Big Data & Distributed Computing

Production-grade big data processing with Apache Spark, distributed systems patterns, and petabyte-scale data engineering.

Quick Start

# PySpark 3.5+ modern DataFrame API
from pyspark.sql import SparkSession
from pyspark.sql import functions as F
from pyspark.sql.window import Window

# Initialize Spark with optimal settings
spark = (SparkSession.builder
    .appName("ProductionETL")
    .config("spark.sql.adaptive.enabled", "true")
    .config("spark.sql.adaptive.coalescePartitions.enabled", "true")
    .config("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
    .getOrCreate())