--- title: MongoDB 建模示例 date: 2020-09-12 10:43:53 categories: - 数据库 - 文档数据库 - MongoDB tags: - 数据库 - 文档数据库 - MongoDB - 建模 permalink: /pages/88c7d3/ --- # MongoDB 建模示例 ## 关系型模型 ### 嵌入式文档一对一关系模型 #### 嵌入式文档一对一关系模型 - 嵌入式文档模式 ```json // patron document { _id: "joe", name: "Joe Bookreader" } // address document { patron_id: "joe", // reference to patron document street: "123 Fake Street", city: "Faketon", state: "MA", zip: "12345" } ``` 合并为： ```json { "_id": "joe", "name": "Joe Bookreader", "address": { "street": "123 Fake Street", "city": "Faketon", "state": "MA", "zip": "12345" } } ``` #### 嵌入式文档一对一关系模型 - 子集模式 假设，有一个用于描述电影信息的 collection 定义： ```json { "_id": 1, "title": "The Arrival of a Train", "year": 1896, "runtime": 1, "released": ISODate("01-25-1896"), "poster": "http://ia.media-imdb.com/images/M/MV5BMjEyNDk5MDYzOV5BMl5BanBnXkFtZTgwNjIxMTEwMzE@._V1_SX300.jpg", "plot": "A group of people are standing in a straight line along the platform of a railway station, waiting for a train, which is seen coming at some distance. When the train stops at the platform, ...", "fullplot": "A group of people are standing in a straight line along the platform of a railway station, waiting for a train, which is seen coming at some distance. When the train stops at the platform, the line dissolves. The doors of the railway-cars open, and people on the platform help passengers to get off.", "lastupdated": ISODate("2015-08-15T10:06:53"), "type": "movie", "directors": ["Auguste Lumière", "Louis Lumière"], "imdb": { "rating": 7.3, "votes": 5043, "id": 12 }, "countries": ["France"], "genres": ["Documentary", "Short"], "tomatoes": { "viewer": { "rating": 3.7, "numReviews": 59 }, "lastUpdated": ISODate("2020-01-09T00:02:53") } } ``` 在应用中，有的场景只需要显示电影的简单浏览信息，不需要显示类似 fullplot、poster 这样的详细信息。因为，我们可以考虑将原结构一份为二，并通过 id 字段关联起来。 用于展示摘要信息的 movie collection ```json // movie collection { "_id": 1, "title": "The Arrival of a Train", "year": 1896, "runtime": 1, "released": ISODate("1896-01-25"), "type": "movie", "directors": ["Auguste Lumière", "Louis Lumière"], "countries": ["France"], "genres": ["Documentary", "Short"] } ``` 用于展示细节信息的 movie_details collection ```json // movie_details collection { "_id": 156, "movie_id": 1, // reference to the movie collection "poster": "http://ia.media-imdb.com/images/M/MV5BMjEyNDk5MDYzOV5BMl5BanBnXkFtZTgwNjIxMTEwMzE@._V1_SX300.jpg", "plot": "A group of people are standing in a straight line along the platform of a railway station, waiting for a train, which is seen coming at some distance. When the train stops at the platform, ...", "fullplot": "A group of people are standing in a straight line along the platform of a railway station, waiting for a train, which is seen coming at some distance. When the train stops at the platform, the line dissolves. The doors of the railway-cars open, and people on the platform help passengers to get off.", "lastupdated": ISODate("2015-08-15T10:06:53"), "imdb": { "rating": 7.3, "votes": 5043, "id": 12 }, "tomatoes": { "viewer": { "rating": 3.7, "numReviews": 59 }, "lastUpdated": ISODate("2020-01-29T00:02:53") } } ``` ### 嵌入式文档一对多关系模型 #### 嵌入式文档一对多关系模型 - 嵌入式文档模式 ```json // patron document { _id: "joe", name: "Joe Bookreader" } // address documents { patron_id: "joe", // reference to patron document street: "123 Fake Street", city: "Faketon", state: "MA", zip: "12345" } { patron_id: "joe", street: "1 Some Other Street", city: "Boston", state: "MA", zip: "12345" } ``` 合并为： ```json { "_id": "joe", "name": "Joe Bookreader", "addresses": [ { "street": "123 Fake Street", "city": "Faketon", "state": "MA", "zip": "12345" }, { "street": "1 Some Other Street", "city": "Boston", "state": "MA", "zip": "12345" } ] } ``` #### 嵌入式文档一对多关系模型 - 子集模式 考虑一个电商网站用于表示商品的 collection： ```json { "_id": 1, "name": "Super Widget", "description": "This is the most useful item in your toolbox.", "price": { "value": NumberDecimal("119.99"), "currency": "USD" }, "reviews": [ { "review_id": 786, "review_author": "Kristina", "review_text": "This is indeed an amazing widget.", "published_date": ISODate("2019-02-18") }, { "review_id": 785, "review_author": "Trina", "review_text": "Nice product. Slow shipping.", "published_date": ISODate("2019-02-17") }, ...{ "review_id": 1, "review_author": "Hans", "review_text": "Meh, it's okay.", "published_date": ISODate("2017-12-06") } ] } ``` 评论按时间倒序排列。 当用户访问产品页面时，应用程序将加载十条最近的评论。可以将集合分为两个集合，而不是与产品一起存储所有评论： 产品集合存储有关每个产品的信息，包括产品的十个最新评论： ```json { "_id": 1, "name": "Super Widget", "description": "This is the most useful item in your toolbox.", "price": { "value": NumberDecimal("119.99"), "currency": "USD" }, "reviews": [ { "review_id": 786, "review_author": "Kristina", "review_text": "This is indeed an amazing widget.", "published_date": ISODate("2019-02-18") } ... { "review_id": 776, "review_author": "Pablo", "review_text": "Amazing!", "published_date": ISODate("2019-02-16") } ] } ``` review collection 存储所有的评论 ```json { "review_id": 786, "product_id": 1, "review_author": "Kristina", "review_text": "This is indeed an amazing widget.", "published_date": ISODate("2019-02-18") } { "review_id": 785, "product_id": 1, "review_author": "Trina", "review_text": "Nice product. Slow shipping.", "published_date": ISODate("2019-02-17") } ... { "review_id": 1, "product_id": 1, "review_author": "Hans", "review_text": "Meh, it's okay.", "published_date": ISODate("2017-12-06") } ``` ### 引用式文档一对多关系模型 考虑以下映射出版商和书籍关系的示例。 该示例说明了引用式文档的优点，以避免重复发布者信息。 ```json { title: "MongoDB: The Definitive Guide", author: [ "Kristina Chodorow", "Mike Dirolf" ], published_date: ISODate("2010-09-24"), pages: 216, language: "English", publisher: { name: "O'Reilly Media", founded: 1980, location: "CA" } } { title: "50 Tips and Tricks for MongoDB Developer", author: "Kristina Chodorow", published_date: ISODate("2011-05-06"), pages: 68, language: "English", publisher: { name: "O'Reilly Media", founded: 1980, location: "CA" } } ``` 为避免重复出版商数据，可以使用引用型文档，并将出版商信息与书本分开保存。 使用引用时，关系的增长决定了将引用存储在何处。 如果每个出版商的图书数量很少且增长有限，则有时将图书参考存储在出版商文档中可能会很有用。 否则，如果每个发布者的书籍数量不受限制，则此数据模型将导致可变的，不断增长的数组，如以下示例所示： ```json { name: "O'Reilly Media", founded: 1980, location: "CA", books: [123456789, 234567890, ...] } { _id: 123456789, title: "MongoDB: The Definitive Guide", author: [ "Kristina Chodorow", "Mike Dirolf" ], published_date: ISODate("2010-09-24"), pages: 216, language: "English" } { _id: 234567890, title: "50 Tips and Tricks for MongoDB Developer", author: "Kristina Chodorow", published_date: ISODate("2011-05-06"), pages: 68, language: "English" } ``` 为了避免可变的，增长的数组，请将发行者参考存储在书籍文档中： ```json { _id: "oreilly", name: "O'Reilly Media", founded: 1980, location: "CA" } { _id: 123456789, title: "MongoDB: The Definitive Guide", author: [ "Kristina Chodorow", "Mike Dirolf" ], published_date: ISODate("2010-09-24"), pages: 216, language: "English", publisher_id: "oreilly" } { _id: 234567890, title: "50 Tips and Tricks for MongoDB Developer", author: "Kristina Chodorow", published_date: ISODate("2011-05-06"), pages: 68, language: "English", publisher_id: "oreilly" } ``` ## 树形结构模型 ![img](https://raw.githubusercontent.com/dunwu/images/master/snap/20200911194846.svg) ### 具有父节点的树形结构模型 上图结构可以用父引用来表示： ```json db.categories.insertMany([ { "_id": "MongoDB", "parent": "Databases" }, { "_id": "dbm", "parent": "Databases" }, { "_id": "Databases", "parent": "Programming" }, { "_id": "Languages", "parent": "Programming" }, { "_id": "Programming", "parent": "Books" }, { "_id": "Books", "parent": null } ]) ``` - 检索节点的父节点： ``` db.categories.findOne( { _id: "MongoDB" } ).parent ``` - 可以在父字段上创建索引以启用父节点的快速搜索： ``` db.categories.createIndex( { parent: 1 } ) ``` - 可以通过父字段查询找到其直接子节点： ``` db.categories.find( { parent: "Databases" } ) ``` - 检索子树，可以参考： [`$graphLookup`](https://docs.mongodb.com/manual/reference/operator/aggregation/graphLookup/#pipe._S_graphLookup). ### 具有子节点的树形结构模型 ```json db.categories.insertMany([ { "_id": "MongoDB", "children": [] }, { "_id": "dbm", "children": [] }, { "_id": "Databases", "children": ["MongoDB", "dbm"] }, { "_id": "Languages", "children": [] }, { "_id": "Programming", "children": ["Databases", "Languages"] }, { "_id": "Books", "children": ["Programming"] } ]) ``` - 检索节点的 children： ``` db.categories.findOne( { _id: "Databases" } ).children ``` - 可以在 children 字段上创建索引以启用子节点的快速搜索： ``` db.categories.createIndex( { children: 1 } ) ``` - 可以在 children 字段中查询节点，以找到其父节点及其兄弟节点： ``` db.categories.find( { children: "MongoDB" } ) ``` ### 具有祖先的树形结构模型 ```json db.categories.insertMany([ { "_id": "MongoDB", "ancestors": ["Books", "Programming", "Databases"], "parent": "Databases" }, { "_id": "dbm", "ancestors": ["Books", "Programming", "Databases"], "parent": "Databases" }, { "_id": "Databases", "ancestors": ["Books", "Programming"], "parent": "Programming" }, { "_id": "Languages", "ancestors": ["Books", "Programming"], "parent": "Programming" }, { "_id": "Programming", "ancestors": ["Books"], "parent": "Books" }, { "_id": "Books", "ancestors": [], "parent": null } ]) ``` - 检索节点的祖先或路径的查询是快速而直接的： ```json db.categories.findOne({ "_id": "MongoDB" }).ancestors ``` - 可以在 ancestors 字段上创建索引，以启用祖先节点的快速搜索： ```json db.categories.createIndex({ "ancestors": 1 }) ``` - 可以通过 ancestors 字段查询查找其所有后代： ```json db.categories.find({ "ancestors": "Programming" }) ``` ### 具有实体化路径的树形结构模型 ```json db.categories.insertMany([ { "_id": "Books", "path": null }, { "_id": "Programming", "path": ",Books," }, { "_id": "Databases", "path": ",Books,Programming," }, { "_id": "Languages", "path": ",Books,Programming," }, { "_id": "MongoDB", "path": ",Books,Programming,Databases," }, { "_id": "dbm", "path": ",Books,Programming,Databases," } ]) ``` - 可以查询以检索整个树，并按字段路径排序： ``` db.categories.find().sort( { path: 1 } ) ``` - 可以在 path 字段上使用正则表达式来查找 Programming 的后代 ``` db.categories.find( { path: /,Programming,/ } ) ``` - 可以检索 Books 的后代，其中 Books 也位于层次结构的最高级别： ``` db.categories.find( { path: /^,Books,/ } ) ``` - 要在 path 字段上创建索引，请使用以下调用： ``` db.categories.createIndex( { path: 1 } ) ``` ### 具有嵌套集的树形结构模型 ![img](https://raw.githubusercontent.com/dunwu/images/master/snap/20200911204252.svg) ```javascript db.categories.insertMany([ { _id: 'Books', parent: 0, left: 1, right: 12 }, { _id: 'Programming', parent: 'Books', left: 2, right: 11 }, { _id: 'Languages', parent: 'Programming', left: 3, right: 4 }, { _id: 'Databases', parent: 'Programming', left: 5, right: 10 }, { _id: 'MongoDB', parent: 'Databases', left: 6, right: 7 }, { _id: 'dbm', parent: 'Databases', left: 8, right: 9 } ]) ``` 可以查询以检索节点的后代： ```javascript var databaseCategory = db.categories.findOne({ _id: 'Databases' }) db.categories.find({ left: { $gt: databaseCategory.left }, right: { $lt: databaseCategory.right } }) ``` ## 设计模式 ### 大文档，很多列，很多索引 解决方案是：列转行 ![img](https://raw.githubusercontent.com/dunwu/images/master/snap/20200919225901.png) ### 管理文档不同版本 MongoDB 文档格式非常灵活，势必会带来版本维护上的难度。 解决方案是：可以增加一个版本号字段 - 快速过滤掉不需要升级的文档 - 升级时，对不同版本的文档做不同处理 ### 统计网页点击量 统计数据精确性要求并不是十分重要。 解决方案：用近似计算 每隔 10 次写一次： ```json { "$inc": { "views": 1 } } ``` ### 精确统计 解决方案：使用预聚合 ## 参考资料 - [Data Model Examples and Patterns](https://docs.mongodb.com/manual/applications/data-models/)