upload xl/CSV to S3 and process it via lambda for db insert

create a bucket 

create a lambda function and add trigger function as S3

when you create lambda a role will be created for you, add additional policy to it , dynamodb and S3 policy

Now add the following code in the lambda_handler function of the lambda

========================================

import json
import boto3

s3 = boto3.client('s3')
dynamodb = boto3.resource('dynamodb')

def lambda_handler(event, context):
    # TODO implement
   
    bucket = event['Records'][0]['s3']['bucket']['name']
    key = event['Records'][0]['s3']['object']['key']

    obj = s3.get_object(Bucket=bucket, Key=key)

    rows = obj['Body'].read().decode('utf-8') .split('\n')

    table = dynamodb.Table('entity')
   
    print(len(rows))
    with table.batch_writer() as batch:
        for row in rows[:-1]:
            batch.put_item(Item={

                'name':row.split(',')[0],
                'address':row.split(',')[1]
            })
           
    return {
        'statusCode': 200,
        'body': json.dumps('Hello from Lambda!')
    }

===================================

^^ make sure you have a dynamodb with table name entity and field name,address 

you can add as many fields as you want.

Now upload the csv to s3 and you should see lambda processing your xl and inserting to dynamo.

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Sample csv

name,address,city

target,23230,austin

walmart,77707,houston

macy,80808,dallas

First row will be skipped as per the lambda for loop