Spark权威指南（影印版 英文版）

Preface

Part I. Gentle Overview of Big Data and Spark

1. What Is Apache Spark?

Apache Spark's Philosophy

Context: The Big Data Problem

History of Spark

The Present and Future of Spark

Running Spark

Downloading Spark Locally

Launching Spark's Interactive Consoles

Running Spark in the Cloud

Data Used in This Book

2. A Gentle Introduction to Spark

Spark's Basic Architecture

Spark Applications

Spark's Language APIs

Spark's APIs

Starting Spark

The SparkSession

DataFrames

Partitions

Transformations

Lazy Evaluation

Actions

Spark UI

An End-to-End Example

DataFrames and SQL

Conclusion

3. A Tour of Spark's Too1set

Running Production Applications

Datasets: Type-Safe Structured APIs

Structured Streaming

Machine Learning and Advanced Analytics

Lower-Level APIs

SparkR

Spark's Ecosystem and Packages

Conclusion

Part II. Structured APls--DataFrames, SQL, and Datasets

4. Structured API Overview

DataFrames and Datasets

Schemas

Overview of Structured Spark Types

DataFrames Versus Datasets

Columns

Rows

Spark Types

Overview of Structured API Execution

Logical Planning

Physical Planning

Execution