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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
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