PYSPARK · BEGINNER
What is PySpark?
PySpark is the Python API for Apache Spark, a distributed data processing engine used to process large datasets across multiple machines.
Why do Data Engineers use it?
Traditional Python tools are excellent for data that fits comfortably on one machine. Spark is designed for workloads that need distributed processing, making it useful for large-scale ETL and analytics.
Core concepts
- SparkSession — entry point for Spark applications.
- DataFrame — structured distributed data.
- Transformations — operations such as select, filter and join.
- Actions — operations that trigger computation, such as count and collect.
Your first DataFrame
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("SkillPath").getOrCreate()
data = [("Ravi", 25), ("Anita", 28)]
df = spark.createDataFrame(data, ["name", "age"])
df.show()Next step
After DataFrame basics, learn transformations, actions, joins, aggregations, partitioning and Delta Lake.