infra: mirror light per-source Airflow DAGs + generators (GEN_ROWS), fix script path

2026-06-26 01:07:23 +00:00
parent 9400f9410c
commit 62b416d210
6 changed files with 690 additions and 0 deletions
@@ -0,0 +1,107 @@
+#!/usr/bin/env python3
+"""
+Script to generate fake employee event data for MySQL
+Generates approximately 1GB of data
+"""
+
+import mysql.connector
+import random
+from datetime import datetime, timedelta
+import uuid
+import sys
+
+# Database connection details
+DB_HOST = "10.0.21.51"
+DB_PORT = "3306"
+DB_NAME = "hr"
+DB_USER = "mo"
+DB_PASSWORD = "Dell2026!"
+
+# Data generation settings
+import os
+TARGET_ROWS = int(os.getenv("GEN_ROWS", "5000"))  # light, configurable via GEN_ROWS
+BATCH_SIZE = min(10000, max(500, TARGET_ROWS))
+
+# Sample data
+DEPARTMENTS = ["HR", "Operations", "Sales", "Marketing", "Finance", "IT", "Engineering", "Legal"]
+ROLE_NAMES = ["Analyst", "Lead", "Manager", "Consultant", "Director", "Engineer", "Specialist", "Coordinator"]
+REGIONS = ["EU", "APAC", "LATAM", "NA", "EMEA"]
+EVENT_TYPES = ["TRANSFER", "PROMOTION", "TERMINATION", "HIRED", "SALARY_CHANGE", "DEPARTMENT_CHANGE"]
+
+def generate_fake_employee_event():
+    """Generate a single fake employee event"""
+    employee_id = random.randint(1, 100000)
+    department = random.choice(DEPARTMENTS)
+    role_name = random.choice(ROLE_NAMES)
+    region = random.choice(REGIONS)
+    event_type = random.choice(EVENT_TYPES)
+    
+    # Random timestamp within the last 2 years
+    days_ago = random.randint(0, 730)
+    event_ts = datetime.now() - timedelta(days=days_ago, hours=random.randint(0, 23), 
+                                          minutes=random.randint(0, 59))
+    
+    salary_change = round(random.uniform(1000.0, 20000.0), 2) if random.random() > 0.3 else None
+    
+    # Generate a long notes field (like the existing data)
+    notes = str(uuid.uuid4()) * 10
+    
+    return (employee_id, department, role_name, region, event_type, salary_change, event_ts, notes)
+
+def main():
+    print(f"Connecting to MySQL at {DB_HOST}:{DB_PORT}...")
+    
+    conn = mysql.connector.connect(
+        host=DB_HOST,
+        port=DB_PORT,
+        database=DB_NAME,
+        user=DB_USER,
+        password=DB_PASSWORD
+    )
+    cursor = conn.cursor()
+    
+    print(f"Generating {TARGET_ROWS} employee events...")
+    print(f"Batch size: {BATCH_SIZE}")
+    
+    total_generated = 0
+    batch = []
+    
+    for i in range(TARGET_ROWS):
+        batch.append(generate_fake_employee_event())
+        
+        if len(batch) >= BATCH_SIZE:
+            cursor.executemany(
+                """
+                INSERT INTO employee_events (employee_id, department, role_name, region, 
+                                            event_type, salary_change, event_ts, notes)
+                VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
+                """,
+                batch
+            )
+            conn.commit()
+            total_generated += len(batch)
+            batch = []
+            
+            if total_generated % 100000 == 0:
+                print(f"Generated {total_generated} rows...")
+    
+    # Insert remaining rows
+    if batch:
+        cursor.executemany(
+            """
+            INSERT INTO employee_events (employee_id, department, role_name, region, 
+                                        event_type, salary_change, event_ts, notes)
+            VALUES (%s, %s, %s, %s, %s, %s, %s, %s)
+            """,
+            batch
+        )
+        conn.commit()
+        total_generated += len(batch)
+    
+    cursor.close()
+    conn.close()
+    
+    print(f"Completed! Generated {total_generated} employee events.")
+
+if __name__ == "__main__":
+    main()