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            [翻譯]Berkeley DB 文檔 - C++入門篇 - 1.3節 - 訪問方式(Access Methods)

            Access Methods
            訪問方式

            While this manual will focus primarily on the BTree access method, it is still useful to briefly describe all of the access methods that DB makes available.
            本手冊先來關注一下B樹的訪問方式,這對概述DB其他可用的方式也有幫助.

            Note that an access method can be selected only when the database is created. Once selected, actual API usage is generally identical across all access methods. That is, while some exceptions exist, mechanically you interact with the library in the same way regardless of which access method you have selected.
            注意,只能在數據庫創建時設定訪問的方式.一旦選定,所有的訪問方式的API的使用實際上基本一致的.也就是說,雖然有一些例外的存在,但基本上你可以照本宣章的通過同樣的途徑控制數據庫而不用操心你選用的是何種方式.

            The access method that you should choose is gated first by what you want to use as a key, and then secondly by the performance that you see for a given access method.
            你選擇訪問的方式首先要考慮的是用什么來做鍵,然后根據性能選擇合適的訪問方式.

            The following are the available access methods:
            下面是可用的訪問方式:

            BTree    
            B樹

            Data is stored in a sorted, balanced tree structure. Both the key and the data for BTree records can be arbitrarily complex. That is, they can contain single values such as an integer or a string, or complex types such as a structure. Also, although not the default behavior, it is possible for two records to use keys that compare as equals. When this occurs, the records are considered to be duplicates of one another.
            數據被保存到有序平衡樹中.鍵和值都可以是任意復雜的.也就是說,他們(鍵和值)可以是單一的類型比如整數或字串,也可以是復雜的類型比如一個結構體.另外,盡管不是默認的行為,擁有兩個鍵等同的記錄也是可以的.這種情況下,這些記錄被認為一個是另一個的副本.

            Hash    
            哈希

            Data is stored in an extended linear hash table. Like BTree, the key and the data used for Hash records can be of arbitrarily complex data. Also, like BTree, duplicate records are optionally supported.
            數據被保存在一個擴展的線性哈希表中.和B樹類似,鍵和值可以是任意復雜的.另外,和B樹類似,多重記錄也是可選的.

            Queue
            隊列

            Data is stored in a queue as fixed-length records. Each record uses a logical record number as its key. This access method is designed for fast inserts at the tail of the queue, and it has a special operation that deletes and returns a record from the head of the queue.
            數據被保存在一個作為定長記錄集的隊列中.每個記錄使用一個邏輯記錄號作為鍵.這種訪問方式被用在需要在隊列尾巴快速插入數據的場合,它還有特殊的操作來返回和刪除頭部的數據.

            This access method is unusual in that it provides record level locking. This can provide beneficial performance improvements in applications requiring concurrent access to the queue.
            這種訪問方式與眾不同處在于他提供記錄級別的鎖.當程序需要并發的訪問隊列時,這一點可以提高性能.

            Recno
            Recno

            Data is stored in either fixed or variable-length records. Like Queue, Recno records use logical record numbers as keys.
            數據被保存在一個定長/變長記錄集中.類似Queueh,Recno使用邏輯記錄號作為鍵.

            Selecting Access Methods
            選擇訪問方式

            To select an access method, you should first consider what you want to use as a key for you database records. If you want to use arbitrary data (even strings), then you should use either BTree or Hash. If you want to use logical record numbers (essentially integers) then you should use Queue or Recno.
            選擇一種訪問方式你首先需要您的數據庫記錄集鍵的類型.如果你想使用任意類型的數據(甚至僅是字串),你就應該用B樹或哈希.如果你想使用邏輯記錄號(本質上說是整數),那么使用隊列或是Recon吧.

            Once you have made this decision, you must choose between either BTree or Hash, or Queue or Recno. This decision is described next.
            一旦你做出以上的決定,你就要在B樹,哈希,隊列,Recno中選取了.下面來對比描述一下.

            Choosing between BTree and Hash
            在B樹和哈希中選取

            For small working datasets that fit entirely in memory, there is no difference between BTree and Hash. Both will perform just as well as the other. In this situation, you might just as well use BTree, if for no other reason than the majority of DB applications use BTree.
            對于小到應該被完全加載到內存的工作數據集,B樹和哈希沒有什么區別.他們彼此的表現幾乎一樣優秀.這種情況下你或許應該選擇B樹,如果沒有特殊的原因,大半的DB應用使用B樹.

            Note that the main concern here is your working dataset, not your entire dataset. Many applications maintain large amounts of information but only need to access some small portion of that data with any frequency. So what you want to consider is the data that you will routinely use, not the sum total of all the data managed by your application.
            注意,這里主要關心的是你的工作數據集,不是你的整個數據集.許多應用維護著大量信息但是在任何情況下只需要訪問其中的一小部分.如此你就需要考慮你通常使用的數據,而不是你的應用程序使用的所有數據.

            However, as your working dataset grows to the point where you cannot fit it all into memory, then you need to take more care when choosing your access method. Specifically, choose:
            然而,當你的工作數據集增長到不能全部加載到內存的臨界點時,你就需要注意選擇訪問方式了,特別是,選擇:

                *    BTree if your keys have some locality of reference. That is, if they sort well and you can expect that a query for a given key will likely be followed by a query for one of its neighbors.
                *    B樹:如果你的鍵有位置上的關聯.也就是說,如果他們排序良好那么你可以預期一個給定鍵的查詢很可能在查詢它的一個鄰居之后.

                *    Hash if your dataset is extremely large. For any given access method, DB must maintain a certain amount of internal information. However, the amount of information that DB must maintain for BTree is much greater than for Hash. The result is that as your dataset grows, this internal information can dominate the cache to the point where there is relatively little space left for application data. As a result, BTree can be forced to perform disk I/O much more frequently than would Hash given the same amount of data.
                *    哈希:如果你的數據集非常巨大.所有的給出訪問方式,DB都要維護一個確定大小額外信息.然而,B樹比哈希所需要的額外信息多得多.結果就是當你的數據集增長時,額外信息可能裝滿了緩存相對的應用程序可用的空間就小了.影響就是,B樹不是不比哈希更頻繁的訪問相同數量的數據.

                Moreover, if your dataset becomes so large that DB will almost certainly have to perform disk I/O to satisfy a random request, then Hash will definitely out perform BTree because it has fewer internal records to search through than does BTree.
                更重要的是如果你的數據集龐大到DB幾乎肯定要執行磁盤I/O操作來滿足一個隨機的訪問,Hash毫無疑問的會勝出B樹因為它內部搜索的記錄更少.

            Choosing between Queue and Recno
            在隊列和Recno中選取

            Queue or Recno are used when the application wants to use logical record numbers for the primary database key. Logical record numbers are essentially integers that uniquely identify the database record. They can be either mutable or fixed, where a mutable record number is one that might change as database records are stored or deleted. Fixed logical record numbers never change regardless of what database operations are performed.
            隊列和Recno被用在當程序需要使用邏輯記錄號作為主記錄的鍵時.邏輯記錄號本質上是唯一標識記錄的整數。可以是變化的也可以是固定的,可變的記錄號可以在記錄數據數據保存或刪除時被改變.固定的邏輯記錄號無論數據庫如何運行也不會改變.

            When deciding between Queue and Recno, choose:
            當在隊列和Recno中取舍時:

                *      Queue if your application requires high degrees of concurrency. Queue provides record-level locking (as opposed to the page-level locking that the other access methods use), and this can result in significantly faster throughput for highly concurrent applications.
                *    隊列:如果你的應用需要高度并發.隊列提供了記錄級(record-level)的鎖(相對是另一種訪問方式的頁級(page-level)鎖),這在并發中性能有著顯著優勢.
               
                Note, however, that Queue provides support only for fixed length records. So if the size of the data that you want to store varies widely from record to record, you should probably choose an access method other than
                Queue.
                注意,然而,隊列只提供對定長記錄的支持.那么如果你的每條數據大小差異顯著,你可能需要隊列之外的一種訪問方式.
               
                *      Recno if you want mutable record numbers. Queue is only capable of providing fixed record numbers. Also, Recno provides support for databases whose permanent storage is a flat text file. This is useful for applications looking for fast, temporary storage while the data is being read or modified.
                *    Recno:如果你需要可變的記錄號.隊列只能提供固定的記錄號.同時,Recno支持將數據庫存儲在一個文本文件.這對需要快速,臨時存儲的正在讀取和修改數據的應用很有用.


            posted on 2007-05-11 16:49 張沈鵬 閱讀(906) 評論(0)  編輯 收藏 引用 所屬分類: C++
             
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