Uploading CSV Data to DynamoDB using Lambda in Node.js

It can definitely feel overwhelming when you’re just starting out with AWS and trying to connect everything together! Here’s a breakdown that might help you get a clearer picture of the whole process.

1. Storing CSV in S3

The common approach is indeed to upload your CSV file to an S3 bucket first. This way, you can set up a trigger for your Lambda function to run whenever a new file is uploaded. So yes, go for option A!

2. Setting Up Your Lambda Function

When you create your Lambda function, make sure to give it the right permissions. It needs access to both S3 to read the file and DynamoDB to write the data. You’ll typically attach a role that includes the necessary permissions.

3. Reading the CSV File

For reading the CSV file within the Lambda function, you can use the AWS SDK along with a CSV parsing library. csv-parser is pretty straightforward to use in a Lambda function. Here’s how you could structure your code:

const AWS = require('aws-sdk');
const csv = require('csv-parser');
const s3 = new AWS.S3();
const dynamoDB = new AWS.DynamoDB.DocumentClient();

exports.handler = async (event) => {
    const bucket = 'your-bucket-name';
    const key = 'your-csv-file-key.csv';
    
    const data = [];
    
    const params = {
        Bucket: bucket,
        Key: key,
    };
    
    const s3Stream = s3.getObject(params).createReadStream();
    
    s3Stream.pipe(csv())
        .on('data', (row) => {
            data.push(row);
        })
        .on('end', async () => {
            // Here is where you'd write the data to DynamoDB
            await Promise.all(data.map(item => dynamoDB.put({
                TableName: 'YourDynamoDBTable',
                Item: item
            }).promise()));
        });
};

4. Structuring Items for DynamoDB

When converting CSV rows to DynamoDB items, remember that each item should be a JavaScript object, where the keys match your DynamoDB table’s attributes. Make sure to handle types correctly since DynamoDB differentiates between strings, numbers, booleans, etc.

5. Error Handling

As for error handling, definitely plan for cases where the CSV might have bad formatting or if DynamoDB throttles your requests. You can wrap your DynamoDB calls in try-catch blocks and implement retries for throttled requests. Consider using exponential backoff for your retries to minimize the risk of overwhelming the service.

It might feel a bit complex at first, but breaking it down into these steps should make it easier to tackle. Good luck, and remember, practice makes perfect! You’ll get the hang of this in no time!