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1.
Introduction
1.1
Project Goals
1.2
Purpose and Applications
2.
Preparation Steps
2.1
Create IAM Role
2.2
Create S3 Bucket
2.3
Upload Sample Data
3.
Create Glue Crawler
3.1
Create Glue Database
3.2
Create Glue Crawler
3.3
Run Crawler
4.
Create Glue Job
4.1
Create New Glue Job
4.2
Write ETL Script
4.3
Run Job & Verify Output
5.
Create Glue Crawler for Processed Data
5.1
Create New Crawler
5.2
Run Crawler and Verify Table
6.
Query with Amazon Athena
6.1
Configure Athena
6.2
Query Processed Data
6.3
Advanced Queries
7.
Automate with AWS Lambda
7.1
Create Lambda Function
7.2
Write Python Code for Lambda
7.3
Attach S3 Trigger
7.4
Track User Behavior with AWS CloudTrail
8.
Visualize with Amazon QuickSight
8.1
Connect Athena to QuickSight
8.2
Create interactive dashboard
9.
Clean Up Resources
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Cloud Journey
Last Updated
26-11-2023
Team
Gia Hưng
AWS Data Pipeline Workshop
>
Automate with AWS Lambda
> Create Lambda Function
7.1 Create Lambda Function
Create Lambda Function
7.1 Create Lambda Function
Go to
AWS Lambda
→ Select
Create function
Select Author from scratch:
Name:
gluecrawljob
Runtime: Python 3.13
Role: select the IAM Role created (with Glue + CloudWatch + S3 permissions)
In the function code section, you will write code to perform:
Start crawler for
sales_data_raw
Run Glue Job
ProcessJob
Run crawler for
sales_data_processed