【正文】 基于頁的數(shù)據(jù)結(jié)構(gòu)不再重要了（因為頁不再是數(shù)據(jù)檢索的單位），同時，聚簇也不重要了（因為訪問主存的任何區(qū)域的開銷是一致的）?；謴?fù)算法同樣也需要優(yōu)化，因為很少這種情況：某頁因需要為其他頁省出空間而不得不被移出。 主存也不能幸免于系統(tǒng)崩潰，所以仍然需要實現(xiàn)日志和恢復(fù)機(jī)制，以保證事務(wù)的原子性和持久性。 主存數(shù)據(jù)庫 由于主存的價格已經(jīng)很便宜了，許多應(yīng)有可以購買足夠的主存來保存整個數(shù)據(jù)庫。通常將數(shù)據(jù)生成多個副本，以使從不同位置的訪問開銷最小化。 通過無線連接的用戶帶寬是以太網(wǎng)的 1/10 左右，是 ATM 網(wǎng)的 1/100 左右。如果一個用戶希望以這種方式來指導(dǎo)優(yōu)化，那么他應(yīng)該對優(yōu)化和給定的 DBMS 的能力有一個全面的理 解。當(dāng)將條件變?yōu)?時，將會出現(xiàn)相反的情況。 當(dāng)調(diào)整一個查詢時，第一件事就是確定系統(tǒng)是否使用了你所希望的執(zhí)行計劃。 另外，在重新設(shè)計概念模式時，特別是如果調(diào)整一個現(xiàn)存數(shù)據(jù)庫的模式時，我們需要考慮是否定義視圖來向用戶隱藏這些改變，因為對于用戶來說原始的模式可能更自然一些。而且，我們可能在特定的關(guān)系上加上一些字段來加速一些重要的查詢，即使這樣會 導(dǎo)致對一些信息的冗余存儲（從而使得模式既不是 3NF 也不是 BCNF）。 如果將一個關(guān)系分解為 3NF 或 BCNF 有兩種方式，那么應(yīng)該根據(jù)工作負(fù)載來進(jìn)行選擇。一旦數(shù)據(jù)庫設(shè)計完成并且已經(jīng)被裝載數(shù)據(jù)了，如果要改變概念模式，就需要做出很大的努力去映射受到影響的關(guān)系的內(nèi)容。 為了獲得可 能的最好的性能，對數(shù)據(jù)庫進(jìn)行連續(xù)的調(diào)整是很重要的。 如何區(qū)分設(shè)計和調(diào)整并不是很 重要的 （五）數(shù)據(jù)庫調(diào)整簡介 當(dāng)數(shù)據(jù)庫初始設(shè)計完成后，數(shù)據(jù)庫的實際使用提供了一些有用的詳細(xì)信息，它們可以用來對初始設(shè)計進(jìn)行進(jìn)一步求精。 對于如何區(qū)別數(shù)據(jù)庫設(shè)計和數(shù)據(jù)庫調(diào)整，人們有不同的看法。這樣，盡管查詢總可以從索引受益，但是索引也可能使一個給定的更新加快或變慢。這些參數(shù)的值決定了選擇和連接條件的選擇性。 類似地，對工作負(fù)載中每個更新，我們必須確定： 在哪些屬性上有選擇或連接條件（在 WHERE 語句中），以及有多大的選擇性。 。 11 如果數(shù)據(jù)庫允許多個用戶并發(fā)訪問，或者是分布式數(shù)據(jù)庫，那么這是設(shè)計任務(wù)就變得更復(fù)雜了，還需要考慮 DBMS 的其他特點。用戶有一些特定的要求，如，某些查詢或更新的執(zhí)行速度應(yīng)該有多快，或者每秒鐘必須處理多少個事務(wù)等。今天，眾多領(lǐng)域的發(fā)展需求，例如，多媒體數(shù)據(jù)庫，互動視頻，流數(shù)據(jù)，數(shù)字圖書館等精彩視頻節(jié)目，人類基因圖和 NASA 的地球觀測系統(tǒng)等科學(xué)項目，以及公司對鞏固它們的決策支持處理和有用信息挖掘的渴望，正推動著數(shù)據(jù)庫領(lǐng)域的發(fā)展。第一代Web 站點是把數(shù)據(jù)存儲在操作系統(tǒng)的文件中，而現(xiàn)在，使用 DBMS 存儲數(shù)據(jù)并通過 Web瀏覽器瀏覽數(shù)據(jù)已變得越來越普遍。廣泛使用的軟件包有Baan,Oracle,PeopleSoft,SAP 和 Siebel 等系統(tǒng)，它們先確定大多數(shù)組織機(jī)構(gòu)所遇到的共同任務(wù)（例如，庫存管理，人力資源規(guī)劃，財務(wù)分析等），并提供一個通用的應(yīng)用層以完成這些任務(wù)。相當(dāng)多的研究側(cè)重于功能強(qiáng)大的查詢語言和更豐富的數(shù)據(jù)模型，其重點也放在了支持對企業(yè)各部分?jǐn)?shù)據(jù)的復(fù)雜分析上。并發(fā)編程使用最廣的形式就是數(shù)據(jù)庫程序（稱為事務(wù)）的并發(fā)執(zhí)行。其益處被廣泛認(rèn)同，使用 DBMS 來管理公司數(shù)據(jù)變得很普遍。 1970 年， Edgar Codd 在 IBM 的 San Jose 研究實驗室推出了一種新的，稱為關(guān)系數(shù)據(jù)模型的數(shù)據(jù)表達(dá)框架。直至今天，它還在許多系統(tǒng)中使用。第一個通用的DBMS 是由 Charles Bechman 于 20 世紀(jì) 60 年代早期在通用電器公司設(shè)計的，稱為集成數(shù)據(jù)存儲 (Integrated Data Store).它奠定了網(wǎng)狀數(shù)據(jù)模型的基礎(chǔ)。 rather, we want to create two distinct relations (possibly with different constraints and indexes on each). Incidentally, when we redesign the conceptual schema, especially if we are tuning an existing database schema, it is worth considering whether we should create views to mask these changes from users for whom the original schema is more natural. TUNING QUERIES AND VIEWS If we notice that a query is running much slower than we expected, we have to examine the query carefully to end the problem. Some rewriting of the query, perhaps in conjunction with some index tuning, can often ?x the problem. Similar tuning may be called for if queries on some view run slower than expected. When tuning a query, the first thing to verify is that the system is using the plan that you expect it to use. It may be that the system is not finding the best plan for a variety of 7 reasons. Some mon situations that are not handled efficiently by many optimizers follow: A selection condition involving null values. Selection conditions involving arithmetic or string expressions or conditions using the or connective. For example, if we have a condition = 2* in the WHERE clause, the optimizer may correctly utilize an available index on but fail to utilize an available index on . Replacing the condition by situation. Inability to recognize a sophisticated plan such as an indexonly scan for an aggregation query involving a GROUP BY clause. If the optimizer is not smart enough to and the best plan (using access methods and evaluation strategies supported by the DBMS), some systems allow users to guide the choice of a plan by providing hints to the optimizer。 he received the award in 1973. In the late 1960s, IBM developed the Information Management System (IMS) DBMS, used even today in many major installations. IMS formed the basis for an alternative data representation framework called the hierarchical data model. The SABRE system for making airline reservations was jointly developed by American Airlines and IBM around the same time, and it allowed several people to access the same data through puter work. Interestingly, today the same SABRE system is used to power popular Webbased travel services such as Travelocity! In 1970, Edgar Codd, at IBM’s San Jose Research Laboratory, proposed a new data representation framework called the relational data model. This proved to be a watershed in the development of database systems: it sparked rapid development of several DBMSs based on the relational model, along with a rich body of theoretical results that placed the field on a firm foundation. Codd won the 1981 Turing Award for his seminal work. Database systems matured as an academic discipline, and the popularity of relational DBMSs changed the mercial landscape. Their benefits were widely recognized, and the use of DBMSs for managing corporate data became standard practice. In the 1980s, the relational model consolidated its position as the dominant