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At once deeply personal and yet universal, the poet's reflections,
musings, and chronicles of life from birth to death impart a
plethora of emotions, from tenderness to outrage, but also an
intellectual grasp and appreciation of the astronomically low odds
of being born at all. His poems both celebrate and commiserate,
embrace and embroil, tantalize and deny, but, always and in all
ways, depict what it means to be human.
Data is getting bigger, arriving faster, and coming in varied
formats-and it all needs to be processed at scale for analytics or
machine learning. How can you process such varied data workloads
efficiently? Enter Apache Spark. Updated to emphasize new features
in Spark 2.4., this second edition shows data engineers and
scientists why structure and unification in Spark matters.
Specifically, this book explains how to perform simple and complex
data analytics and employ machine-learning algorithms. Through
discourse, code snippets, and notebooks, you'll be able to: Learn
Python, SQL, Scala, or Java high-level APIs: DataFrames and
Datasets Peek under the hood of the Spark SQL engine to understand
Spark transformations and performance Inspect, tune, and debug your
Spark operations with Spark configurations and Spark UI Connect to
data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka
Perform analytics on batch and streaming data using Structured
Streaming Build reliable data pipelines with open source Delta Lake
and Spark Develop machine learning pipelines with MLlib and
productionize models using MLflow Use open source Pandas framework
Koalas and Spark for data transformation and feature engineering
A landmark collection from one of Canada's literary icons, and the
founder of House of Anansi Press, Heart Residence collects for the
first time work from all corners of Dennis Lee's extraordinary
career. This book is an exhilarating revelation. No other poet in
Canada has the depth and range of Dennis Lee - jazzman, jester, and
metaphysician, hardball political thinker and passionate lover, he
has been publishing poems for fifty years. His first book, Kingdom
of Absence, published in 1967, was the founding publication of
House of Anansi Press. Since then Lee has produced work across the
poetic spectrum, from nursery rhymes and skipping songs to
uncompromising moral introspection to full-tilt love songs,
plangent psalms, and ecstatic, solitary prayer. There are poets'
poets and people's poets. And then there are those few who are
neither and both: the few who become, over time, part of the warp
and weft of their culture. Heart Residence collects, for the first
time, work from all corners of this extraordinary career. In its
verve and variety, this is a one-of-a-kind collection.
Super Facts for Super Kids is a fun and fresh take on nonfiction for beginning readers. Filled with engaging photographs, comic-style illustrations, and cool infographics, this Level 2 Ready-to-Read series about animals is sure to flip, float, and fly off the shelves.
What are the most amazing facts about sharks? Whale Sharks can grow to be longer than a school bus, Greenland Sharks can live for up to 600 years, and some kinds of sharks can actually glow in the dark! Find out more super facts&;like how sharks can&;t smile and don&;t have bones&;in this book that presents information in a highly visual way for young readers. A backmatter section touches on ocean conservation and why sharks need to be protected.
This paperback edition comes with two sheets of fin-tastic shark stickers!
Civil Elegies is Dennis Lee's uncompromising exploration of
citizenship, both Canadian and human. Eli Mandel has called Civil
Elegies one of the most important contemporary books of poetry in
our country. It was the winner of the Governor General's Literary
Award for Poetry in 1972. This edition features a new introduction
by noted academic Nick Mount, who places this important collection
in the context of Canadian literature and Lee’s career.
The 12th and final adventure in the legendary Hardman series It's
doing the small, simple favors that gets Jim Hardman in the most
trouble. A waitress he knows asks him to find her missing husband,
a freelance bartender who never returned from a weekend party that
he was working. Hardman figures it's a two-day job that will lead
to a tawdry end. Instead, Hardman and his buddy Hump, the ex-NFL
star, get sucked into a scheme involving a hundred grand in stolen
jewelry and two corpses...and counting. "Hardman spoke directly to
me. If I had a spirit guide with the Hap & Leonard novels, it
was Ralph Dennis. I wish you the joy I got from first reading these
novels." Joe R. Lansdale, New York Times bestselling author
"Everything one expects from a private eye novel: exceptional
characterization, strong and vigorous prose, and a glimpse into a
place and time that has long since disappeared." Mystery Scene
Magazine "Ralph Dennis has mastered the genre and supplied top
entertainment." The New York Times "Among the best book series
around." Philadelphia Daily News "A lightning-paced crime story
packed with irreverence and loads of action." Publishers Weekly "By
far the best of the action-adventure series." Mother Jones Magazine
This new edition includes an afterword by Lee Goldberg, the #1 New
York Times bestselling author of True Fiction
Combine the power of Apache Spark and Python to build effective big
data applications Key Features Perform effective data processing,
machine learning, and analytics using PySpark Overcome challenges
in developing and deploying Spark solutions using Python Explore
recipes for efficiently combining Python and Apache Spark to
process data Book DescriptionApache Spark is an open source
framework for efficient cluster computing with a strong interface
for data parallelism and fault tolerance. The PySpark Cookbook
presents effective and time-saving recipes for leveraging the power
of Python and putting it to use in the Spark ecosystem. You'll
start by learning the Apache Spark architecture and how to set up a
Python environment for Spark. You'll then get familiar with the
modules available in PySpark and start using them effortlessly. In
addition to this, you'll discover how to abstract data with RDDs
and DataFrames, and understand the streaming capabilities of
PySpark. You'll then move on to using ML and MLlib in order to
solve any problems related to the machine learning capabilities of
PySpark and use GraphFrames to solve graph-processing problems.
Finally, you will explore how to deploy your applications to the
cloud using the spark-submit command. By the end of this book, you
will be able to use the Python API for Apache Spark to solve any
problems associated with building data-intensive applications. What
you will learn Configure a local instance of PySpark in a virtual
environment Install and configure Jupyter in local and multi-node
environments Create DataFrames from JSON and a dictionary using
pyspark.sql Explore regression and clustering models available in
the ML module Use DataFrames to transform data used for modeling
Connect to PubNub and perform aggregations on streams Who this book
is forThe PySpark Cookbook is for you if you are a Python developer
looking for hands-on recipes for using the Apache Spark 2.x
ecosystem in the best possible way. A thorough understanding of
Python (and some familiarity with Spark) will help you get the best
out of the book.
Build data-intensive applications locally and deploy at scale using
the combined powers of Python and Spark 2.0 About This Book * Learn
why and how you can efficiently use Python to process data and
build machine learning models in Apache Spark 2.0 * Develop and
deploy efficient, scalable real-time Spark solutions * Take your
understanding of using Spark with Python to the next level with
this jump start guide Who This Book Is For If you are a Python
developer who wants to learn about the Apache Spark 2.0 ecosystem,
this book is for you. A firm understanding of Python is expected to
get the best out of the book. Familiarity with Spark would be
useful, but is not mandatory. What You Will Learn * Learn about
Apache Spark and the Spark 2.0 architecture * Build and interact
with Spark DataFrames using Spark SQL * Learn how to solve graph
and deep learning problems using GraphFrames and TensorFrames
respectively * Read, transform, and understand data and use it to
train machine learning models * Build machine learning models with
MLlib and ML * Learn how to submit your applications
programmatically using spark-submit * Deploy locally built
applications to a cluster In Detail Apache Spark is an open source
framework for efficient cluster computing with a strong interface
for data parallelism and fault tolerance. This book will show you
how to leverage the power of Python and put it to use in the Spark
ecosystem. You will start by getting a firm understanding of the
Spark 2.0 architecture and how to set up a Python environment for
Spark. You will get familiar with the modules available in PySpark.
You will learn how to abstract data with RDDs and DataFrames and
understand the streaming capabilities of PySpark. Also, you will
get a thorough overview of machine learning capabilities of PySpark
using ML and MLlib, graph processing using GraphFrames, and
polyglot persistence using Blaze. Finally, you will learn how to
deploy your applications to the cloud using the spark-submit
command. By the end of this book, you will have established a firm
understanding of the Spark Python API and how it can be used to
build data-intensive applications. Style and approach This book
takes a very comprehensive, step-by-step approach so you understand
how the Spark ecosystem can be used with Python to develop
efficient, scalable solutions. Every chapter is standalone and
written in a very easy-to-understand manner, with a focus on both
the hows and the whys of each concept.
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