國立高雄大學圖資館 |

Language: English

Back

Beginning Apache Spark 3with DataFra...

Luu, Hien.

Beginning Apache Spark 3with DataFrame, Spark SQL, structured streaming, and spark machine learning library /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Beginning Apache Spark 3by Hien Luu.
Reminder of title:	with DataFrame, Spark SQL, structured streaming, and spark machine learning library /
Author:	Luu, Hien.
Published:	Berkeley, CA :Apress :2021.
Description:	1 online resource (xvii, 438 p.) :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Big data.
Online resource:	https://doi.org/10.1007/978-1-4842-7383-8
ISBN:	9781484273838$q(electronic bk.)

Beginning Apache Spark 3with DataFrame, Spark SQL, structured streaming, and spark machine learning library /
Luu, Hien.

Beginning Apache Spark 3with DataFrame, Spark SQL, structured streaming, and spark machine learning library /[electronic resource] :by Hien Luu. - Second edition. - Berkeley, CA :Apress :2021. - 1 online resource (xvii, 438 p.) :ill., digital ;24 cm.

Chapter 1: Introduction to Apache Spark -- Chapter 2: Working with Apache Spark -- Chapter 3: Spark SQL - Foundation -- Chapter 4: Spark SQL - Advance -- Chapter 5: Optimizing Apache Spark Applications -- Chapter 6: Structured Streaming - Foundation -- Chapter 7: Structured Streaming - Advanced -- Chapter 8: Machine Learning with Apache Spark -- Chapter 9: Managing the Machine Learning Lifecycle.

Take a journey toward discovering, learning, and using Apache Spark 3.0. In this book, you will gain expertise on the powerful and efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing data in batch and streaming; and the scalable machine learning algorithms and practical utilities to build machine learning applications. Beginning Apache Spark 3 begins by explaining different ways of interacting with Apache Spark, such as Spark Concepts and Architecture, and Spark Unified Stack. Next, it offers an overview of Spark SQL before moving on to its advanced features. It covers tips and techniques for dealing with performance issues, followed by an overview of the structured streaming processing engine. It concludes with a demonstration of how to develop machine learning applications using Spark MLlib and how to manage the machine learning development lifecycle. This book is packed with practical examples and code snippets to help you master concepts and features immediately after they are covered in each section. After reading this book, you will have the knowledge required to build your own big data pipelines, applications, and machine learning applications. You will: Master the Spark unified data analytics engine and its various components Work in tandem to provide a scalable, fault tolerant and performant data processing engine Leverage the user-friendly and flexible programming model to perform simple to complex data analytics using dataframe and Spark SQL Develop machine learning applications using Spark MLlib Manage the machine learning development lifecycle using MLflow.

ISBN: 9781484273838$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-7383-8doiSubjects--Uniform Titles:

Spark (Electronic resource : Apache Software Foundation)
Subjects--Topical Terms:

609582
Big data.

LC Class. No.: QA76.9.D3 / L88 2021

Dewey Class. No.: 005.7

Beginning Apache Spark 3with DataFrame, Spark SQL, structured streaming, and spark machine learning library /
LDR:03194nmm a2200337 a 4500 001 614936
003 DE-He213
005 20220124160535.0
006 m o d
007 cr nn 008maaau
008 220802s2021 cau s 0 eng d
020 $a 9781484273838$q(electronic bk.)
020 $a 9781484273821$q(paper)
024 7 $a 10.1007/978-1-4842-7383-8 $2 doi
035 $a 978-1-4842-7383-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D3 $b L88 2021
072 7 $a UN $2 bicssc
072 7 $a COM031000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.7 $2 23
090 $a QA76.9.D3 $b L975 2021
100 1 $a Luu, Hien. $3 822608
245 1 0 $a Beginning Apache Spark 3 $h [electronic resource] : $b with DataFrame, Spark SQL, structured streaming, and spark machine learning library / $c by Hien Luu.
250 $a Second edition.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2021.
300 $a 1 online resource (xvii, 438 p.) : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Introduction to Apache Spark -- Chapter 2: Working with Apache Spark -- Chapter 3: Spark SQL - Foundation -- Chapter 4: Spark SQL - Advance -- Chapter 5: Optimizing Apache Spark Applications -- Chapter 6: Structured Streaming - Foundation -- Chapter 7: Structured Streaming - Advanced -- Chapter 8: Machine Learning with Apache Spark -- Chapter 9: Managing the Machine Learning Lifecycle.
520 $a Take a journey toward discovering, learning, and using Apache Spark 3.0. In this book, you will gain expertise on the powerful and efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing data in batch and streaming; and the scalable machine learning algorithms and practical utilities to build machine learning applications. Beginning Apache Spark 3 begins by explaining different ways of interacting with Apache Spark, such as Spark Concepts and Architecture, and Spark Unified Stack. Next, it offers an overview of Spark SQL before moving on to its advanced features. It covers tips and techniques for dealing with performance issues, followed by an overview of the structured streaming processing engine. It concludes with a demonstration of how to develop machine learning applications using Spark MLlib and how to manage the machine learning development lifecycle. This book is packed with practical examples and code snippets to help you master concepts and features immediately after they are covered in each section. After reading this book, you will have the knowledge required to build your own big data pipelines, applications, and machine learning applications. You will: Master the Spark unified data analytics engine and its various components Work in tandem to provide a scalable, fault tolerant and performant data processing engine Leverage the user-friendly and flexible programming model to perform simple to complex data analytics using dataframe and Spark SQL Develop machine learning applications using Spark MLlib Manage the machine learning development lifecycle using MLflow.
630 0 0 $a Spark (Electronic resource : Apache Software Foundation) $3 750546
650 0 $a Big data. $3 609582
650 0 $a Distributed databases. $3 184457
650 0 $a Open source software. $3 200208
650 0 $a Machine learning. $3 188639
650 1 4 $a Data Science. $3 913495
650 2 4 $a Machine Learning. $3 833608
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-7383-8
950 $a Professional and Applied Computing (SpringerNature-12059)