PySpark is the Python API for Apache Spark, the distributed computing framework designed for large-scale data processing. By leveraging Spark's in-memory computation engine and resilient distributed datasets (RDDs), PySpark enables data scientists and engineers to process terabytes of data across clusters while writing code in Python. Understanding the lazy evaluation model is critical—transformations build a logical plan, but nothing executes until an action is called, allowing Spark's Catalyst optimizer to generate the most efficient physical execution strategy. This approach makes PySpark both powerful for big data workloads and surprisingly accessible for those familiar with pandas-style operations.