Excellent 👍
Now you’re entering real AWS Data Engineering territory.

📚 LESSON 4 — AWS Glue Catalog

(Hive Metastore → AWS Glue | Hands-On + Interview-Ready)

AWS Glue

🎯 Lesson Outcome

By the end of this lesson, you will:

• Replace Hive Metastore with Glue Catalog
• Create Glue Database & Tables
• Use Glue Crawler
• Query data using Athena
• Add strong resume bullets

🧠 First: Understand the Role of Glue Catalog

Think like this:

Glue Catalog is ONLY metadata, not data.

📌 Spark, Athena, EMR all read schema from Glue

🧩 Glue Architecture (Visual Mental Model)

S3 (raw data)
   ↓
Glue Crawler
   ↓
Glue Catalog (schema)
   ↓
Athena / EMR / Spark

1️⃣ Create Glue Database (Hands-On)

🔹 Go to:

AWS Console → Glue → Data Catalog → Databases → Add database

🔹 Database Details

• Name:

rajeev_data_lake_db

• Description:

Glue catalog for S3 data lake

Create database ✅

🧪 TASK 1 (Reply Required)

Glue database created: YES
Database name:

2️⃣ Create Glue Crawler (MOST IMPORTANT STEP)

🧠 What is a Crawler?

A crawler:

• Scans S3
• Infers schema
• Creates Glue tables automatically

🔹 Create Crawler

Glue → Crawlers → Create crawler

Step-by-Step:

• Name:

sales-raw-crawler

• Data source:
  • S3
  • Path:

s3://rajeev-data-lake-2026/raw/sales/

• IAM Role:
  • Create new role

AWSGlueServiceRole-sales

• Target database:

rajeev_data_lake_db

• Table name prefix:

raw_

Create crawler ✅

▶️ Run the Crawler

Click Run crawler

Wait ~1 minute ⏳

🧪 TASK 2 (Reply Required)

Crawler run: SUCCESS
Table created:

(Expected: raw_sales)

3️⃣ Verify Glue Table (Schema Check)

Go to:
Glue → Databases → rajeev_data_lake_db → Tables

Open table:

raw_sales

You should see:

• Columns
• Data types
• S3 location

📌 Exactly like Hive Metastore

4️⃣ Query Using Athena (BIG INTERVIEW POINT)

Amazon Athena

🔹 Setup Athena (First Time Only)

1. Go to Athena
2. Set query result location:

s3://rajeev-data-lake-2026/athena-results/

(Create folder if needed)

🔹 Run SQL

SELECT * FROM rajeev_data_lake_db.raw_sales;

🎉 You just ran serverless SQL on S3

🧠 On-Prem vs AWS Querying

💡 Interview GOLD (Remember This)

✔ Glue is metadata only
✔ Athena reads data directly from S3
✔ Glue Crawler handles schema evolution
✔ Spark uses Glue as metastore

🧾 Resume Bullets You Earn

Implemented AWS Glue Catalog as Hive Metastore replacement
Automated schema discovery using Glue Crawlers and queried data via Athena

⏭ NEXT LESSON (VERY EXCITING)

⚡ LESSON 5 — PySpark on AWS (EMR)

You will:

• Launch EMR cluster
• Attach IAM role
• Read S3 data in PySpark
• Write transformed data back to S3

Amazon EMR

🔔 Quick Confirmation (Reply)

Glue DB created:
Crawler success:
Athena query ran:

Once confirmed, we jump into Lesson 5: Spark on EMR 🚀