更新时间：2021-08-20 10:32:41
封面
版权页
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
eBooks discount offers and more
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Big Data Analytics at a 10 000-Foot View
Big Data analytics and the role of Hadoop and Spark
Big Data science and the role of Hadoop and Spark
Tools and techniques
Real-life use cases
Summary
Chapter 2. Getting Started with Apache Hadoop and Apache Spark
Introducing Apache Hadoop
Introducing Apache Spark
Why Hadoop plus Spark?
Installing Hadoop plus Spark clusters
Chapter 3. Deep Dive into Apache Spark
Starting Spark daemons
Learning Spark core concepts
Lifecycle of Spark program
Spark applications
Persistence and caching
Spark resource managers – Standalone YARN and Mesos
Chapter 4. Big Data Analytics with Spark SQL DataFrames and Datasets
History of Spark SQL
Architecture of Spark SQL
Introducing SQL Datasources DataFrame and Dataset APIs
Evolution of DataFrames and Datasets
Why Datasets and DataFrames?
When to use RDDs Datasets and DataFrames?
Analytics with DataFrames
Analytics with the Dataset API
Data Sources API
Spark SQL as a distributed SQL engine
Hive on Spark
Chapter 5. Real-Time Analytics with Spark Streaming and Structured Streaming
Introducing real-time processing
Architecture of Spark Streaming
Spark Streaming transformations and actions
Input sources and output stores
Spark Streaming with Kafka and HBase
Advanced concepts of Spark Streaming
Monitoring applications
Introducing Structured Streaming
Chapter 6. Notebooks and Dataflows with Spark and Hadoop
Introducing web-based notebooks
Introducing Jupyter
Introducing Apache Zeppelin
The Livy REST job server and Hue Notebooks
Introducing Apache NiFi for dataflows
Chapter 7. Machine Learning with Spark and Hadoop
Introducing machine learning
Machine learning on Spark and Hadoop
Machine learning algorithms
An example of machine learning algorithms
Building machine learning pipelines
Machine learning with H2O and Spark
Introducing Hivemall
Introducing Hivemall for Spark
Chapter 8. Building Recommendation Systems with Spark and Mahout
Building recommendation systems
Limitations of a recommendation system
A recommendation system with MLlib
The Mahout and Spark integration
Chapter 9. Graph Analytics with GraphX
Introducing graph processing
Getting started with GraphX
Analyzing flight data using GraphX
Introducing GraphFrames
Chapter 10. Interactive Analytics with SparkR
Introducing R and SparkR
Getting started with SparkR
Using DataFrames with SparkR
Using SparkR with RStudio
Machine learning with SparkR
Using SparkR with Zeppelin
Index
