MongoDB基础教程：快速上手指南

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"mongodb入门" 本书是一本针对初学者的MongoDB入门指南，旨在帮助读者快速掌握MongoDB的基础用法。MongoDB是一款流行的开源、非关系型数据库系统，以灵活的数据模型、高性能和高可用性著称。通过阅读本书，你可以深入了解MongoDB的基本概念和操作方法。 MongoDB的主要特点包括： 1. **文档型数据库**：MongoDB存储数据以JSON（JavaScript Object Notation）格式的文档形式，这使得数据结构更为灵活，易于理解和操作。 2. **分布式设计**：MongoDB支持分布式部署，能够轻松扩展到多台服务器，实现水平扩展，以处理大规模数据。 3. **自动分片**：MongoDB提供自动分片功能，可将数据分散在多个物理节点上，提高读写性能。 4. **复制集**：通过复制集，MongoDB能够实现数据冗余和故障切换，确保高可用性。 5. **丰富的查询语言**：MongoDB的查询语言强大，支持丰富的查询表达式和聚合操作，同时支持地理位置索引和正则表达式。本书作者Karl Seguin是一位经验丰富的开发者，他在.NET和Ruby领域有深厚的专业背景，并且对开源项目有所贡献。他在MongoDB领域的贡献包括：参与C# MongoDB库NoRM的核心开发，编写交互式教程Mongly，以及MongoWebAdmin项目。他还利用MongoDB为休闲游戏开发者提供了免费服务mogade.com。本书遵循 Attribution-NonCommercial 3.0 Unported 许可证，允许读者自由复制、分发、修改或展示书籍内容，但需署名原作者并不得用于商业用途。完整许可证文本可在Creative Commons网站上查看。通过阅读本书，你将学习到如何安装MongoDB，创建数据库、集合和文档，进行数据插入、查询、更新和删除操作，以及如何利用复制集和分片来构建高可用和高性能的MongoDB集群。此外，书中可能还会涵盖索引创建、备份与恢复、性能调优等相关主题，帮助你全面掌握MongoDB的基本技能。作者Karl Seguin的博客和Twitter账号也是获取更多技术信息和更新的好去处。如果你对MongoDB感兴趣，这本书将是你理想的起点。

A small side note: Because this is a JavaScript shell, if you execute a method and omit the parentheses (), you’ll

see the method body rather than executing the method. I only mention it so that the first time you do it and get a

response that starts with function (...){ you won’t be surprised. For example, if you enter db.help (without the

parentheses), you’ll see the internal implementation of the help method.

First we’ll use the global use helper to switch databases, so go ahead and enter use learn. It doesn’t matter that the

database doesn’t really exist yet. The first collection that we create will also create the actual learn database. Now

that you are inside a database, you can start issuing database commands, like db.getCollectionNames(). If you do

so, you should get an empty array ([ ]). Since collections are schema-less, we don’t explicitly need to create them.

We can simply insert a document into a new collection. To do so, use the insert command, supplying it with the

document to insert:

db.unicorns.insert({name: 'Aurora',

gender: 'f', weight: 450})

The above line is executing insert against the unicorns collection, passing it a single parameter. Internally MongoDB

uses a binary serialized JSON format called BSON. Externally, this means that we use JSON a lot, as is the case with

our parameters. If we execute db.getCollectionNames() now, we’ll actually see two collections: unicorns and

system.indexes. The collection system.indexes is created once per database and contains the information on our

database’s indexes.

You can now use the find command against unicorns to return a list of documents:

db.unicorns.find()

Notice that, in addition to the data you specified, there’s an _id field. Every document must have a unique _id field.

You can either generate one yourself or let MongoDB generate a value for you which has the type ObjectId. Most of

the time you’ll probably want to let MongoDB generate it for you. By default, the _id field is indexed - which explains

why the system.indexes collection was created. You can look at system.indexes:

db.system.indexes.find()

What you’re seeing is the name of the index, the database and collection it was created against and the fields included

in the index.

Now, back to our discussion about schema-less collections. Insert a totally different document into unicorns, such as:

db.unicorns.insert({name: 'Leto',

gender: 'm',

home: 'Arrakeen',

worm: false})

And, again use find to list the documents. Once we know a bit more, we’ll discuss this interesting behavior of MongoDB,

but hopefully you are starting to understand why the more traditional terminology wasn’t a good fit.

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MongoDB基础教程：快速上手指南

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