir par\u00e7aya eri\u015fmesine izin verdi\u011finden, veri al\u0131m\u0131 ve depolamas\u0131 daha h\u0131zl\u0131 hale gelir.<\/li>\n
  3. Kullan\u0131labilirlik ve Yedeklilik<\/strong>: Par\u00e7alamada, bir par\u00e7an\u0131n ar\u0131zalanmas\u0131 t\u00fcm veritaban\u0131n\u0131 \u00e7\u00f6kertmez. Ayr\u0131ca, veri kullan\u0131labilirli\u011fini sa\u011flamak i\u00e7in par\u00e7alar birden fazla sunucuda \u00e7o\u011falt\u0131labilir.<\/li>\n
  4. Co\u011frafi da\u011f\u0131l\u0131m<\/strong>: Par\u00e7alar, kullan\u0131c\u0131lar\u0131n co\u011frafi konumuna g\u00f6re konumland\u0131r\u0131labilir; bu, gecikmeyi azaltabilir ve performans\u0131 art\u0131rabilir.<\/li>\n<\/ol>\n

    Veritaban\u0131 Par\u00e7alama T\u00fcrleri<\/h2>\n\n\n\n\n\n\n\n
    Par\u00e7alama T\u00fcr\u00fc<\/th>\nTan\u0131m<\/th>\n<\/tr>\n<\/thead>\n
    Yatay Par\u00e7alama<\/strong><\/td>\nVeritaban\u0131n\u0131 sat\u0131rlara b\u00f6ler ve bunlar\u0131 farkl\u0131 par\u00e7alara da\u011f\u0131t\u0131r.<\/td>\n<\/tr>\n
    Dikey Par\u00e7alama<\/strong><\/td>\nVeritaban\u0131n\u0131 s\u00fctunlara veya ilgili s\u00fctun gruplar\u0131na b\u00f6ler ve bunlar\u0131 farkl\u0131 par\u00e7alara da\u011f\u0131t\u0131r.<\/td>\n<\/tr>\n
    \u0130\u015flevsel Par\u00e7alama<\/strong><\/td>\nVeritaban\u0131n\u0131 i\u015flevselli\u011fe veya i\u015f gereksinimlerine g\u00f6re b\u00f6ler.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Veritaban\u0131 Par\u00e7alaman\u0131n Uygulanmas\u0131 ve Y\u00f6netilmesi<\/h2>\n

    Veritaban\u0131 par\u00e7alaman\u0131n uygulanmas\u0131 performans, \u00f6l\u00e7eklenebilirlik ve art\u0131kl\u0131k ile ilgili sorunlar\u0131 \u00e7\u00f6zebilir. Ancak par\u00e7alama ayn\u0131 zamanda birden fazla par\u00e7an\u0131n y\u00f6netilmesindeki karma\u015f\u0131kl\u0131k, veri tutarl\u0131l\u0131\u011f\u0131n\u0131n sa\u011flanmas\u0131 ve gerekti\u011finde yeniden par\u00e7alama gibi yeni zorluklar\u0131 da beraberinde getirir.<\/p>\n

    \u00c7e\u015fitli veritaban\u0131 y\u00f6netim sistemleri bu zorluklara \u00e7\u00f6z\u00fcmler sunmaktad\u0131r. \u00d6rne\u011fin, MongoDB otomatik par\u00e7alamay\u0131 ve yeniden par\u00e7alamay\u0131 destekler ve PostgreSQL par\u00e7alamay\u0131 verimli bir \u015fekilde y\u00f6netmek i\u00e7in ara\u00e7lar sa\u011flar.<\/p>\n

    Veritaban\u0131 Par\u00e7alaman\u0131n Benzer Kavramlarla Kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131<\/h2>\n\n\n\n\n\n\n\n
    Terim<\/th>\nTan\u0131m<\/th>\n<\/tr>\n<\/thead>\n
    Veritaban\u0131 Par\u00e7alama<\/strong><\/td>\nPerformans\u0131 ve \u00f6l\u00e7eklenebilirli\u011fi art\u0131rmak i\u00e7in bir veritaban\u0131n\u0131 birden \u00e7ok sunucuya b\u00f6ler.<\/td>\n<\/tr>\n
    Veritaban\u0131 B\u00f6l\u00fcmleme<\/strong><\/td>\nBir veritaban\u0131n\u0131 daha k\u00fc\u00e7\u00fck, daha y\u00f6netilebilir par\u00e7alara b\u00f6ler ancak bunlar genellikle ayn\u0131 sunucuda depolan\u0131r.<\/td>\n<\/tr>\n
    \u00c7o\u011faltma<\/strong><\/td>\nYedekleme ve kullan\u0131labilirlik i\u00e7in t\u00fcm veritaban\u0131n\u0131n kopyalar\u0131n\u0131 birden fazla sunucuda olu\u015fturur.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    Veritaban\u0131 Par\u00e7alaman\u0131n Gelece\u011fi<\/h2>\n

    Veri hacimlerinin katlanarak artmaya devam etmesi nedeniyle verimli veri y\u00f6netimi \u00f6ncelik olmaya devam edecek. Makine \u00f6\u011frenimi ve yapay zekadaki geli\u015fmelerin par\u00e7alama stratejilerini iyile\u015ftirmesi ve s\u00fcreci daha da otomatikle\u015ftirmesi muhtemeldir. Ek olarak, par\u00e7alaman\u0131n bulut tabanl\u0131 veritabanlar\u0131yla entegrasyonu, veritaban\u0131 \u00f6l\u00e7eklenebilirli\u011fi ve performans\u0131 i\u00e7in yeni yollar a\u00e7acakt\u0131r.<\/p>\n

    Proxy Sunucular\u0131 ve Veritaban\u0131 Par\u00e7alama<\/h2>\n

    Performans\u0131 ve veri g\u00fcvenli\u011fini art\u0131rmak i\u00e7in proxy sunucular veritaban\u0131 par\u00e7alamayla birlikte kullan\u0131labilir. \u00d6rne\u011fin, bir proxy sunucusu, istekleri par\u00e7alama anahtar\u0131na g\u00f6re uygun par\u00e7aya y\u00f6nlendirecek ve b\u00f6ylece sorgu performans\u0131n\u0131 iyile\u015ftirecek \u015fekilde yap\u0131land\u0131r\u0131labilir. Ayr\u0131ca proxy sunucular, ek bir g\u00fcvenlik katman\u0131 sa\u011flayarak, par\u00e7alara do\u011frudan eri\u015fimi \u00f6nleyerek veritaban\u0131 par\u00e7alar\u0131n\u0131n g\u00fcvenli\u011finin sa\u011flanmas\u0131na yard\u0131mc\u0131 olabilir.<\/p>\n

    \u0130lgili Ba\u011flant\u0131lar<\/h2>\n
      \n
    1. Google'\u0131n BigTable'\u0131<\/a><\/li>\n
    2. Amazon'un Dinamosu<\/a><\/li>\n
    3. MongoDB Par\u00e7alama<\/a><\/li>\n
    4. PostgreSQL Par\u00e7alama<\/a><\/li>\n<\/ol>\n

      Sonu\u00e7 olarak, veritaban\u0131 par\u00e7alama, b\u00fcy\u00fck, veri yo\u011funluklu uygulamalar\u0131n y\u00f6netilmesinde temel bir stratejidir. Daha y\u00fcksek performans, geli\u015fmi\u015f \u00f6l\u00e7eklenebilirlik ve art\u0131r\u0131lm\u0131\u015f g\u00fcvenilirlik potansiyeli sunan, veritaban\u0131 y\u00f6neticilerinin ve geli\u015ftiricilerinin elindeki g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r.<\/p>","protected":false},"featured_media":468169,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476741","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about Database Sharding: An Essential Strategy for Data Management<\/mark>","faq_items":[{"question":"What is database sharding?","answer":"

      Database sharding is a data management strategy where a large database is broken down into smaller, more manageable parts called \"shards.\" These shards are distributed across multiple servers to enhance performance, scalability, and reliability.<\/p>"},{"question":"When was database sharding first mentioned?","answer":"

      Database sharding was first mentioned in the context of Google's BigTable and Amazon's Dynamo. These were early database systems designed to distribute large data sets across many servers for improved performance and scalability.<\/p>"},{"question":"How does database sharding work?","answer":"

      Sharding works by dividing the data based on a specific sharding key. This key is used to determine the shard containing the relevant data when a query is executed. The data is then retrieved directly from that shard, bypassing the need to search the entire database.<\/p>"},{"question":"What are some key features of database sharding?","answer":"

      Some key features of database sharding include scalability (as it distributes the database load across multiple servers), improved performance (as it allows queries to access a single shard rather than the entire database), availability and redundancy (with sharding, the failure of one shard doesn't impact the entire database), and geographical distribution (shards can be located based on the geographic location of users to reduce latency).<\/p>"},{"question":"What are the different types of database sharding?","answer":"

      There are three main types of database sharding: horizontal sharding (where the database is divided into rows and distributed across different shards), vertical sharding (where the database is divided into columns or groups of related columns and distributed across different shards), and functional sharding (where the database is split based on functionality or business requirements).<\/p>"},{"question":"How can proxy servers be used with database sharding?","answer":"

      Proxy servers can be used in conjunction with database sharding to enhance performance and data security. They can route requests to the appropriate shard based on the sharding key, improving query performance. Proxy servers can also provide an additional layer of security to the database shards by preventing direct access.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476741","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki"}],"about":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/types\/wiki"}],"version-history":[{"count":0,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476741\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/468169"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476741"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}