A richly illustrated look at the natural history of moths Moths are among the most underappreciated insects on the planet, yet they make up the majority of some 180,000 known species of Lepidoptera. Filled with striking images, The Lives of Moths looks at the remarkable world of these amazing and beautiful creatures. While butterflies may get more press than moths, Andrei Sourakov and Rachel Warren Chadd reveal that the lopsided attention is unjust. Moths evolved long before butterflies, and their importance cannot be overestimated. From the tiniest leaf miners to exotic hawk moths that are two hundred to three hundred times larger, these creatures are often crucial pollinators of flowers, including many that bloom at night or in twilight. The authors show that moths and their larvae are the main food source for thousands of animal species, and interact with other insect, plant, and vertebrate communities in ecosystems around the world, from tropical forests and alpine meadows to deserts and wetlands. The authors also explore such topics as evolution, life cycles, methods of communication, and links to humans. A feast of remarkable facts and details, The Lives of Moths will appeal to insect lovers everywhere.

Apache Spark is amazing when everything clicks. But if you haven't seen the performance improvements you expected, or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources. Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you'll also learn how to make it sing. With this book, you'll explore: How Spark SQL's new interfaces improve performance over SQL's RDD data structure The choice between data joins in Core Spark and Spark SQL Techniques for getting the most out of standard RDD transformations How to work around performance issues in Spark's key/value pair paradigm Writing high-performance Spark code without Scala or the JVM How to test for functionality and performance when applying suggested improvements Using Spark MLlib and Spark ML machine learning libraries Spark's Streaming components and external community packages