What this book covers
Chapter 1, Discovering Databricks, will help you learn the fundamentals of Spark and all the different features of the Databricks platform and workspace.
Chapter 2, Batch and Real-Time Processing in Databricks, will help you learn about the SQL/DataFrame API for processing batch loads and the Streaming API for processing real-time data streams.
Chapter 3, Learning about Machine Learning and Graph Processing in Databricks, will help you get an introduction to machine learning on big data using SparkML and the Spark Graph Processing API.
Chapter 4, Managing Spark Clusters, will help you learn to select the optimal Spark cluster configurations for running big data processing and workloads in Databricks.
Chapter 5, Big Data Analytics, will help you learn some very useful optimization techniques for Spark DataFrames.
Chapter 6, Databricks Delta Lake, will help you learn the best practices for optimizing Delta Lake workloads in Databricks.
Chapter 7, Spark Core, will help you learn techniques to optimize Spark jobs through a true understanding of Spark core.
Chapter 8, Case Studies, will look at a number of real-world case studies where Databricks played a crucial role in an organization's data journey. We will also learn how Databricks is helping drive innovation across various industries around the world.
