By Trisha Gee, Java Engineer and Advocate at MongoDB Java is one of the most popular programming languages in the MongoDB Community. For new users, it’s important to provide an overview of how to work with the MongoDB Java driver and how
By Trisha Gee, Java Engineer and Advocate at MongoDB
Java is one of the most popular programming languages in the MongoDB Community. For new users, it’s important to provide an overview of how to work with the MongoDB Java driver and how to use MongoDB as a Java developer.
In this post, which is aimed at Java/JVM developers who are new to MongoDB, we’re going to give you a guide on how to get started, including:
- Installation
- Setting up your dependencies
- Connecting
- What are Collections and Documents?
- The basics of writing to and reading from the database
- An overview of some of the JVM libraries
Installation
The installation instructions for MongoDB are extensively documented, so I’m not going to repeat any of that here. If you want to follow along with this “getting started” guide, you’ll want to download the appropriate version of MongoDB and unzip/install it. At the time of writing, the latest version of MongoDB is 2.6.3, which is the version I’ll be using.
A note about security
In a real production environment, of course you’re going to want to consider authentication. This is something that MongoDB takes seriously and there’s a whole section of documentation on security. But for the purpose of this demonstration, I’m going to assume you’ve either got that working or you’re running in “trusted mode” (i.e. that you’re in a development environment that isn’t open to the public).
Take a look around
Once you’ve got MongoDB installed and started (a process that should only take a few minutes), you can connect to the MongoDB shell. Most of the MongoDB technical documentation is written for the shell, so it’s always useful to know how to access it, and how use it to troubleshoot problems or prototype solutions.
When you’ve connected, you should see something like
MongoDB shell version: 2.6.3 connecting to: test > _
Since you’re in the console, let’s take it for a spin. Firstly we’ll have a look at all the databases that are there right now:
> show dbs
Assuming this is a clean installation, there shouldn’t be much to see:
> show dbs admin (empty) local 0.078GB >
That’s great, but as you can see there’s loads of documentation on how to play with MongoDB from the shell. The shell is a really great environment for trying out queries and looking at things from the point-of-view of the server. However, I promised you Java, so we’re going to step away from the shell and get on with connecting via Java.
Getting started with Java
First, you’re going to want to set up your project/IDE to use the MongoDB Java Driver. These days IDEs tend to pick up the correct dependencies through your Gradle or Maven configuration, so I’m just going to cover configuring these.
At the time of writing, the latest version of the Java driver is 2.12.3 - this is designed to work with the MongoDB 2.6 series.
Gradle
You’ll need to add the following to your dependencies in build.gradle:
<code>compile 'org.mongodb:mongo-java-driver:2.12.3' </code>
Maven
For maven, you’ll want:
<code><dependencies> <dependency> <groupid>org.mongodb</groupid> <artifactid>mongo-java-driver</artifactid> <version>2.12.3</version> </dependency> </dependencies> </code>
Alternatively, if you’re really old-school and like maintaining your dependencies the hard way, you can always download the JAR file.
If you don’t already have a project that you want to try with MongoDB, I’ve created a series of unit tests on github which you can use to get a feel for working with MongoDB and Java.
Connecting via Java
Assuming you’ve resolved your dependencies and you’ve set up your project, you’re ready to connect to MongoDB from your Java application.
Since MongoDB is a document database, you might not be surprised to learn that you don’t connect to it via traditional SQL/relational DB methods like JDBC. But it’s simple all the same:
Where I’ve put mongodb://localhost:27017
, you’ll want to put the address of where you’ve installed MongoDB. There’s more detailed information on how to create the correct URI, including how to connect to a Replica Set, in the MongoClientURI documentation.
If you’re connecting to a local instance on the default port, you can simply use:
Note that this does throw a checked Exception, UnknownHostException
. You’ll either have to catch this or declare it, depending upon what your policy is for exception handling.
The MongoClient
is your route in to MongoDB, from this you’ll get your database and collections to work with (more on this later). Your instance of MongoClient
(e.g. mongoClient
above) will ordinarily be a singleton in your application. However, if you need to connect via different credentials (different user names and passwords) you’ll want a MongoClient
per set of credentials.
It is important to limit the number of MongoClient
instances in your application, hence why we suggest a singleton - the MongoClient
is effectively the connection pool, so for every new MongoClient
, you are opening a new pool. Using a single MongoClient
(and optionally configuring its settings) will allow the driver to correctly manage your connections to the server. This MongoClient
singleton is safe to be used by multiple threads.
One final thing you need to be aware of: you want your application to shut down the connections to MongoDB when it finishes running. Always make sure your application or web server calls MongoClient.close()
when it shuts down.
Try out connecting to MongoDB by getting the test in Exercise1ConnectingTest to pass.
Where are my tables?
MongoDB doesn’t have tables, rows, columns, joins etc. There are some new concepts to learn when you’re using it, but nothing too challenging.
While you still have the concept of a database, the documents (which we’ll cover in more detail later) are stored in collections, rather than your database being made up of tables of data. But it can be helpful to think of documents like rows and collections like tables in a traditional database. And collections can have indexes like you’d expect.
Selecting Databases and Collections
You’re going to want to define which databases and collections you’re using in your Java application. If you remember, a few sections ago we used the MongoDB shell to show the databases in your MongoDB instance, and you had an admin
and a local
.
Creating and getting a database or collection is extremely easy in MongoDB:
You can replace "TheDatabaseName"
with whatever the name of your database is. If the database doesn’t already exist, it will be created automatically the first time you insert anything into it, so there’s no need for null checks or exception handling on the off-chance the database doesn’t exist.
Getting the collection you want from the database is simple too:
Again, replacing "TheCollectionName"
with whatever your collection is called.
If you’re playing along with the test code, you now know enough to get the tests
in Exercise2MongoClientTest to pass.
An introduction to documents
Something that is, hopefully, becoming clear to you as you work through the examples in this blog, is that MongoDB is different from the traditional relational databases you’ve used. As I’ve mentioned, there are collections, rather than tables, and documents, rather than rows and columns.
Documents are much more flexible than a traditional row, as you have a dynamic schema rather than an enforced one. You can evolve the document over time without incurring the cost of schema migrations and tedious update scripts. But I’m getting ahead of myself.
Although documents don’t look like the tables, columns and rows you’re used to, they should look familiar if you’ve done anything even remotely JSON-like. Here’s an example:
<code>person = { _id: "jo", name: "Jo Bloggs", age: 34, address: { street: "123 Fake St", city: "Faketon", state: "MA", zip: “12345” } books: [ 27464, 747854, ...] } </code>
There are a few interesting things to note:
- Like JSON, documents are structures of name/value pairs, and the values can be one of a number of primitive types, including Strings and various number types.
- It also supports nested documents - in the example above,
address
is a subdocument inside theperson
document. Unlike a relational database, where you might store this in a separate table and provide a reference to it, in MongoDB if that data benefits from always being associated with its parent, you can embed it in its parent. - You can even store an array of values. The books field in the example above is an array of integers that might represent, for example, IDs of books the person has bought or borrowed.
You can find out more detailed information about Documents in the documentation.
Creating a document and saving it to the database
In Java, if you wanted to create a document like the one above, you’d do something like:
At this point, it’s really easy to save it into your database:
Note that the first three lines are set-up, and you don’t need to re-initialize those every time.
Now if we look inside MongoDB, we can see that the database has been created:
> show dbs
Examples 0.078GB
admin (empty)
local 0.078GB
> _
…and we can see the collection has been created as well:
<code>> use Examples switched to db Examples > show collections people system.indexes > _ </code>
…finally, we can see the our person, “Jo”, was inserted:
<code>> db.people.findOne() { "_id" : "jo", "name" : "Jo Bloggs", "age": 34, "address" : { "street" : "123 Fake St", "city" : "Faketon", "state" : "MA", "zip" : "12345" }, "books" : [ 27464, 747854 ] } > _ </code>
As a Java developer, you can see the similarities between the Document that’s stored in MongoDB, and your domain object. In your code, that person would probably be a Person class, with simple primitive fields, an array field, and an Address field.
So rather than building your DBObject
manually like the above example, you’re more likely to be converting your domain object into a DBObject. It’s best not to have the MongoDB-specific DBObject class in your domain objects, so you might want to create a PersonAdaptor that converts your Person domain object to a DBObject:
As before, once you have the DBObject, you can save this into MongoDB:
Now you’ve got all the basics to get the tests in Exercise3InsertTest to pass.
Getting documents back out again
Now you’ve saved a Person to the database, and we’ve seen it in the database using the shell, you’re going to want to get it back out into your Java application. In this post, we’re going to cover the very basics of retrieving a document - in a later post we’ll cover more complex querying.
You’ll have guessed by the fact that MongoDB is a document database that we’re not going to be using SQL to query. Instead, we query by example, building up a document that looks like the document we’re looking for. So if we wanted to look for the person we saved into the database, “Jo Bloggs”, we remember that the _id
field had the value of “jo”, and we create a document that matches this shape:
As you can see, the find
method returns a cursor for the results. Since _id
needs to be unique, we know that if we look for a document with this ID, we will find only one document, and it will be the one we want:
Earlier we saw that documents are simply made up of name/value pairs, where the value can be anything from a simple String or primitive, to more complex types like arrays or subdocuments. Therefore in Java, we can more or less treat DBObject as a Map<string object></string>
. So if we wanted to look at the fields of the document we got back from the database, we can get them with:
Note that you’ll need to cast the value to a String
, as the compiler only knows that it’s an Object
.
If you’re still playing along with the example code, you’re now ready to take on all the tests in Exercise4RetrieveTest
Overview of JVM Libraries
So far I’ve shown you the basics of the official Java Driver, but you’ll notice that it’s quite low-level - you have to do a lot of taking things out of your domain objects and poking them into MongoDB-shaped DBObjects, and vice-versa. If this is the level of control you want, then the Java driver makes this easy for you. But if it seems like this is extra work that you shouldn’t have to do, there are plenty of other options for you.
The tools I’m about to describe all use the MongoDB Java Driver at their core to interact with MongoDB. They provide a high-level abstraction for converting your domain objects into MongoDB documents, whilst also giving you a way to get to the underlying driver as well in case you need to use it at a lower level.
Morphia
Morphia is a really lightweight ODM (Object Document Mapper), so it’s similar to ORMs like Hibernate. Documents can be in a fairly similar shape to your Java domain objects, so this mapping can be automatic, but Morphia allows you point the mapper in the right direction.
Morphia is open source, and has contributors from MongoDB. Sample code and documentation can be found here.
Spring Data
Another frequently used ODM is Spring Data. This supports traditional relational and non-relational databases, including MongoDB. If you’re already using Spring in your application, this should be a familiar way to work.
As always with Spring projects, there’s a lot of really great documentation, including a Getting Started guide with example code.
MongoJack
If you’re working with web services or something else that supports JSON, and you’re using Jackson to work with this data, it probably seems like a waste to be turning it from this form into a Java object and then into a MongoDB DBObject. But MongoJack might make your job easier, as it’s designed to map JSON objects directly into MongoDB. Take a look at the example code and documentation.
Jongo
This is another Jackson-based ODM, but provides an interesting extra in the form of supporting queries the way you’d write them in the shell. Documentation and example code is available on the website.
Grails MongoDB GORM
The Grails web application framework also supports its own Object-Relational Mapping (GORM), including support for MongoDB. More documentation for this plugin can be found here.
Casbah
This isn’t an ODM like the other tools mentioned, but the officially supported Scala driver for MongoDB. Like the previous libraries, it uses the MongoDB Java Driver under the covers, but it provides a Scala API for application developers to work with. If you like working with Scala but are searching for an async solution, consider ReactiveMongo, a community-supported driver that provides async and non-blocking operations.
Other libraries and tools
This is far from an extensive list, and I apologise if I’ve left a favourite out. But we’ve compiled a list of many more libraries for the JVM, which includes community projects and officially supported drivers.
Conclusion
We’ve covered the basics of using MongoDB from Java - we’ve touched on what MongoDB is, and you can find out a lot more detailed information about it from the manual; we’ve installed it somewhere that lets us play with it; we’ve talked a bit about collections and documents, and what these look like in Java; and we’ve started inserting things into MongoDB and getting them back out again.
If you haven’t already started playing with the test code, you can find it in this github repository. And if you get desperate and look hard enough, you’ll even find the answers there too.
Finally, there are more examples of using the Java Driver in the Quick Tour, and there is example code in github, including examples for authentication.
If you want to learn more, try our 7-week online course, "Intro to MongoDB and Java".
Try it out, and hopefully you’ll see how easy it is to use MongoDB from Java.
Read Part II
原文地址:Getting Started with MongoDB and Java: Part I, 感谢原作者分享。

Innodbbufferpoolは、データをキャッシュしてページをインデックス作成することにより、ディスクI/Oを削減し、データベースのパフォーマンスを改善します。その作業原則には次のものが含まれます。1。データ読み取り:Bufferpoolのデータを読む。 2。データの書き込み:データを変更した後、bufferpoolに書き込み、定期的にディスクに更新します。 3.キャッシュ管理:LRUアルゴリズムを使用して、キャッシュページを管理します。 4.読みメカニズム:隣接するデータページを事前にロードします。 BufferPoolのサイジングと複数のインスタンスを使用することにより、データベースのパフォーマンスを最適化できます。

他のプログラミング言語と比較して、MySQLは主にデータの保存と管理に使用されますが、Python、Java、Cなどの他の言語は論理処理とアプリケーション開発に使用されます。 MySQLは、データ管理のニーズに適した高性能、スケーラビリティ、およびクロスプラットフォームサポートで知られていますが、他の言語は、データ分析、エンタープライズアプリケーション、システムプログラミングなどのそれぞれの分野で利点があります。

MySQLは、データストレージ、管理、分析に適した強力なオープンソースデータベース管理システムであるため、学習する価値があります。 1)MySQLは、SQLを使用してデータを操作するリレーショナルデータベースであり、構造化されたデータ管理に適しています。 2)SQL言語はMySQLと対話するための鍵であり、CRUD操作をサポートします。 3)MySQLの作業原則には、クライアント/サーバーアーキテクチャ、ストレージエンジン、クエリオプティマイザーが含まれます。 4)基本的な使用には、データベースとテーブルの作成が含まれ、高度な使用にはJoinを使用してテーブルの参加が含まれます。 5)一般的なエラーには、構文エラーと許可の問題が含まれ、デバッグスキルには、構文のチェックと説明コマンドの使用が含まれます。 6)パフォーマンスの最適化には、インデックスの使用、SQLステートメントの最適化、およびデータベースの定期的なメンテナンスが含まれます。

MySQLは、初心者がデータベーススキルを学ぶのに適しています。 1.MySQLサーバーとクライアントツールをインストールします。 2。selectなどの基本的なSQLクエリを理解します。 3。マスターデータ操作:テーブルを作成し、データを挿入、更新、削除します。 4.高度なスキルを学ぶ:サブクエリとウィンドウの関数。 5。デバッグと最適化:構文を確認し、インデックスを使用し、選択*を避け、制限を使用します。

MySQLは、テーブル構造とSQLクエリを介して構造化されたデータを効率的に管理し、外部キーを介してテーブル間関係を実装します。 1.テーブルを作成するときにデータ形式と入力を定義します。 2。外部キーを使用して、テーブル間の関係を確立します。 3。インデックス作成とクエリの最適化により、パフォーマンスを改善します。 4.データベースを定期的にバックアップおよび監視して、データのセキュリティとパフォーマンスの最適化を確保します。

MySQLは、Web開発で広く使用されているオープンソースリレーショナルデータベース管理システムです。その重要な機能には、次のものが含まれます。1。さまざまなシナリオに適したInnodbやMyisamなどの複数のストレージエンジンをサポートします。 2。ロードバランスとデータバックアップを容易にするために、マスタースレーブレプリケーション機能を提供します。 3.クエリの最適化とインデックスの使用により、クエリ効率を改善します。

SQLは、MySQLデータベースと対話して、データの追加、削除、変更、検査、データベース設計を実現するために使用されます。 1)SQLは、ステートメントの選択、挿入、更新、削除を介してデータ操作を実行します。 2)データベースの設計と管理に作成、変更、ドロップステートメントを使用します。 3)複雑なクエリとデータ分析は、ビジネス上の意思決定効率を改善するためにSQLを通じて実装されます。

MySQLの基本操作には、データベース、テーブルの作成、およびSQLを使用してデータのCRUD操作を実行することが含まれます。 1.データベースの作成:createdatabasemy_first_db; 2。テーブルの作成:createTableBooks(idintauto_incrementprimarykey、titlevarchary(100)notnull、authorvarchar(100)notnull、published_yearint); 3.データの挿入:InsertIntoBooks(タイトル、著者、公開_year)VA


ホットAIツール

Undresser.AI Undress
リアルなヌード写真を作成する AI 搭載アプリ

AI Clothes Remover
写真から衣服を削除するオンライン AI ツール。

Undress AI Tool
脱衣画像を無料で

Clothoff.io
AI衣類リムーバー

AI Hentai Generator
AIヘンタイを無料で生成します。

人気の記事

ホットツール

メモ帳++7.3.1
使いやすく無料のコードエディター

SecLists
SecLists は、セキュリティ テスターの究極の相棒です。これは、セキュリティ評価中に頻繁に使用されるさまざまな種類のリストを 1 か所にまとめたものです。 SecLists は、セキュリティ テスターが必要とする可能性のあるすべてのリストを便利に提供することで、セキュリティ テストをより効率的かつ生産的にするのに役立ちます。リストの種類には、ユーザー名、パスワード、URL、ファジング ペイロード、機密データ パターン、Web シェルなどが含まれます。テスターはこのリポジトリを新しいテスト マシンにプルするだけで、必要なあらゆる種類のリストにアクセスできるようになります。

PhpStorm Mac バージョン
最新(2018.2.1)のプロフェッショナル向けPHP統合開発ツール

AtomエディタMac版ダウンロード
最も人気のあるオープンソースエディター

ZendStudio 13.5.1 Mac
強力な PHP 統合開発環境
