PySpark Complete Course

Foundations

01🗄 Big data fundamentals 02🌐 Spark architecture 03⚙️ Spark setup & configuration 04📦 RDD fundamentals

DataFrames & SQL

05📊 DataFrame fundamentals 06🔤 Spark data types 07🔄 DataFrame transformations 08🗃 Spark SQL 09🧮 Built-in functions 10🪟 Window functions 11⚡ Advanced transformations advanced 12💻 User-defined functions (UDFs)

Data I/O & Storage

13📥 Reading data sources 14📤 Writing data 15🗂 Partitioning

Performance & Internals

16🚀 Performance optimization advanced 17🧠 Spark memory internals advanced

Structured Streaming

18a🌊 Streaming fundamentals streaming 18b⚙️ Streaming internals streaming 18c💾 State management streaming 18d🕐 Watermarking streaming 18e📡 Kafka streaming streaming 18f🛡 Fault tolerance streaming 18g✅ Exactly-once semantics streaming 18h🔁 foreachBatch streaming 18i📈 Streaming performance streaming 18j🔗 Stream joins in production streaming

Integrations & Lakehouses

19📡 Kafka + PySpark 20💧 Delta Lake lakehouse 21🧊 Apache Iceberg lakehouse 22🔄 Apache Hudi lakehouse 23🗺 Data lake patterns

Operations & Engineering

24💨 Airflow + Spark ops 25🧪 Testing PySpark ops 26📋 Logging & monitoring ops 27🏢 Databricks ops 28☸️ Spark on Kubernetes ops 29☁️ AWS + Boto3 ops 30❄️ Snowflake + PySpark ops

Security, Governance & Quality

31🔒 Spark security 32🛡 Data governance 33✔️ Data quality ecosystem 34🔀 CI/CD for Spark 35🏛 Enterprise patterns

Deep Dives

36🔬 Spark internals advanced 37🔍 Spark SQL deep dive advanced