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Big Data Processing with Apache Spark: Efficiently tackle large datasets and big data analysis with Spark and Python - Tapa blanda
Sinopsis
No need to spend hours ploughing through endless data - let Spark, one of the fastest big data processing engines available, do the hard work for you.
Key Features:
- Get up and running with Apache Spark and Python
- Integrate Spark with AWS for real-time analytics
- Apply processed data streams to machine learning APIs of Apache Spark
Book Description:
Processing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.
You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption.
By the end of this book, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects.
What You Will Learn:
- Write your own Python programs that can interact with Spark
- Implement data stream consumption using Apache Spark
- Recognize common operations in Spark to process known data streams
- Integrate Spark streaming with Amazon Web Services (AWS)
- Create a collaborative filtering model with the movielens dataset
- Apply processed data streams to Spark machine learning APIs
Who this book is for:
Data Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Manuel Ignacio Franco Galeano is a computer scientist from Colombia. He works for Fender Musical Instruments as a lead engineer in Dublin, Ireland. He holds a master's degree in computer science from University College, Dublin UCD. His areas of interest and research are music information retrieval, data analytics, distributed systems, and blockchain technologies.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Big Data Processing with Apache Spark Efficiently tackle large datasets and big data analysis with Spark and Python
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Big Data Processing with Apache Spark: Efficiently tackle large datasets and big data analysis with Spark and Python
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Big Data Processing with Apache Spark: Efficiently tackle large datasets and big data analysis with Spark and Python
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Big Data Processing with Apache Spark (Paperback or Softback)
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Packt Publishing 10/31/2018, 2018
ISBN 10: 1789808812
ISBN 13: 9781789808810
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Big Data Processing with Apache Spark
Publicado por
Packt Publishing Limited, GB, 2018
ISBN 10: 1789808812
ISBN 13: 9781789808810
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Paperback. Condición: New. No need to spend hours ploughing through endless data - let Spark, one of the fastest big data processing engines available, do the hard work for you.Key FeaturesGet up and running with Apache Spark and PythonIntegrate Spark with AWS for real-time analyticsApply processed data streams to machine learning APIs of Apache SparkBook DescriptionProcessing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption.By the end of this book, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects.What you will learnWrite your own Python programs that can interact with SparkImplement data stream consumption using Apache SparkRecognize common operations in Spark to process known data streamsIntegrate Spark streaming with Amazon Web Services (AWS)Create a collaborative filtering model with the movielens datasetApply processed data streams to Spark machine learning APIsWho this book is forData Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended. Nº de ref. del artículo: LU-9781789808810
Cantidad disponible: Más de 20 disponibles
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Big Data Processing with Apache Spark: Efficiently tackle large datasets and big data analysis with Spark and Python
Publicado por
Packt Publishing Limited, 2018
ISBN 10: 1789808812
ISBN 13: 9781789808810
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Big Data Processing with Apache Spark
Publicado por
Packt Publishing Limited, GB, 2018
ISBN 10: 1789808812
ISBN 13: 9781789808810
Nuevo
Paperback
Librería: Rarewaves.com UK, London, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. No need to spend hours ploughing through endless data - let Spark, one of the fastest big data processing engines available, do the hard work for you.Key FeaturesGet up and running with Apache Spark and PythonIntegrate Spark with AWS for real-time analyticsApply processed data streams to machine learning APIs of Apache SparkBook DescriptionProcessing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption.By the end of this book, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects.What you will learnWrite your own Python programs that can interact with SparkImplement data stream consumption using Apache SparkRecognize common operations in Spark to process known data streamsIntegrate Spark streaming with Amazon Web Services (AWS)Create a collaborative filtering model with the movielens datasetApply processed data streams to Spark machine learning APIsWho this book is forData Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended. Nº de ref. del artículo: LU-9781789808810
Cantidad disponible: Más de 20 disponibles
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Big Data Processing with Apache Spark
Publicado por
Packt Publishing Limited, GB, 2018
ISBN 10: 1789808812
ISBN 13: 9781789808810
Nuevo
Paperback
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: New. No need to spend hours ploughing through endless data - let Spark, one of the fastest big data processing engines available, do the hard work for you.Key FeaturesGet up and running with Apache Spark and PythonIntegrate Spark with AWS for real-time analyticsApply processed data streams to machine learning APIs of Apache SparkBook DescriptionProcessing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streaming API, machine learning extension, and structured streaming.You'll begin by learning data processing fundamentals using Resilient Distributed Datasets (RDDs), SQL, Datasets, and Dataframes APIs. After grasping these fundamentals, you'll move on to using Spark Streaming APIs to consume data in real time from TCP sockets, and integrate Amazon Web Services (AWS) for stream consumption.By the end of this book, you'll not only have understood how to use machine learning extensions and structured streams but you'll also be able to apply Spark in your own upcoming big data projects.What you will learnWrite your own Python programs that can interact with SparkImplement data stream consumption using Apache SparkRecognize common operations in Spark to process known data streamsIntegrate Spark streaming with Amazon Web Services (AWS)Create a collaborative filtering model with the movielens datasetApply processed data streams to Spark machine learning APIsWho this book is forData Processing with Apache Spark is for you if you are a software engineer, architect, or IT professional who wants to explore distributed systems and big data analytics. Although you don't need any knowledge of Spark, prior experience of working with Python is recommended. Nº de ref. del artículo: LU-9781789808810
Cantidad disponible: Más de 20 disponibles
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Big Data Processing with Apache Spark: Efficiently tackle large datasets and big data analysis with Spark and Python
Publicado por
Packt Publishing 2018-10-31, 2018
ISBN 10: 1789808812
ISBN 13: 9781789808810
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