Data
252 learners
Getting Started with PySpark and RDDs
Embark on your PySpark adventure by mastering Resilient Distributed Datasets (RDDs). Create and transform data efficiently, unlocking the basics needed to handle large datasets and set the stage for exciting data processing challenges ahead.
Python
Spark
See path
5 lessons
22 practices
3 hours
Badge for Big Data Processing,
Big Data Processing
Lessons and practices
Lesson 1: Creating Your First RDD with SparkSession
Building Your First PySpark RDD
Optimize SparkSession Configuration
Fix Bugs in PySpark Script
Create and Collect the RDD
Build a PySpark Application
Lesson 2: Loading and Analyzing File Data with RDDs
Complete the RDD Operations with File
Switch File Format in PySpark
Troubleshooting RDD File Loading
Complete RDD Operations from File
Master RDD File Operations
Lesson 3: Applying Map Transformations to RDDs
Complete the PySpark Map Transformation
Cube RDD Elements with Map
Capitalizing Words with Map Transformation
Master Map Transformations with Usernames
Lesson 4: Filtering RDD Elements Based on Conditions
Inserting PySpark Filter Method
Filter Odd Numbers in PySpark
Filtering Names RDD in PySpark
Filter Logs Within RDD
Lesson 5: Transforming and Saving Data with RDDs
Complete the Code for Saving Data
Modify RDD Data Reading Pattern
Master RDD Data Partitioning
Process High-Value Sales Effortlessly
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