فهرست مطالب

• Table of Contents
• About the Author
• About the Technical Reviewers
• Acknowledgments
• Introduction
• Chapter 1: Introduction to Apache Spark
• Overview
• History
• Spark Core Concepts and Architecture
• Apache Spark 3.0
• Apache Spark Applications
• Spark Example Applications
• Apache Spark Ecosystem
• Summary
• Chapter 2: Working with Apache Spark
• Downloading and Installation
• Having Fun with the Spark Scala Shell
• Introduction to Collaborative Notebooks
• Setting up Spark Source Code
• Summary
• Chapter 3: Spark SQL: Foundation
• Understanding RDD
• Introduction to the DataFrame API
• Creating a DataFrame
• Introduction to Datasets
• Using SQL in Spark SQL
• Writing Data Out to Storage Systems
• The Trio: DataFrame, Dataset, and SQL
• DataFrame Persistence
• Summary
• Chapter 4: Spark SQL: Advanced
• Aggregations
• Joins
• Functions
• Advanced Analytics Functions
• Exploring Catalyst Optimizer
• Summary
• Chapter 5: Optimizing Spark Applications
• Common Performance Issues
• Leverage In-Memory Computation
• Understanding Spark Joins
• Adaptive Query Execution
• Summary
• Chapter 6: Spark Streaming
• Stream Processing
• Spark Streaming Overview
• Spark DStream
• Summary
• Chapter 7: Advanced Spark Streaming
• Event Time
• Arbitrary Stateful Processing
• Handling Duplicate Data
• Fault Tolerance
• Streaming Query Metrics and Monitoring
• Summary
• Chapter 8: Machine Learning with Spark
• Machine Learning Overview
• Spark Machine Learning Library
• Machine Learning Tasks in Action
• Deep Learning Pipeline
• Summary
• Chapter 9: Managing the Machine Learning Life Cycle
• The Rise of MLOps
• MLflow Overview
• Model Deployment and Prediction
• Summary
• Index