Mastering Apache Spark 2.x - Second Edition: Scale your machine learning and deep learning systems with SparkML, DeepLearning4j and H2O: Romeo Kienzler: 9781786462749: Amazon.com: Books

Romeo Kienzler takes the reader on a big and detailed tour through significant Spark topics and exercises, which occur in the practical usage of Spark in Big Data, Analytics, Data Science and Analytic Data Warehouse ("ADW") projects. In his book topics like the new Spark V2 Ecosystem, Machine Learning, Spark Streaming, Graph Processing, Cluster Design and Management (Yarn and Mesos), Cloud based deployments, Performance topics around HDFS, Date importing and handling, Spark Data Source API, Spark Dataframes and Datasets API, Code Generation for expression evaluation, Project Tungsten, Spark error handling and much more are covered. If you have taken one or more of the well done Spark courses from Databricks before, the topics might familiar but the book covers even some more enhanced topics as well it can be taken as a good comprehension or as in-depth notes. Additionally the book focus on very specific details and problems in parallel programming with Spark, derived from practical use cases.As well the book contains links and references on papers, literature and web forums. To summarize I would recommend this book as an excellent starting point and Spark reference guide.