Data EngineeringVER_4.02
Distributed Batch Processing Engine
PythonPySparkApache AirflowLinux
System Architecture
Logic Flow & Infrastructure Analysis
01_The_Problem
Single-node processing hit throughput ceilings and lacked recovery guarantees.
02_Architecture_Solution
PySpark jobs orchestrated by Airflow processed multi-GB batches with worker pool sizing, retry logic, and idempotent writes. Skew-aware partitioning and broadcast joins kept resource usage predictable under growing data volumes.
Execution Metrics
Throughput / Volume
Multi-GB per batch
Performance / Latency
Minutes per batch