Name: 亞馬遜網絡服務教程--在 AWS 中使用 DynamoDB (Amazon Web Services Tutorial - Using DynamoDB with AWS)
Uploaded: 2025-08-03T18:38:31.000Z
Duration: 8 min 10 s

程度副詞

Let's imagine you have just built a promising app that the world has never seen before.

讓我們想象一下，您剛剛開發了一款前景廣闊的應用程序，這是世界上從未見過的。

New users are coming in, but can your database scale to handle all the incoming requests?

新用戶不斷湧入，但您的數據庫是否能夠處理所有的請求？

基礎被動語態

Amazon DynamoDB is built to handle internet-scale applications as traditional databases cannot handle millions of requests per second during Black Fridays or Cyber Mondays kind of scenarios.

Amazon DynamoDB 是專為處理互聯網規模的應用程序而構建的，因為傳統數據庫無法在黑色星期五或網絡星期一之類的情況下處理每秒數百萬次的請求。

You can store hundreds of terabytes of data in DynamoDB and can expect great performance.

您可以在 DynamoDB 中存儲數百 TB 的數據，並期待獲得出色的性能。

So let's discuss key features of DynamoDB.

下面我們就來討論一下 DynamoDB 的主要功能。

DynamoDB is a fully managed, multi-region, multi-master and highly available database.

DynamoDB 是一個全面管理、多區域、多主控和高可用的數據庫。

And all your data is replicated across three availability zones and you don't have to worry about patching and upgrading.

你的所有數據都會在三個可用區之間複製，你不必擔心打補丁和升級的問題。

That means it's not a relational database.

Amazon DynamoDB is primarily designed to manage semi-structured data.

Amazon DynamoDB 主要用於管理半結構化數據。

DynamoDB tables do not have a fixed schema.

So each data item can have a different number of attributes, which is very different to a relational database, which does require the attributes in a table to be consistent.

是以，每個數據項可以有不同數量的屬性，這與關係數據庫截然不同，關係數據庫要求表中的屬性保持一致。

It will scale through massive workload and will be distributed and that's what makes it scale.

它將通過大量的工作負載進行擴展，並且是分佈式的，這就是它的擴展性所在。

You can issue on it millions of requests per second.

The really good thing about DynamoDB is that you get fast and consistent performance.

DynamoDB 的真正優勢在於其快速而穩定的性能。

So that means every retrieval will be low latency, usually in the single-digit millisecond.

這意味著每次檢索的延遲時間都很短，通常只有個位數毫秒。

It will be integrated with IAM for security and authorization, which is the best practice in AWS to manage security anyway.

它將與用於安全和授權的 IAM 集成，這是 AWS 管理安全的最佳做法。

On top of it, we can enable event-driven programming for your DynamoDB streams, where we can reply to events that happen to our table and see in real time that what we want to do about it.

除此之外，我們還可以為 DynamoDB 數據流啟用事件驅動編程，這樣我們就可以回覆表中發生的事件，並實時查看我們要做的事情。

It's a low cost and has auto-scaling capabilities, which makes it the perfect serverless database.

它成本低，具有自動擴展功能，是完美的無服務器數據庫。

Now let's log into AWS console and see how DynamoDB dashboard looks like.

現在，讓我們登錄 AWS 控制檯，看看 DynamoDB 控制面板的樣子。

So basically DynamoDB is a database, but you don't need to create databases as they are already there for you.

是以，DynamoDB 基本上就是一個數據庫，但你不需要創建數據庫，因為它們已經為你準備好了。

是以，讓我們在這裡創建一個新表。

Each table will have a primary key and you can also define a composite key by including a sort key.

每個表都有一個主鍵，還可以通過包含排序鍵來定義複合鍵。

So let's define player ID as the primary key and country as a sort key.

是以，我們將球員 ID 定義為主鍵，將國家定義為排序鍵。

Each table can have infinite number of rows and each row may have different number of attributes, which we don't need to define at the table creation, which is in contrast to any RDBMS.

每個表可以有無限多的行，每一行可以有不同數量的屬性，我們不需要在創建表時定義這些屬性，這與任何 RDBMS 都不同。

The maximum size of a row can be up to 400 kilobytes.

行的最大大小可達 400 千字節。

However, you can have any number of rows of this magnitude.

不過，您可以擁有任意數量的此類行。

So this is really important decision while designing for your storage that what kind of data it holds.

是以，在設計存儲設備時，決定存儲什麼樣的數據非常重要。

As DynamoDB has a limitation of 400 KB while S3 can store objects up to five terabytes in size.

由於 DynamoDB 的限制為 400 KB，而 S3 可存儲的對象最大可達 5 TB。

So here either we can simply create table with default settings or can provide customized configurations.

是以，在這裡我們可以簡單地創建默認設置的表格，也可以提供自定義配置。

And key thing to define here is the throughput you need in terms of read and write capacity units.

這裡需要定義的關鍵是你所需要的讀寫能力組織、部門的吞吐量。

Read capacity unit or RCU is the number of elements you will read per second while write capacity unit or WCU is number of elements you will write per second.

讀取容量組織、部門或 RCU 是指每秒讀取的元素數量，而寫入容量組織、部門或 WCU 是指每秒寫入的元素數量。

And you have a capacity calculator here where you can calculate the required read and write capacity.

這裡有一個容量計算器，可以計算所需的讀寫容量。

So if your item size is 1 KB and you want to read and write one item per second, you will need one one read and write capacity units.

是以，如果項目大小為 1 KB，而您希望每秒讀寫一個項目，則需要一個讀寫容量組織、部門。

However, if your item size is let's say 300 KB and you want to read and write one one item per second, then you will need 38 read capacity units and 300 write capacity units.

但是，如果您的項目大小是 300 KB，而您希望每秒讀寫一個項目，那麼您將需要 38 個讀取容量組織、部門和 300 個寫入容量組織、部門。

And worth noticing here that it will also increase the cost.

值得注意的是，這也會增加成本。

You can also turn on scaling and impose encryption on your DynamoDB data.

您還可以打開擴展功能，並對 DynamoDB 數據進行加密。

So let's go ahead and create this table with default settings.

是以，讓我們使用默認設置創建這個表格。

And now let's try to add some data in this table.

現在，讓我們嘗試在表格中添加一些數據。

So as we can see here, this table is being created.

是以，我們可以看到，這個表格正在創建中。

讓我們嘗試刷新一下這個表格。

是以，我們可以看到它是可用的。

And this is where we can create records into this table.

在這裡，我們可以在這個表中創建記錄。

So let's say player ID is P01 and it represents country USA.

假設玩家 ID 是 P01，代表的國家是美國。

Let's try to add another row here with player ID P02 representing country as India.

讓我們嘗試在這裡添加另一行，球員 ID P02 代表國家為印度。

And here we also want to add another attribute as city that this player is from Delhi city in India.

在這裡，我們還想添加另一個屬性，即該球員來自印度德里市。

So here we can see that we have two rows and both the rows has different number of attributes.

是以，我們可以看到這裡有兩行，兩行的屬性數量各不相同。

So you can have any number of rows in your DynamoDB table with varied number of attributes.

是以，您可以在 DynamoDB 表中擁有任意數量的行和不同數量的屬性。

Now you might be thinking that how DynamoDB relate in data engineering.

現在你可能在想，DynamoDB 與數據工程有什麼關係。

Well, there are some very common use cases that includes mobile apps, gaming, digital ad service, live voting, audience interaction for live events, sensor network, log ingestion, access control for web-based content, metadata storage for Amazon S3 objects, e-com, web session management, etc.

有一些非常常見的使用案例，包括移動應用程序、遊戲、數字廣告服務、現場投票、現場活動的觀眾互動、傳感器網絡、日誌攝取、基於網絡內容的訪問控制、亞馬遜 S3 對象的元數據存儲、電子商務、網絡會話管理等。

In terms of anti-patterns where DynamoDB is not a good choice for, for example, RDS like fixed schema, complex joins or complex transactions or large size objects.

就反模式而言，DynamoDB 並不適合 RDS，例如固定模式、複雜連接、複雜事務或大型對象。

And in general, if you have large data that has low IO rate, so few write or very few read, then S3 is going to be a much better storage option for you.

一般來說，如果你的大數據 IO 率很低，只有很少的寫入或讀取，那麼 S3 將是你更好的存儲選擇。

是以，使用案例是多種多樣的。

But basically, that means that any time if you have some data that need to be very hot, small in size and needs to be ingested at scale within a database, then DynamoDB is going to be a great fit for that.

但基本上，這意味著任何時候，如果你有一些數據需要非常熱、體積小，並且需要在數據庫中大規模攝取，那麼 DynamoDB 將非常適合。