{"id":476178,"date":"2023-08-09T07:26:52","date_gmt":"2023-08-09T07:26:52","guid":{"rendered":""},"modified":"2023-09-05T11:12:10","modified_gmt":"2023-09-05T11:12:10","slug":"cardinality-sql","status":"publish","type":"wiki","link":"https:\/\/oneproxy.pro\/tr\/wiki\/cardinality-sql\/","title":{"rendered":"Kardinalite (SQL)"},"content":{"rendered":"<p>SQL&#039;deki kardinalite, bir veritaban\u0131 tablosunun bir s\u00fctunundaki veya dizinindeki farkl\u0131 de\u011fer say\u0131s\u0131n\u0131 ifade eder. Veri da\u011f\u0131t\u0131m\u0131na ili\u015fkin \u00f6ng\u00f6r\u00fcler sa\u011flad\u0131\u011f\u0131 ve veritaban\u0131 motorunun y\u00fcr\u00fctme planlar\u0131 olu\u015ftururken bilin\u00e7li kararlar almas\u0131na yard\u0131mc\u0131 oldu\u011fu i\u00e7in sorgu optimizasyonunda ve performans ayarlamas\u0131nda \u00e7ok \u00f6nemli bir rol oynar. Kardinalite, veritabanlar\u0131 alan\u0131nda temel bir kavramd\u0131r ve \u00e7e\u015fitli veritaban\u0131 y\u00f6netim sistemlerinde (DBMS) yayg\u0131n olarak kullan\u0131l\u0131r.<\/p>\n<h2>Kardinalli\u011fin (SQL) k\u00f6keninin tarihi ve ilk s\u00f6z\u00fc<\/h2>\n<p>SQL&#039;deki Kardinalite kavram\u0131n\u0131n k\u00f6keni ili\u015fkisel veritabanlar\u0131n\u0131n ilk g\u00fcnlerine kadar uzanabilir. \u0130li\u015fkisel model, Dr. EF Codd taraf\u0131ndan 1970 y\u0131l\u0131nda yay\u0131nlanan \u201cA Relational Model of Data for Large Shared Data Banks\u201d adl\u0131 \u00e7\u0131\u011f\u0131r a\u00e7an makalesinde tan\u0131t\u0131ld\u0131. Bu makalede Codd, verileri sat\u0131rlar ve s\u00fctunlarla birlikte tablolar halinde temsil etme fikrini sundu. verileri i\u015flemek i\u00e7in bir dizi matematiksel i\u015flem.<\/p>\n<p>\u0130li\u015fkisel veritaban\u0131 y\u00f6netim sistemleri geli\u015fip olgunla\u015ft\u0131k\u00e7a \u201c\u00d6nemlilik\u201d terimi daha sonra pop\u00fcler hale geldi. En verimli y\u00fcr\u00fctme plan\u0131n\u0131 se\u00e7mek i\u00e7in bir sorgudan d\u00f6nd\u00fcr\u00fclecek sat\u0131r say\u0131s\u0131n\u0131 tahmin etmenin gerekli hale geldi\u011fi sorgu optimizasyonundaki \u00f6nemi nedeniyle \u00f6n plana \u00e7\u0131kt\u0131.<\/p>\n<h2>Cardinality (SQL) hakk\u0131nda detayl\u0131 bilgi<\/h2>\n<p>SQL veritabanlar\u0131 ba\u011flam\u0131nda Kardinalite, bir s\u00fctunda veya dizinde bulunan farkl\u0131 de\u011ferlerin say\u0131s\u0131n\u0131 ifade eder. Bir tablodaki verilerin da\u011f\u0131t\u0131m\u0131 hakk\u0131nda istatistiksel bilgiler sa\u011flayarak sorgu iyile\u015ftiricinin bir sorguyu i\u015flemenin en etkili yolunu belirlemesine yard\u0131mc\u0131 olur.<\/p>\n<h2>Cardinality&#039;nin (SQL) i\u00e7 yap\u0131s\u0131 ve nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131<\/h2>\n<p>Cardinality&#039;nin i\u00e7 yap\u0131s\u0131 veritaban\u0131 istatistiklerinde korunur. DBMS, sat\u0131r say\u0131s\u0131, farkl\u0131 de\u011ferler ve veri da\u011f\u0131t\u0131m\u0131 hakk\u0131ndaki bilgileri i\u00e7eren tablolar ve dizinler hakk\u0131ndaki istatistikleri saklar. Bir sorgu y\u00fcr\u00fct\u00fcld\u00fc\u011f\u00fcnde, sorgu iyile\u015ftirici bu istatistikleri Kardinaliteyi tahmin etmek ve en uygun sorgu y\u00fcr\u00fctme plan\u0131n\u0131 se\u00e7mek i\u00e7in kullan\u0131r.<\/p>\n<p>Veritaban\u0131 y\u00f6netim sistemi, Cardinality&#039;yi verimli bir \u015fekilde takip etmek i\u00e7in \u00e7e\u015fitli algoritmalar ve veri yap\u0131lar\u0131 kullanabilir. Bu yap\u0131lar, veritaban\u0131nda veri de\u011fi\u015fiklikleri meydana geldi\u011finde periyodik olarak veya iste\u011fe ba\u011fl\u0131 olarak g\u00fcncellenir.<\/p>\n<h2>Cardinality&#039;nin (SQL) temel \u00f6zelliklerinin analizi<\/h2>\n<p>SQL&#039;de Cardinality&#039;nin temel \u00f6zellikleri \u015funlar\u0131 i\u00e7erir:<\/p>\n<ol>\n<li>\n<p><strong>Sorgu Optimizasyonu:<\/strong> Kardinalite, bir sorgunun y\u00fcr\u00fctme plan\u0131n\u0131 belirlemede \u00e7ok \u00f6nemli bir fakt\u00f6rd\u00fcr. Daha y\u00fcksek bir Kardinalite genellikle daha se\u00e7ici dizinlerle sonu\u00e7lan\u0131r ve bu da sorgunun daha h\u0131zl\u0131 y\u00fcr\u00fct\u00fclmesine yol a\u00e7ar.<\/p>\n<\/li>\n<li>\n<p><strong>Veri Da\u011f\u0131t\u0131m Analizi:<\/strong> Kardinalite, bir s\u00fctundaki veri de\u011ferlerinin da\u011f\u0131l\u0131m\u0131na ili\u015fkin \u00f6ng\u00f6r\u00fcler sa\u011flar. \u00c7arp\u0131k veriler veya yinelenen giri\u015fler gibi olas\u0131 veri kalitesi sorunlar\u0131n\u0131n belirlenmesine yard\u0131mc\u0131 olur.<\/p>\n<\/li>\n<li>\n<p><strong>Optimizasyona Kat\u0131l\u0131n:<\/strong> Kardinallik, birle\u015ftirme i\u015flemlerinin optimize edilmesinde \u00f6nemli bir rol oynar. Veritaban\u0131 iyile\u015ftiricisi, i\u00e7 i\u00e7e d\u00f6ng\u00fc birle\u015ftirme, karma birle\u015ftirme veya birle\u015ftirme birle\u015ftirme gibi en verimli birle\u015ftirme stratejisini se\u00e7mek i\u00e7in birle\u015ftirilmi\u015f s\u00fctunlar\u0131n \u00d6nem Derecesini kullan\u0131r.<\/p>\n<\/li>\n<li>\n<p><strong>Dizin Tasar\u0131m\u0131:<\/strong> Kardinalite, veritaban\u0131 indekslerinin etkinli\u011fini etkiler. D\u00fc\u015f\u00fck Kardinaliteli s\u00fctunlar, \u00e7ok fazla se\u00e7icilik sunmad\u0131klar\u0131 i\u00e7in indeksleme i\u00e7in zay\u0131f adaylard\u0131r; y\u00fcksek Kardinaliteli s\u00fctunlar ise indeksleme i\u00e7in daha iyi adaylard\u0131r.<\/p>\n<\/li>\n<\/ol>\n<h2>Kardinalite T\u00fcrleri (SQL)<\/h2>\n<p>\u00dc\u00e7 ana Kardinalite t\u00fcr\u00fc vard\u0131r:<\/p>\n<ol>\n<li>\n<p><strong>D\u00fc\u015f\u00fck Kardinalite:<\/strong> Kardinalitesi d\u00fc\u015f\u00fck bir s\u00fctun, tablodaki toplam sat\u0131r say\u0131s\u0131na g\u00f6re az say\u0131da farkl\u0131 de\u011fere sahiptir. Yayg\u0131n \u00f6rnekler aras\u0131nda, genellikle bir\u00e7ok sat\u0131rda tekrarlanan yaln\u0131zca birka\u00e7 benzersiz de\u011fere sahip olan cinsiyet veya \u00fclke s\u00fctunlar\u0131 yer al\u0131r.<\/p>\n<\/li>\n<li>\n<p><strong>Y\u00fcksek Kardinalite:<\/strong> Kardinalitesi y\u00fcksek bir s\u00fctun, tablodaki toplam sat\u0131r say\u0131s\u0131na g\u00f6re \u00e7ok say\u0131da farkl\u0131 de\u011fere sahiptir. \u00d6rne\u011fin, bir birincil anahtar veya benzersiz tan\u0131mlay\u0131c\u0131 s\u00fctun, her sat\u0131r\u0131n benzersiz bir de\u011fere sahip olmas\u0131 nedeniyle y\u00fcksek Kardinalli\u011fe sahip olma e\u011filimindedir.<\/p>\n<\/li>\n<li>\n<p><strong>Orta Kardinalite:<\/strong> Orta Kardinallik, d\u00fc\u015f\u00fck ve y\u00fcksek Kardinallik aras\u0131ndad\u0131r. Orta Kardinaliteye sahip s\u00fctunlar, orta say\u0131da farkl\u0131 de\u011fere sahiptir; bu da onlar\u0131 d\u00fc\u015f\u00fck Kardinaliteye sahip s\u00fctunlardan daha se\u00e7ici, ancak y\u00fcksek Kardinaliteye sahip s\u00fctunlardan daha az se\u00e7ici k\u0131lar.<\/p>\n<\/li>\n<\/ol>\n<p>\u0130\u015fte \u00fc\u00e7 Kardinalite t\u00fcr\u00fcn\u00fcn kar\u015f\u0131la\u015ft\u0131rmas\u0131:<\/p>\n<table>\n<thead>\n<tr>\n<th>\u00d6nem T\u00fcr\u00fc<\/th>\n<th>Farkl\u0131 De\u011fer Say\u0131s\u0131<\/th>\n<th>Se\u00e7icilik<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>D\u00fc\u015f\u00fck<\/td>\n<td>Bir ka\u00e7<\/td>\n<td>D\u00fc\u015f\u00fck<\/td>\n<\/tr>\n<tr>\n<td>Orta<\/td>\n<td>Il\u0131man<\/td>\n<td>Orta<\/td>\n<\/tr>\n<tr>\n<td>Y\u00fcksek<\/td>\n<td>Bir\u00e7ok<\/td>\n<td>Y\u00fcksek<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Cardinality&#039;yi (SQL) kullanma yollar\u0131, sorunlar ve kullan\u0131ma ili\u015fkin \u00e7\u00f6z\u00fcmler<\/h2>\n<h3>SQL&#039;de Cardinality&#039;yi kullanma yollar\u0131<\/h3>\n<ol>\n<li>\n<p><strong>Sorgu Performans\u0131 Optimizasyonu:<\/strong> Cardinality, sorgu iyile\u015ftiricinin en verimli y\u00fcr\u00fctme plan\u0131n\u0131 se\u00e7mesine yard\u0131mc\u0131 olarak daha h\u0131zl\u0131 sorgu performans\u0131 sa\u011flar.<\/p>\n<\/li>\n<li>\n<p><strong>Dizin Se\u00e7imi:<\/strong> Cardinality&#039;yi analiz ederek daha iyi sorgu performans\u0131 i\u00e7in hangi s\u00fctunlar\u0131n dizine eklenece\u011fi konusunda bilin\u00e7li kararlar verebilirsiniz.<\/p>\n<\/li>\n<li>\n<p><strong>Veri Kalitesi Analizi:<\/strong> Cardinality, veri temizli\u011fi ve bak\u0131m\u0131 a\u00e7\u0131s\u0131ndan kritik olabilecek yinelenen veya eksik verilerin belirlenmesine yard\u0131mc\u0131 olur.<\/p>\n<\/li>\n<\/ol>\n<h3>SQL&#039;de Kardinalite ile \u0130lgili Sorunlar ve \u00c7\u00f6z\u00fcmler<\/h3>\n<ol>\n<li>\n<p><strong>G\u00fcncel Olmayan \u0130statistikler:<\/strong> G\u00fcncelli\u011fini yitirmi\u015f veya hatal\u0131 istatistikler, sorgu planlar\u0131n\u0131n optimumun alt\u0131nda olmas\u0131na neden olabilir. Do\u011fru Kardinalite tahminini sa\u011flamak i\u00e7in veritaban\u0131 istatistiklerini d\u00fczenli olarak g\u00fcncelleyin.<\/p>\n<\/li>\n<li>\n<p><strong>\u00c7arp\u0131k Veri Da\u011f\u0131t\u0131m\u0131:<\/strong> Bir de\u011ferin bir s\u00fctuna hakim oldu\u011fu \u00e7arp\u0131k veri da\u011f\u0131t\u0131m\u0131, verimsiz sorgu planlar\u0131na yol a\u00e7abilir. Bu t\u00fcr senaryolar\u0131 i\u015flemek i\u00e7in b\u00f6l\u00fcmlemeyi veya dizine eklemeyi d\u00fc\u015f\u00fcn\u00fcn.<\/p>\n<\/li>\n<li>\n<p><strong>Histogram Kutusu Boyutu:<\/strong> Kardinalite tahmini i\u00e7in kullan\u0131lan histogramlar farkl\u0131 b\u00f6lme boyutlar\u0131na sahip olabilir ve bu da Kardinalite tahminlerinin kesin olmamas\u0131na neden olabilir. Histogram b\u00f6lmesi boyutunun ayarlanmas\u0131 do\u011frulu\u011fu art\u0131rabilir.<\/p>\n<\/li>\n<\/ol>\n<h2>Ana \u00f6zellikler ve benzer terimlerle di\u011fer kar\u015f\u0131la\u015ft\u0131rmalar<\/h2>\n<h3>Kardinalite ve Yo\u011funluk<\/h3>\n<p>Kardinalite ve Yo\u011funluk, sorgu optimizasyonunda kullan\u0131lan iki temel kavramd\u0131r ancak farkl\u0131 ama\u00e7lara hizmet ederler:<\/p>\n<ul>\n<li>\n<p><strong>Kardinalite<\/strong> bir s\u00fctun veya dizindeki farkl\u0131 de\u011ferlerin say\u0131s\u0131n\u0131 ifade eder ve sorgu iyile\u015ftiricinin bir sorgu taraf\u0131ndan d\u00f6nd\u00fcr\u00fclen sat\u0131r say\u0131s\u0131n\u0131 tahmin etmesine yard\u0131mc\u0131 olur.<\/p>\n<\/li>\n<li>\n<p><strong>Yo\u011funluk<\/strong> Bir indeksteki veri de\u011ferlerinin benzersizli\u011fini temsil eder. Bu, rastgele se\u00e7ilen iki sat\u0131r\u0131n dizine eklenen s\u00fctun i\u00e7in ayn\u0131 de\u011fere sahip olma olas\u0131l\u0131\u011f\u0131n\u0131 g\u00f6steren Kardinalitenin tersidir.<\/p>\n<\/li>\n<\/ul>\n<p>Hem Kardinalite hem de Yo\u011funluk sorgu optimizasyonunu etkilerken, verimli sorgu plan\u0131 se\u00e7imi i\u00e7in sorgu optimize ediciye farkl\u0131 bilgiler sa\u011flar.<\/p>\n<h2>Cardinality (SQL) ile ilgili gelece\u011fin perspektifleri ve teknolojileri<\/h2>\n<p>Teknoloji ilerledik\u00e7e ve veritabanlar\u0131 daha karma\u015f\u0131k hale geldik\u00e7e, SQL&#039;de Cardinality&#039;nin \u00f6nemi artmaya devam edecek. Sorgu optimizasyon algoritmalar\u0131 ve geli\u015fmi\u015f istatistiksel tekniklerdeki gelecekteki geli\u015fmelerin, Kardinalite tahmininin do\u011frulu\u011funu daha da art\u0131rmas\u0131 bekleniyor. Ek olarak, donan\u0131m ve veri taban\u0131 mimarisindeki geli\u015fmeler, Kardinalite hesaplamalar\u0131n\u0131n daha da verimli hale getirilmesine ve veri taban\u0131 sistemlerinin genel performans\u0131n\u0131n iyile\u015ftirilmesine yol a\u00e7acakt\u0131r.<\/p>\n<h2>Proxy sunucular\u0131 Cardinality (SQL) ile nas\u0131l kullan\u0131labilir veya ili\u015fkilendirilebilir?<\/h2>\n<p>OneProxy taraf\u0131ndan sa\u011flananlar gibi proxy sunucular\u0131, web kaynaklar\u0131na eri\u015firken gizlili\u011fi, g\u00fcvenli\u011fi ve performans\u0131 art\u0131rmada hayati bir rol oynar. SQL&#039;deki Cardinality ile do\u011frudan ili\u015fkili olmasa da, proxy sunucular veri eri\u015fimini ve kullan\u0131labilirli\u011fini geli\u015ftirmek i\u00e7in veritaban\u0131 uygulamalar\u0131yla birlikte kullan\u0131labilir.<\/p>\n<p>Proxy sunucular\u0131 s\u0131k eri\u015filen veritaban\u0131 kaynaklar\u0131n\u0131 \u00f6nbelle\u011fe alabilir, veritaban\u0131 sunucusuna ula\u015fan isteklerin say\u0131s\u0131n\u0131 azalt\u0131r ve yan\u0131t s\u00fcrelerini potansiyel olarak iyile\u015ftirebilir. Ek olarak, proxy sunucular istemciler ve veritabanlar\u0131 aras\u0131nda arac\u0131 g\u00f6revi g\u00f6rerek ekstra bir g\u00fcvenlik ve y\u00fck dengeleme katman\u0131 ekleyerek \u00f6zellikle y\u00fcksek trafikli senaryolarda yararl\u0131 olabilir.<\/p>\n<h2>\u0130lgili Ba\u011flant\u0131lar<\/h2>\n<p>SQL&#039;de Cardinality hakk\u0131nda daha fazla bilgi i\u00e7in a\u015fa\u011f\u0131daki kaynaklar\u0131 yararl\u0131 bulabilirsiniz:<\/p>\n<ul>\n<li><a href=\"https:\/\/docs.microsoft.com\/en-us\/previous-versions\/sql\/sql-server-2008\/dd535534(v=sql.100)\" target=\"_new\" rel=\"noopener nofollow\">SQL Server Kardinalite Tahminini Anlamak<\/a><\/li>\n<li><a href=\"https:\/\/www.postgresql.org\/docs\/current\/planner-stats.html\" target=\"_new\" rel=\"noopener nofollow\">PostgreSQL&#039;de Kardinalite Tahmini<\/a><\/li>\n<li><a href=\"https:\/\/dev.mysql.com\/doc\/mysql\/en\/query-optimization.html\" target=\"_new\" rel=\"noopener nofollow\">MySQL Sorgu Optimizasyonu ve Kardinalite<\/a><\/li>\n<\/ul>\n<p>Unutmay\u0131n, Cardinality&#039;yi anlamak, veritaban\u0131 performans\u0131n\u0131 optimize etmek ve verimli sorgu y\u00fcr\u00fctmeyi sa\u011flamak i\u00e7in \u00e7ok \u00f6nemlidir. Veritaban\u0131 teknolojilerindeki en son geli\u015fmeleri takip etmek, bilin\u00e7li kararlar vermenizi ve veri odakl\u0131 uygulamalar\u0131n\u0131z\u0131n t\u00fcm potansiyelini ortaya \u00e7\u0131karman\u0131z\u0131 sa\u011flayacakt\u0131r.<\/p>","protected":false},"featured_media":467828,"menu_order":0,"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"class_list":["post-476178","wiki","type-wiki","status-publish","has-post-thumbnail","hentry"],"acf":{"faq_title":"Frequently Asked Questions about <mark>Cardinality (SQL)<\/mark>","faq_items":[{"question":"What is Cardinality in SQL?","answer":"<p>Cardinality in SQL refers to the number of distinct values present in a column or index of a database table. It helps the database engine optimize queries and make efficient execution plans.<\/p>"},{"question":"How does Cardinality work in SQL?","answer":"<p>Cardinality is maintained within the database statistics, which store information about the number of rows, distinct values, and data distribution. The query optimizer uses this information to estimate the number of rows returned by a query and choose the best execution plan.<\/p>"},{"question":"What are the types of Cardinality in SQL?","answer":"<p>There are three primary types of Cardinality:<\/p><ol><li>Low Cardinality: Few distinct values, often seen in columns like gender or country.<\/li><li>Medium Cardinality: Moderate distinct values, falling between low and high Cardinality.<\/li><li>High Cardinality: Many distinct values, common in primary key or unique identifier columns.<\/li><\/ol>"},{"question":"How can I use Cardinality in SQL?","answer":"<p>Cardinality is essential for:<\/p><ul><li>Optimizing query performance<\/li><li>Selecting appropriate indexes for better performance<\/li><li>Identifying data quality issues like duplicates or missing data<\/li><\/ul>"},{"question":"What are the challenges related to Cardinality in SQL?","answer":"<p>Problems related to Cardinality include outdated statistics, skewed data distribution, and inaccurate histogram bin sizes. Regularly updating statistics and considering partitioning or indexing can address these challenges.<\/p>"},{"question":"How is Cardinality different from Density in SQL?","answer":"<p>Cardinality represents the number of distinct values, while Density indicates the uniqueness of data values in an index. Both impact query optimization but serve different purposes.<\/p>"},{"question":"What is the future perspective of Cardinality in SQL?","answer":"<p>As technology advances, Cardinality's importance will continue to grow, leading to more accurate estimations and efficient query plans. Advancements in hardware and database architecture will further improve Cardinality computations and overall database performance.<\/p>"},{"question":"How can proxy servers be associated with Cardinality in SQL?","answer":"<p>While not directly related, proxy servers can work with database applications to improve data access and availability. They can cache frequently accessed resources, add security layers, and perform load balancing for high-traffic scenarios.<\/p>"}]},"_links":{"self":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/wiki\/476178","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\/476178\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media\/467828"}],"wp:attachment":[{"href":"https:\/\/oneproxy.pro\/tr\/wp-json\/wp\/v2\/media?parent=476178"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}