فهرست مطالب

• Cover
• Title Page
• Copyright and Credits
• Foreword
• Contributors
• Table of Contents
• Preface
• Part 1: Exam Overview
• Chapter 1: Overview of the Certification Guide and Exam
• Overview of the certification exam
• Registering for your exam
• Types of questions
• Summary
• Part 2: Introducing Spark
• Chapter 2: Understanding Apache Spark and Its Applications
• What is Apache Spark?
• Why choose Apache Spark?
• What are the Spark use cases?
• Who are the Spark users?
• Summary
• Sample questions
• Chapter 3: Spark Architecture and Transformations
• Spark architecture
• Execution hierarchy
• Spark components
• Partitioning in Spark
• Deployment modes
• RDDs
• Summary
• Sample questions
• Part 3: Spark Operations
• Chapter 4: Spark DataFrames and their Operations
• Getting Started in PySpark
• Dataset API
• DataFrame API
• Creating DataFrame operations
• How to view the DataFrames
• Collecting the data
• Converting a PySpark DataFrame to a Pandas DataFrame
• How to manipulate data on rows and columns
• Summary
• Sample question
• Chapter 5: Advanced Operations and Optimizations in Spark
• Grouping data in Spark and different Spark joins
• Joining DataFrames in Spark
• Reading and writing data
• Using SQL in Spark
• UDFs in Apache Spark
• Optimizations in Apache Spark
• Data-based optimizations in Apache Spark
• Narrow and wide transformations in Apache Spark
• Persisting and caching in Apache Spark
• Repartitioning and coalescing in Apache Spark
• Summary
• Sample questions
• Chapter 6: SQL Queries in Spark
• What is Spark SQL?
• Getting started with Spark SQL
• Advanced Spark SQL operations
• Summary
• Sample questions
• Part 4: Spark Applications
• Chapter 7: Structured Streaming in Spark
• Real-time data processing
• What is streaming?
• Streaming architectures
• Introducing Spark Streaming
• Introducing Structured Streaming
• Streaming fundamentals
• Structured Streaming concepts
• Streaming sources and sinks
• Advanced techniques in Structured Streaming
• Different joins in Structured Streaming
• Final thoughts and future developments
• Summary
• Chapter 8: Machine Learning with Spark ML
• Introduction to ML
• ML with Spark
• ML life cycle
• Problem statement
• Case studies and real-world examples
• Future trends in Spark ML and distributed ML
• Summary
• Part 5: Mock Papers
• Chapter 9: Mock Test 1
• Questions
• Chapter 10: Mock Test 2
• Questions
• Index
• Other Books You May Enjoy