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Module-07
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Module7-Lambda-Code.py
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aws-data-engineering
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Module7-Lambda-Code.py
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import base64
import json
import boto3
import os
from datetime import datetime
s3_client = boto3.client("s3")
# Get the current datetime object
date_obj = datetime.now()
# Format the datetime object as a string
timestamp = date_obj.strftime("%Y-%m-%d-%H-%M-%S")
# Create an empty list to store the whole batch of records
kinesis_records = []
# Environment variable for S3 bucket name
bucket_name = os.environ["bucket_name"]
def lambda_handler(event, context):
# Get some information of the size of the batch
record_count = len(event["Records"])
print(f"Received {record_count} records from Kinesis stream.")
for record in event["Records"]:
# Kinesis data is base64 encoded so decode here
payload = base64.b64decode(record["kinesis"]["data"]).decode("utf-8")
# Use this print statement for more verbose logging
# print("Decoded payload: " + payload)
kinesis_records.append(payload)
# Convert the list of records to a JSON string
json_data = json.dumps(kinesis_records)
file_name = f"data_{timestamp}.json"
s3_client.put_object(
Bucket=bucket_name,
Key=file_name,
Body=json_data,
ContentType="application/json",
)
print(f"Successfully uploaded file to S3: {file_name}")
return "Successfully processed {} records.".format(len(event["Records"]))
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