DynamoDB와 통합하기
완전 관리형 NoSQL 데이터베이스인 Amazon DynamoDB에 Lambda 함수를 연결하여 서버리스 애플리케이션에서 고성능의 확장 가능한 데이터 저장 및 검색을 구현합니다.
DynamoDB와 통합하기은(는) CoddyKit의 무료 Serverless AWS Lambda Development 강의입니다. 이것은 4개 중 1번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Serverless AWS Lambda Development 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Serverless AWS Lambda Development 강의에는 총 4개의 강의가 포함되어 있습니다.
이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.
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), andDeleteItem(remove).
This integration is fundamental for building dynamic, event-driven serverless backends!
자주 묻는 질문
“DynamoDB와 통합하기” 강의는 무료인가요?
네 — “DynamoDB와 통합하기” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 Serverless AWS Lambda Development 강의 전체를 잠금 해제할 수 있습니다. Serverless AWS Lambda Development 강의에는 총 4개의 강의가 포함되어 있습니다.
“DynamoDB와 통합하기”에서 뭘 배우나요?
완전 관리형 NoSQL 데이터베이스인 Amazon DynamoDB에 Lambda 함수를 연결하여 서버리스 애플리케이션에서 고성능의 확장 가능한 데이터 저장 및 검색을 구현합니다. 브라우저에서 직접 실행하는 실습 코드로 Serverless AWS Lambda Development을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.
Serverless AWS Lambda Development을(를) 시작하는 데 경험이 필요한가요?
사전 경험은 필요하지 않습니다. CoddyKit의 Serverless AWS Lambda Development은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 1번째 강의입니다.
“DynamoDB와 통합하기” 강의는 얼마나 걸리나요?
대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.
이 Serverless AWS Lambda Development 강의에서 코드를 작성하고 실행할 수 있나요?
네. 모든 Serverless AWS Lambda Development 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.