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Serverless AWS Lambda Development · 课时

与 DynamoDB 集成

将 Lambda 函数连接到 Amazon DynamoDB——一种完全托管的 NoSQL 数据库，为无服务器应用提供高性能、可扩展的数据存储与读取能力

与 DynamoDB 集成 是 CoddyKit 上的免费 Serverless AWS Lambda Development 课时。 这是第 1 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Serverless AWS Lambda Development 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Serverless AWS Lambda Development 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

Lambda Meets DynamoDB

Welcome! In this lesson, we'll connect the power of serverless AWS Lambda with Amazon DynamoDB, a super-fast and flexible NoSQL database.

This combination is perfect for building scalable, high-performance applications without managing servers or database infrastructure.

DynamoDB: NoSQL in a Nutshell

Amazon DynamoDB is a fully managed, serverless NoSQL database. Unlike traditional SQL databases, it uses a key-value and document data model.

  • Tables: Similar to SQL tables, but hold items.
  • Items: Like rows in SQL, but can have different attributes.
  • Attributes: Like columns, but flexible (no fixed schema).
  • Primary Key: Uniquely identifies each item. Can be a simple Partition Key or a composite Partition Key + Sort Key.

Setting Up Your DynamoDB Table

Before Lambda can interact with DynamoDB, you need a table. You can create one easily in the AWS Management Console.

When creating, you'll define a Primary Key. For example, an id attribute as a Partition Key is common for simple lookups.

Giving Lambda DynamoDB Access

For your Lambda function to talk to DynamoDB, it needs permission. This is managed via an IAM Role attached to your Lambda function.

You'll need to grant policies like dynamodb:PutItem, dynamodb:GetItem, etc., to specific tables for secure, granular access. For simplicity in learning, AmazonDynamoDBFullAccess might be used initially, but always prefer least privilege in production.

Writing Data: The PutItem Op

The PutItem operation is used to add a new item to a table or replace an existing item if an item with the same primary key already exists.

Try running this example to see how to add an item. We're using a mock AWS SDK for local execution.

// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
  DocumentClient: function() {
    return {
      put: (params) => ({
        promise: () => {
          console.log("MOCK: Put item to table '" + params.TableName + "':", params.Item);
          return Promise.resolve({ success: true, item: params.Item });
        }
      })
    };
  }
};

// Simulate the Lambda handler function
async function handler(event) {
  const ddb = new mockDynamoDB.DocumentClient();

  const params = {
    TableName: "MyUsersTable", // Replace with your table name
    Item: {
      id: event.userId,
      name: event.userName,
      email: event.userEmail
    }
  };

  try {
    const data = await ddb.put(params).promise();
    console.log("Operation successful (mock):", data);
    return { statusCode: 200, body: JSON.stringify(data) };
  } catch (err) {
    console.error("Operation failed (mock):", err);
    return { statusCode: 500, body: JSON.stringify(err) };
  }
}

// Entry point for CoddyKit's runnable environment
async function main() {
  console.log("Running simulated PutItem operation...");
  const testEvent = {
    userId: "user123",
    userName: "Alice",
    userEmail: "alice@example.com"
  };
  await handler(testEvent);
}

main();

Understanding the PutItem Code

In the example, we're using DynamoDB.DocumentClient() to simplify interactions with DynamoDB, as it handles data types automatically.

  • TableName: The name of your DynamoDB table.
  • Item: A JavaScript object representing the data you want to store. Each key-value pair is an attribute.
  • promise(): Used to handle the asynchronous nature of AWS SDK calls.

Reading Data: The GetItem Op

To retrieve a single item from your table, you use the GetItem operation. You must provide the full Primary Key of the item you want to fetch.

Run this code to see how to get an item back.

// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
  DocumentClient: function() {
    return {
      get: (params) => ({
        promise: () => {
          console.log("MOCK: Get item from table '" + params.TableName + "' with Key:", params.Key);
          // Simulate finding an item with id 'user123'
          if (params.Key.id === "user123") {
            return Promise.resolve({ Item: { id: "user123", name: "Alice", email: "alice@example.com" } });
          }
          return Promise.resolve({ Item: null }); // Item not found
        }
      })
    };
  }
};

// Simulate the Lambda handler function
async function handler(event) {
  const ddb = new mockDynamoDB.DocumentClient();

  const params = {
    TableName: "MyUsersTable", // Replace with your table name
    Key: {
      id: event.userId // The primary key to retrieve
    }
  };

  try {
    const data = await ddb.get(params).promise();
    console.log("Retrieved item (mock):", data.Item);
    return { statusCode: 200, body: JSON.stringify(data.Item) };
  } catch (err) {
    console.error("Operation failed (mock):", err);
    return { statusCode: 500, body: JSON.stringify(err) };
  }
}

// Entry point for CoddyKit's runnable environment
async function main() {
  console.log("Running simulated GetItem operation...");
  const testEvent = {
    userId: "user123" // ID of the item to retrieve
  };
  await handler(testEvent);
}

main();

Updating Data: The UpdateItem Op

The UpdateItem operation modifies existing attributes of an item or adds new attributes if they don't exist. It's more efficient than reading, modifying, and then putting the whole item back.

This example updates the email for an existing user.

// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
  DocumentClient: function() {
    return {
      update: (params) => ({
        promise: () => {
          console.log("MOCK: Update item in table '" + params.TableName + "' with Key:", params.Key);
          console.log("MOCK: Update Expression:", params.UpdateExpression, "Values:", params.ExpressionAttributeValues);
          return Promise.resolve({ Attributes: { id: params.Key.id, email: "updated@example.com" } });
        }
      })
    };
  }
};

// Simulate the Lambda handler function
async function handler(event) {
  const ddb = new mockDynamoDB.DocumentClient();

  const params = {
    TableName: "MyUsersTable", // Replace with your table name
    Key: {
      id: event.userId // Primary key of the item to update
    },
    UpdateExpression: "set email = :e",
    ExpressionAttributeValues: {
      ":e": event.newEmail
    },
    ReturnValues: "UPDATED_NEW" // Return the new values of updated attributes
  };

  try {
    const data = await ddb.update(params).promise();
    console.log("Updated item (mock):", data.Attributes);
    return { statusCode: 200, body: JSON.stringify(data.Attributes) };
  } catch (err) {
    console.error("Operation failed (mock):", err);
    return { statusCode: 500, body: JSON.stringify(err) };
  }
}

// Entry point for CoddyKit's runnable environment
async function main() {
  console.log("Running simulated UpdateItem operation...");
  const testEvent = {
    userId: "user123",
    newEmail: "alice.new@example.com"
  };
  await handler(testEvent);
}

main();

Deleting Data: The DeleteItem Op

When you no longer need an item, you can remove it using the DeleteItem operation. Just like GetItem, you must specify the full primary key of the item to delete.

Be careful with deletions, as they are permanent!

// MOCK AWS SDK for local runnable example
const mockDynamoDB = {
  DocumentClient: function() {
    return {
      delete: (params) => ({
        promise: () => {
          console.log("MOCK: Delete item from table '" + params.TableName + "' with Key:", params.Key);
          return Promise.resolve({ success: true });
        }
      })
    };
  }
};

// Simulate the Lambda handler function
async function handler(event) {
  const ddb = new mockDynamoDB.DocumentClient();

  const params = {
    TableName: "MyUsersTable", // Replace with your table name
    Key: {
      id: event.userId // Primary key of the item to delete
    }
  };

  try {
    const data = await ddb.delete(params).promise();
    console.log("Item deleted successfully (mock).");
    return { statusCode: 200, body: JSON.stringify(data) };
  } catch (err) {
    console.error("Operation failed (mock):", err);
    return { statusCode: 500, body: JSON.stringify(err) };
  }
}

// Entry point for CoddyKit's runnable environment
async function main() {
  console.log("Running simulated DeleteItem operation...");
  const testEvent = {
    userId: "user123" // ID of the item to delete
  };
  await handler(testEvent);
}

main();

Quick Check: DynamoDB Actions

You've learned about basic DynamoDB operations. Let's test your understanding!

Recap: Lambda + DynamoDB

Great job! You've learned how to integrate AWS Lambda with Amazon DynamoDB for powerful serverless applications.

  • DynamoDB provides a scalable NoSQL database.
  • Lambda functions need IAM permissions to interact with DynamoDB tables.
  • You can perform common operations like PutItem (create/replace), GetItem (read), UpdateItem (modify), and DeleteItem (remove).

This integration is fundamental for building dynamic, event-driven serverless backends!

常见问题解答

「与 DynamoDB 集成」课时是免费的吗？

是的 — 「与 DynamoDB 集成」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Serverless AWS Lambda Development 课程的其余内容，请升级到 CoddyKit PRO。 Serverless AWS Lambda Development 课程共包含 4 节课。

「与 DynamoDB 集成」这节课中我会学到什么？

将 Lambda 函数连接到 Amazon DynamoDB——一种完全托管的 NoSQL 数据库，为无服务器应用提供高性能、可扩展的数据存储与读取能力 你通过在浏览器中直接运行的动手代码来练习 Serverless AWS Lambda Development，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Serverless AWS Lambda Development 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Serverless AWS Lambda Development 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 1 节课，共 4 节。

「与 DynamoDB 集成」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Serverless AWS Lambda Development 课中编写并运行代码吗？

能。每节 Serverless AWS Lambda Development 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. 与 DynamoDB 集成
  2. 使用 S3 存储文件与处理事件
  3. 选择合适的数据存储
  4. 使用 Amazon ElastiCache 和 DAX 进行缓存
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