Serverless AWS Lambda Development · 课时

S3 与 SQS 事件触发器

学习如何响应 Amazon S3 对象事件（例如上传）以及 Amazon SQS 队列中的消息来触发 Lambda 函数，从而支持数据处理流程

S3 与 SQS 事件触发器 是 CoddyKit 上的免费 Serverless AWS Lambda Development 课时。这是第 3 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。

Events Drive Serverless

Serverless functions, like AWS Lambda, don't just run on their own. They wait for something to happen! This "something" is called an event.

An event is a signal from another service that tells your Lambda function to execute. Think of it like a doorbell ringing for your function to answer.

S3 Bucket Events

Amazon S3 (Simple Storage Service) is a popular cloud storage service. It can generate events when objects are created, deleted, or modified in your buckets.

Object Created (PUT): An image is uploaded.
Object Deleted: A file is removed.
Object Restored: An archived item is brought back.

These events can trigger a Lambda function to process the changes.

Connecting S3 to Lambda

To link an S3 bucket to a Lambda function, you define a trigger. This tells S3 which events to listen for and which Lambda function to invoke.

You specify the S3 bucket.
You choose the event types (e.g., s3:ObjectCreated:*).
You can filter by object prefix or suffix (e.g., only trigger for images/ folder or .jpg files).

What S3 Sends to Lambda

When an S3 event triggers your Lambda function, the function receives a JSON object containing details about the event. This object is the "event" parameter in your function handler.

Key information includes:

Bucket Name: Where the event occurred.
Object Key: The full path and name of the file affected.
Event Name: The specific action (e.g., ObjectCreated:Put).

Processing an S3 Upload

Here's a Python Lambda function that processes an S3 object creation event. It extracts and prints the bucket name and the key of the uploaded object.

Try uploading a file to an S3 bucket configured to trigger this function!

import json

def lambda_handler(event, context):
    for record in event['Records']:
        bucket_name = record['s3']['bucket']['name']
        object_key = record['s3']['object']['key']
        event_name = record['eventName']
        print(f"Event: {event_name}")
        print(f"Bucket: {bucket_name}")
        print(f"Object Key: {object_key}")
    return {
        'statusCode': 200,
        'body': json.dumps('S3 event processed!')
    }

SQS Queue Messages

Amazon SQS (Simple Queue Service) is a message queuing service. It allows different parts of your application to communicate asynchronously without direct interaction.

When messages are sent to an SQS queue, they can trigger a Lambda function. This is great for tasks that can be processed later or in batches, like sending emails or processing orders.

Connecting SQS to Lambda

Setting up an SQS trigger for Lambda is straightforward. Lambda continuously polls the SQS queue for new messages.

You specify the SQS queue.
You define a batch size (1 to 10,000 messages). This determines how many messages Lambda tries to process in a single invocation.
Lambda deletes messages from the queue only after successful processing.

What SQS Sends to Lambda

Similar to S3, an SQS event passed to your Lambda function is a JSON object. It contains an array of Records, each representing a message from the queue.

Each record includes:

Message Body: The actual content of the message.
Message Attributes: Optional metadata about the message.
Receipt Handle: Used internally by SQS for message deletion.

Processing SQS Messages

This Python Lambda function processes messages from an SQS queue. It iterates through the batch of messages received and prints their content.

Imagine each message contains a task to perform!

import json

def lambda_handler(event, context):
    for record in event['Records']:
        message_body = record['body']
        print(f"Received message: {message_body}")
        # Add your processing logic here
    return {
        'statusCode': 200,
        'body': json.dumps('SQS messages processed!')
    }

S3 vs. SQS Triggers

You've learned about two powerful event sources for AWS Lambda: S3 and SQS. They serve different purposes but both enable event-driven architectures.

Which of the following statements are TRUE regarding S3 and SQS Lambda triggers?

Recap: S3 & SQS Triggers

Great job! You've explored how AWS Lambda functions can be triggered by events from Amazon S3 and SQS.

S3 triggers are perfect for reacting to file changes, like image uploads or document processing.
SQS triggers enable asynchronous processing of messages, allowing for decoupled and scalable workflows.

These event sources are fundamental to building powerful, reactive serverless applications!

常见问题解答

「S3 与 SQS 事件触发器」课时是免费的吗？

是的 — 「S3 与 SQS 事件触发器」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。

「S3 与 SQS 事件触发器」这节课中我会学到什么？

学习如何响应 Amazon S3 对象事件（例如上传）以及 Amazon SQS 队列中的消息来触发 Lambda 函数，从而支持数据处理流程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 3 节课，共 4 节。

「S3 与 SQS 事件触发器」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。

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