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Spark in Action, Second Edition
Summary The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you’ll learn to take advantage of Spark’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark’s powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Analyzing ente...
Ollie Spark and the Accidental Adventure
MACHINES, MYSTERIES AND MAYHEM - THIS MUST BE A CASE FOR OLLIE SPARK.Ollie Spark loves mending machines and solving mysteries. But he gets more than he bargained for when fixing Aunt Caz's van throws him into a real-life spy adventure!Ollie is whisked away to a mysterious city with strange plants, an unknown language and suspicious people round every corner. With the help of Gasket, his new dog best friend, he sets off on a mission to save the city - and Aunt Caz - from disaster.Can Ollie fix things before it's too late?!
Learning Spark
Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data 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 step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug 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
Spark
Professor Peyton Wilde has an enviable life teaching sociology at an idyllic liberal arts college--yet she is troubled by a sense of fading inspiration. One day an invitation arrives. Peyton has been selected to attend a luxurious all-expense-paid seminar in Iceland, where participants, billed as some of the greatest thinkers in the world, will be charged with answering one perplexing question. Meeting her diverse teammates--two neuroscientists, a philosopher, a dance teacher, a collage artist, and a farmer--Peyton wonders what she could ever have to contribute. The ensuing journey of discovery will transform the characters' work, their biases, and themselves. This suspenseful novel shows that the answers you seek can be found in the most unlikely places. It can be read for pleasure, is a great choice for book clubs, and can be used as unique and inspiring reading in qualitative research and other courses in education, sociology, social work, psychology, and communication.
Spark: The Definitive Guide
Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing...
Learning PySpark
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 Lear...
Spark in Action, Second Edition
Summary The Spark distributed data processing platform provides an easy-to-implement tool for ingesting, streaming, and processing data from any source. In Spark in Action, Second Edition, you’ll learn to take advantage of Spark’s core features and incredible processing speed, with applications including real-time computation, delayed evaluation, and machine learning. Spark skills are a hot commodity in enterprises worldwide, and with Spark’s powerful and flexible Java APIs, you can reap all the benefits without first learning Scala or Hadoop. Foreword by Rob Thomas. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the t...
Loitering with Intent
Where does art start or reality end? Happily loitering about London, c. 1949, with the intent of gathering material for her writing, Fleur Talbot finds a job “on the grubby edge of the literary world” at the very peculiar Autobiographical Association. Mad egomaniacs writing their memoirs in advance — or poor fools ensnared by a blackmailer? When the association’s pompous director steals Fleur’s manuscript, fiction begins to appropriate life.
PySpark Cookbook
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 Description Apache 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...
