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PySpark — Free Course — Fun with Learning Technology

Home›Courses›PySpark

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PySpark

Big Data processing with Apache Spark and PySpark

26 topics6 sections26 lessons ready

01

Spark Fundamentals

5

Apache Spark Architecture — Driver, Executor, Cluster
RDDs — Resilient Distributed Datasets
Transformations vs Actions
Lazy Evaluation and DAG
Setting Up PySpark — Local and Cluster

02

DataFrames and SparkSQL

6

PySpark DataFrames vs Pandas
Creating DataFrames
Reading Data Sources — Parquet, CSV, JSON, Delta
Selecting, Filtering, and Aggregating
SparkSQL — Running SQL on DataFrames
Writing Output — Parquet, Delta, JDBC

03

Transformations

5

Joins in Spark — Broadcast, Shuffle
Window Functions in PySpark
UDFs — User Defined Functions
Handling Null Values
String and Date Functions

04

Performance

5

Partitioning and Shuffling
Caching and Persistence
Broadcast Variables and Accumulators
Query Execution Plan — explain()
Tuning — executor memory, cores, shuffle partitions

05

Streaming

3

Spark Structured Streaming Overview
Reading from Kafka
Watermarking and Late Data

06

Interview Prep

2

PySpark Interview Questions
PySpark vs Pandas — Key Differences

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