• <var id="qaci0"><label id="qaci0"></label></var>
      1. <var id="qaci0"></var>
        <table id="qaci0"><menu id="qaci0"></menu></table>
        1. <input id="qaci0"></input>

          <table id="qaci0"></table>
          <var id="qaci0"><label id="qaci0"></label></var>
          <sub id="qaci0"></sub>
        2. <var id="qaci0"><label id="qaci0"><ol id="qaci0"></ol></label></var>
          1. <table id="qaci0"><menu id="qaci0"></menu></table>

          2. <var id="qaci0"><output id="qaci0"></output></var>
            <var id="qaci0"></var>

             

            400-878-1895px51870017
            葩星1752902151 淘寶旺旺passiontechinc
            sales@www.xpj2355.com 13296027252
              加載中,請稍候...
            瀏覽歷史

             


            Database相關概念

            關鍵詞: Database相關概念


            簡介:數據管理系統提供最有效的管理方式用于保存數據在一個可靠的,有組織的形式。 This removes the burden of managing data from the application code and provides several key advantages that an application would 其他wise not have access to.Figure2, “保護, 組織, 和共享”depicts many of the risks that a database can help mitigate. Database features are c...
            品 牌
            產 地
            型 號 PXF2639
            折 扣
            咨詢專家:

            產品說明:

            數據管理系統提供最有效的管理方式用于保存數據在一個可靠的,有組織的形式。 This removes the burden of managing data from the application code and provides several key advantages that an application would 其他wise not have access to.

            Figure 2, “保護, 組織, 和共享” depicts many of the risks that a database can help mitigate. Database features are clustered near related risks, and many features are optional because an application is not always susceptible to every risk. The more database features an application utilizes, the better protected it is against nearby risks.

            Protect, Organize, and Share Data to Mitigate Risks

            Figure 2. Protect, Organize, and Share Data to Mitigate Risks

             

            Reliable storage is the primary motivation for using a database. Operations on a database are grouped into transactions, which will either succeed (commit) or fail (abort) as a single unit. Because transactions are persistent, data will not become lost or corrupted even after a power failure. After a crash, data is automatically recovered up to the last committed transaction.

            [Warning] Warning

            A database cannot protect against a corrupted file system or damaged media hardware. Regular backups are the only way to provide full 保護against data loss.

            A database can also provide powerful tools to help organize and access data. The structure of a database is specified in the database schema, which is used as the basis for navigating the data. Data is stored in tables, which contain a list of typed columns. Keys are defined on certain columns of the table to quickly locate rows based on the data stored in the key column. This fast data access through indexed key fields is an important advantage of a database managment system.

            Because data is stored in an organized format, it is possible to perform generic queries on the data. This allows existing software tools to be used with the data stored in the database, regardless of what application it was created with. Data can also be stored in a platform-independent format so that database files can be moved between different operating systems and processor architectures.

            To prevent data inconsistency, it is important to manage how multiple users modify the database at the same time. A database management system provides concurrency support to ensure that transactions commited by multiple users always appear to complete sequentially. This provides shared access to the database in a safe, efficient way.

            4.1. File and Memory Storage

            Where data is stored controls performance and durability.

            A file storage database is saved to disk continuously. Data is organized into large pages to take advantage of block device performance characteristics. The algorithms used to access data in a file storage database offer consistent overall performance, even as the size of the database grows to exceed the size of main memory.

            A memory storage database is stored primarily in memory. Direct pointers are used internally so that individual operations always complete in a predictable amount of time. For this reason, the size of a memory storage database is limited by the size of main memory.

            A hybrid database uses both file and memory storage to store both disk and memory tables in the same database. In this way, applications can balance requirements for durability and performance by creating some tables as memory tables. A hybrid database is created by setting the memory storage size when opening a file storage database.

            [Warning] Warning

            Avoid creating a memory storage that is larger than main memory. Virtual memory page faults will occur frequently in a large memory storage database. Instead, use a file storage and store some or all data in disk tables. The paging algorithms used for disk tables are specifically designed to minimize paging for table data.

            The storage model can be 改變d easily because it does not affect the way that tables are used. The only differences are in:

            • How the application 連接s to the database.

            • Whether tables are created on disk or in memory. For file storage, disk tables are created by default. For memory storage, memory tables are created by default.

            • Performance characteristics.

            • What data is lost when the database is closed or an unexpected failure occurs.

            The fundamental difference between disk and memory storage is the index algorithms used to sort and search for rows. Disk tables use B+ tree indexes, which have a shallow tree structure to minimize disk I/O as depicted in Figure 3, “B+ Tree Index Organization”. Reading a page from disk is an expensive operation and each node in the B+ tree is a page. The organization of a B+ tree ensures that even in a very large table, any key can be located with very few page read operations. The B+ tree contains a full copy of the data in each index column, so that full rows do not need to be loaded from disk when using an index.

            B+ Tree Index Organization

            Figure 3. B+ Tree Index Organization


            Memory tables use T-tree indexes, which have a deep binary tree structure as depicted in Figure 4, “T-Tree Index Organization”. Without disk I/O, traversing the 節點 of the tree is an inexpensive operation. Each node contains pointers to rows in the table rather than a full copy of the index columns.

            T-Tree Index Organization

            Figure 4. T-Tree Index Organization

            4.2. Table Type

            When a table is created, one of several table types can be selected. The table type affects the overhead and performance of storing and accessing data. ITTIA DB SQL™ supports the table types listed in Table 2, “Table Types”. The default table type depends on the storage model used by the database and some storage models do not support all types of tables. The default table type for disk storage is Key Heap, while the default table type for memory storage is Memory.

            Table Type Disk Storage Memory Storage
            Key Heap Table Default Not Supported
            Clustered Table Supported Not Supported
            Memory Table Supported Default

            Table 2. Table Types


            The table type controls how the data is represented inside the database. However, it does not affect how the data is accessed. From an application's perspective, a table is always a collection of rows and columns with zero or more indexes.

            A key heap table uses a hidden 4 byte key to identify each row. Indexes on a key heap table use a copy of this key to locate rows when fetching data, as shown inFigure 5, “Key Heap Table Organization”. One unique index can be designated as the primary key.

            Key Heap Table Organization

            Figure 5. Key Heap Table Organization


            [Tip] Tip

            The overhead of a row in a key heap table uses the following formula: 4 bytes + 2 bytes per column + 12 bytes per index + 2 bytes per index column. This is added to the size of each field that is not null in the table and in each index, which contain a copy of the indexed fields, to get the total size of the row.

            This calculation is valid for the current implementation and is subject to 改變 in future releases.

            A clustered table, shown in Figure 6, “Clustered Table Organization”, groups rows acording to the order specified by an index. This improves performance when accessing a batch of rows with the cluster index because related rows are often stored in the same page. However, 其他 indexes on the same table do not benefit from clustering. The clustering index is specified when the table is created and cannot be 改變d without dropping the table.

            Clustered Table Organization

            Figure 6. Clustered Table Organization


            A clustered table has the following benefits:

            1. Performance is improved for database operations that use the clustering index to fetch a single row or a set of adjacent rows. Because the table and index are combined, such operations avoid an extra index lookup.

            2. Storage overhead is generally reduced.

            A clustered table has a few drawbacks:

            1. The table must have a primary key and the application must provide a value for the primary key whenever a row is inserted. Sequence generators are available for this purpose.

            2. The primary key definition cannot be 改變d without dropping the table.

            The clustering index must meet the following conditions:

            1. The clustered index is the table's primary key.

            2. All index fields are NOT NULL.

            3. No variable-width index field exceeds 255 bytes.

            4. The total size of the index fields is at most (32 - v) bytes, where v is the number of.variable-width index fields.

            [Tip] Tip

            The overhead of a row in a clustered table uses the following formula: 2 bytes per column + 36 bytes per non-clustered index + 2 bytes per non-clustered index column.

            This calculation is valid for the current implementation and is subject to 改變 in future releases.

            The most efficient table type depends on the number of indexes created on the table and the size of the primary key. A clustered table has the most compact representation for a table with only one index or an integer primary key, while a key heap table is more compact when there are many indexes and a large primay key.

            參數資料:
            Database相關概念Database相關概念
            該文章系原廠商文章翻譯,不通之處請參考原文
            價格列表: Database相關概念Database相關概念
            葩星訂貨號 訂貨號 產品名稱 報價 品牌  
            相關產品: Database相關概念Database相關概念
              咨詢歷史:
            2021亚洲精品1卡2卡3卡,国色天香一卡二卡二卡四卡,国产卡一卡二卡三卡四卡视频,一卡二卡三卡四卡无卡免费播放在线观看日本,精品一卡二卡三卡四卡视频版 小黄鸭视频精品导航| 女人下面自熨视频免费播放| 漂亮人妇中出中文字幕在线| 亚洲AV中文无码字幕色本草| 高清无码中文字幕专区| 免费观看又色又爽又黄的视频| 老女老肥熟国产在线视频| 又大又粗又硬又长3p免费视频观看| 国产精品无码无片在线观看| 女人被做到高潮免费视频| 涨精装满肚子| 亚洲乱亚洲乱妇50P| 国产高清自产拍AV在线| 久久WWW免费人成_看片| JAPANBABES日本护士18| 男女啪啦啦超猛烈动态图| VIDEOS妓女CHINESE| 亚洲国产在线精品国自产拍五月| 成为人免费高清完整视频| 把腿扒开让我添| 漂亮的小峓子观看4| 在线看片A免费人成动漫| 爆出白浆超碰人人人人| 中文字幕无码免费久久99| 最好看的中文字幕2019| AV片在线观看| 欧美色欧美亚洲另类二区| JAPANESE老熟女| 亚洲欧美偷拍另类A∨| 日韩AV高清在线看片 | 国产亚洲欧洲日韩在线三区| 被公连续侵犯中文字幕| 在线看片韩国免费人成视频| 日本妈妈无m码在线| 最爽A片无码| 破外女出血视频全过程| 国色天香电视剧剧情介绍| 在线观看永久免费网站| 亚洲欧美综合区丁香五月| 天天躁日日躁狠狠躁欧美老妇| av片在线观看| 被吊起来用道具玩弄| 久久精品国产亚洲久久| 男人把女人桶爽叫床视频| CHINESE夫妇双飞XVIDEOS| 香蕉啪视频在线观看视频久| 小草社区2019| 黄网站色视频免费观看_首页| 抖音短视频网页版在线| 欧美人与动ZOZO欧美人Z0Z0| 无限资源免费韩国日本| 欧美综合婷婷欧美综合五月| 中文字幕欲求不满的熟妇| 国产AV在线播放剧情演绎| 床震吃奶摸下的激烈视频| 国产av一区二区三区| 免费H动漫无码网站| 乌克兰美女浓毛BBw| 一个本道久久综合久久88| 哔哩哔哩在线观看免费视频| 午夜性刺激在线观看| 日本一卡一卡2019| 女人张开腿给男人桶全免视| 好男人视频在线观看完整版视频| 美女张开腿露出尿口扒开来摸| 秋秋在线观看理论免费| 99久久无色码中文字幕| 成年女人免费视频播放体验区| 亚洲AV无码不卡在线播放| 老湿机69福利区在线观看| 男女真人后进式猛视频 | 乱子伦农村XXXX| 云南14学生真实初次破初视频在线| 老师破女学生处特级毛片| 国产成人午夜精品影院| 一卡二卡三卡四卡手机免费观在线| 少妇挑战黑人4P惨叫| 天堂种子WWW在线| 成·人免费午夜视频域名停靠| 白嫩人妻沦为他人胯下| 欧美三级片| 国内真实愉拍系列| 亚洲AV中文无码4区| 麻豆国内剧情AV在线素人搭讪| 日本一卡二卡三卡四卡网| 久久香蕉国产线看观看猫咪| 午夜dj在线观看免费观看1| 国模晨雨浓密毛大尺度| 120秒做受试看体验区| 凸厕所XXXX偷拍日本| 中年夫妇白天啪啪| 一本到中文无码AV在线观看| 无敌神马在线观看2021做啥能挣钱| 强行入侵女人A片| 亚洲制服丝袜有码中文欧美| 青青成线在人线免费啪| 欧美性受XXXX喷水| 交换娇妻高潮| 日本免费无遮挡吸乳视频| 穿短裙在办公室里被老板玩弄| 秋霞手机在线观看秋理论| 11孩岁女被A片| 人人澡人摸人人添学生AV| 男女夜色爽爽影院| 人与动人物A级毛片一| 特殊怀孕系统| 高跟丝袜AV专区| 无限在线观看播放视频| 女教师潮喷弄出白浆| 亚洲人成伊人成综合网站| 天天躁夜夜躁狠狠夜夜| 某机关少妇下班酒店在线播放| 校长办公室梦莹被灌| 亚洲AV无码精品色午夜| 欧美熟妇性XXXX| 中文字日本熟妇色在线观看| 国产XXXX视频在线观看软件| 人妻AV乱片AV出轨| 都市极品医神| 名女躁b久久天天躁| 天堂VA欧美VA亚洲VA好看VA| 做床爱在线观看无遮挡| 777米奇色狠狠8888影视| 玩丰满女领导对白露脸视频| 六年级女生和男生一起差差免费| 无卡在线观看免费| 成年片黄网站色大全网站| 高中生第一次处破女| 日本一卡二卡三卡四卡网站99| 老少交欧美另类| 丰满多水的寡妇| 一品道门在线观看| 强奷妇系列中文字幕| CHINA15末成年VIDEOS中文| 10后呦女交| 日韩亚洲欧美在线无码| 婷婷五月天| 大波大乳VIDEO| 无码中文字幕AⅤ精品影院| 亚洲中文字幕一二三四区免费| 欧美日韩无砖专区一中文字| 天天天狠天天碰天天爱| 女部长出差被部下中出中文字幕| 抖音下载视频免费下载| 色屁屁WWW影院免费观看| 日本在线视频网站WWW色| 天天影视色香欲综合网一寡妇| 插痛30分钟一卡二卡| 人妻少妇-嫩草影院| 高清VIDEOSGRATIS欧美69| 女性高爱潮视频30分钟| 色丁香婷婷综合开心网四月| 日本GAY视频JAPAN| IOS播放ONEDRIVE视频| A毛看片免费观看视频下载| 美女MM131爽爽爽作爱视频| 抖音在线视频有个绿点吗| 顶级少妇做爰视频| 色情综合网-色情在线播放| 国产成人亚洲精品| 另类专区AV无码| 宾馆双飞两少妇闺蜜| 又大又粗又爽又黄少妇毛片| 日韩AV片免费播放|