Core Apache Spark Concepts

• Resilient Distributed Dataset (RDD)
• DataFrames
• Datasets
• Transformations
• Actions
• Lazy Evaluation
• SparkSession
• SparkContext
• Partitions
• Shuffling
• Persistence & Caching
• Lineage Graphs
• Jobs
• Stages
• Tasks

Apache Spark

• Apache Spark: Big Data Processing & Analytics
• Spark DataFrames: Features, Use Cases & Optimization for Big Data
• Spark Architecture
• Dataframe create from file
• Dataframe Pyspark create from collections
• Spark Dataframe save as csv
• Dataframe save as parquet
• Dataframe show() between take() methods
• Apache SparkSession
• Understanding the RDD of Apache Spark
• Spark RDD creation from collection
• Different method to print data from rdd
• Practical use of unionByName method
• Creating Spark DataFrames: Methods & Examples
• Setup Spark in PyCharm
• Apache Spark all APIs
• Spark for the word count program
• Spark Accumulators
• aggregateByKey in Apache Spark
• Spark Broadcast with Examples
• Spark combineByKey
• Apache Spark Using countByKey
• Spark CrossJoin know all
• Optimizing Spark groupByKey: Usage, Best Practices, and Examples
• Mastering Spark Joins: Inner, Outer, Left, Right & Semi Joins Explained
• Apache Spark: Local Mode vs Cluster Mode - Key Differences & Examples
• Spark map vs flatMap: Key Differences with Examples
• Efficient Data Processing with Spark mapPartitionsWithIndex
• Spark reduceByKey with 5 Real-World Examples
• Spark Union vs UnionAll vs Union Available – Key Differences & Examples