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Hands-on Guide to Apache Spark 3, Antol?nez Garc?a


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Цена: 47810T
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Автор: Antol?nez Garc?a   (Гарсия Антоленес)
Название:  Hands-on Guide to Apache Spark 3   (Гарсия Антоленес: Практическое руководство по Апаче Спарк 3)
Издательство: Springer
Классификация:
ISBN: 1484293797
ISBN-13(EAN): 9781484293799
Обложка/Формат: Soft cover
Страницы: 403
Дата издания: 20.06.2023
Язык: English
Рейтинг:
Поставляется из: Германии
Описание: This book explains how to scale Apache Spark 3 to handle massive amounts of data, either via batch or streaming processing. It covers how to use Spark’s structured APIs to perform complex data transformations and analyses you can use to implement end-to-end analytics workflows. This book covers Spark 3s new features, theoretical foundations, and application architecture. The first section introduces the Apache Spark ecosystem as a unified engine for large scale data analytics, and shows you how to run and fine-tune your first application in Spark. The second section centers on batch processing suited to end-of-cycle processing, and data ingestion through files and databases. It explains Spark DataFrame API as well as structured and unstructured data with Apache Spark. The last section deals with scalable, high-throughput, fault-tolerant streaming processing workloads to process real-time data. Here youll learn about Apache Spark Streaming’s execution model, the architecture of Spark Streaming, monitoring, reporting, and recovering Spark streaming. A full chapter is devoted to future directions for Spark Streaming. With real-world use cases, code snippets, and notebooks hosted on GitHub, this book will give you an understanding of large-scale data analysis concepts--and help you put them to use. Upon completing this book, you will have the knowledge and skills to seamlessly implement large-scale batch and streaming workloads to analyze real-time data streams with Apache Spark. What You Will Learn * Master the concepts of Spark clusters and batch data processing * Understand data ingestion, transformation, and data storage * Gain insight into essential stream processing concepts and different streaming architectures * Implement streaming jobs and applications with Spark Streaming Who This Book Is For Data engineers, data analysts, machine learning engineers, Python and R programmers
Дополнительное описание: Part 1: Apache Spark Batch Data Processing.- Chapter 1: Introduction to Apache Spark for Large-Scale Data Analytics.- Chapter 2: Getting Started with Apache Spark.- Chapter 3: Spark Low Level API.- Chapter 4: Spark High-Level APIs.- Chapter 5: Spark Datas


Graph Algorithms: Practical Examples in Apache Spark and Neo4j

Автор: Needham Mark, Hodler Amy E.
Название: Graph Algorithms: Practical Examples in Apache Spark and Neo4j
ISBN: 1492047686 ISBN-13(EAN): 9781492047681
Издательство: Wiley
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Цена: 53350 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they`re used for building dynamic network models or forecasting real-world behavior.

Beginning Apache Spark 3: With Dataframe, Spark Sql, Structured Streaming, and Spark Machine Learning Library

Автор: Luu Hien
Название: Beginning Apache Spark 3: With Dataframe, Spark Sql, Structured Streaming, and Spark Machine Learning Library
ISBN: 1484273826 ISBN-13(EAN): 9781484273821
Издательство: Springer
Рейтинг:
Цена: 47810 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1: Introduction to Apache Spark
Chapter Goal: Provide an overview of Apache SparkNo of pages 15Sub -Topics1. Overview & history2. Spark concepts & architecture3. Spark Unified Stack4. Apache Spark applications
Chapter 2: Working with Apache SparkChapter Goal: Provide details about different ways of interacting with Apache SparkNo of pages: 35Sub - Topics 1. Downloading and Installing Apache Spark2. Exploring Apache Spark using Spark shells3. Exploring Apache Spark using Databricks4. Exploring Apache Spark source code
Chapter 3: Spark SQL - FoundationChapter Goal: Provide an overview to Spark SQL componentNo of pages: 60Sub - Topics 1. Overview & architecture2. Introduction to DataFrames Structured APIs3. Reading & writing data with Spark SQL data sources4. Introduction to datasets
Chapter 4: Spark SQL - AdvanceChapter Goal: Go over the advanced features in Spark SQLNo of pages: 50Sub - Topics: 1. Working with aggregations2. Joining data 3. Working with analytics functions4. Explore Spark SQL catalyst optimizer
Chapter 5: Optimizing Apache Spark ApplicationsChapter Goal: Go over tips and techniques for dealing with performance issues No of pages: 30Sub - Topics: 1. Common performance issues2. Speed up performance by leveraging in-memory computation3. Understand the different support joins in Spark4. Leverage Spark UI to diagnose performance issue
Chapter 6: Structured Streaming - FoundationChapter Goal: Overview of Structured Streaming processing engineNo of pages: 50Sub - Topics: 1. General streaming processing concepts2. Structured Streaming programming model3. Working with streaming data sources and sinks4. Understanding output modes and triggers
Chapter 7: Structured Streaming - AdvancedChapter Goal: Cover complex issues in streaming processingNo of pages: 40Sub - Topics: 1. Streaming processing with event time2. Stateful streaming processing3. Handling duplicate data4. Monitoring streaming processing applications
Chapter 8: Machine Learning with Apache SparkChapter Goal: How to developing Machine Learning applications using Spark MLlibNo of pages: 60Sub - Topics: 1. Machine learning overview2. Taking a tour of supported machine learning algorithms3. Building machine learning pipelines4. Machine learning tasks in action5. Parameters tuning
Chapter 9: Machine Learning Application Development w/ MLflowChapter Goal: Using MLflow to manage the Machine Learning development lifecycle No of pages: 25Sub - Topics: 1. Overview of MLflow2. Tracking machine learning development experiments3. Managing & deploying machine learning models4. Leveraging Spark for batch modeling predictions

Apache Mahout Essentials

Автор: Withanawasam Jayani
Название: Apache Mahout Essentials
ISBN: 1783554991 ISBN-13(EAN): 9781783554997
Издательство: Неизвестно
Рейтинг:
Цена: 29690 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Apache Oozie Essentials

Автор: Singh Jagat Jasjit
Название: Apache Oozie Essentials
ISBN: 1785880381 ISBN-13(EAN): 9781785880384
Издательство: Неизвестно
Рейтинг:
Цена: 42890 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Practical Graph Analytics with Apache Giraph

Автор: Roman Shaposhnik; Claudio Martella; Dionysios Logo
Название: Practical Graph Analytics with Apache Giraph
ISBN: 1484212525 ISBN-13(EAN): 9781484212523
Издательство: Springer
Рейтинг:
Цена: 33090 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation’s Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points. Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities. Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.

Apache HBase Primer

Автор: Vohra
Название: Apache HBase Primer
ISBN: 148422423X ISBN-13(EAN): 9781484224236
Издательство: Springer
Рейтинг:
Цена: 14710 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Learn the fundamental foundations and concepts of the Apache HBase (NoSQL) open source database. It covers the HBase data model, architecture, schema design, API, and administration.Apache HBase is the database for the Apache Hadoop framework. HBase is a column family based NoSQL database that provides a flexible schema model.
What You'll Learn
Work with the core concepts of HBaseDiscover the HBase data model, schema design, and architectureUse the HBase API and administration
Who This Book Is For
Apache HBase (NoSQL) database users, designers, developers, and admins.

Large-Scale Graph Processing Using Apache Giraph

Автор: Sherif Sakr; Faisal Moeen Orakzai; Ibrahim Abdelaz
Название: Large-Scale Graph Processing Using Apache Giraph
ISBN: 3319474308 ISBN-13(EAN): 9783319474304
Издательство: Springer
Рейтинг:
Цена: 33090 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data.

Large-Scale Graph Processing Using Apache Giraph

Автор: Sakr Sherif, Orakzai Faisal Moeen, Abdelaziz Ibrahim
Название: Large-Scale Graph Processing Using Apache Giraph
ISBN: 3319837354 ISBN-13(EAN): 9783319837352
Издательство: Springer
Рейтинг:
Цена: 40450 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power of big data processing to graph data.

Apache Mahout Clustering Designs

Автор: Gupta Ashish
Название: Apache Mahout Clustering Designs
ISBN: 1783284439 ISBN-13(EAN): 9781783284436
Издательство: Неизвестно
Рейтинг:
Цена: 42890 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Apache Spark Deep Learning Cookbook

Автор: Sherif Ahmed, Ravindra Amrith
Название: Apache Spark Deep Learning Cookbook
ISBN: 1788474228 ISBN-13(EAN): 9781788474221
Издательство: Неизвестно
Рейтинг:
Цена: 60490 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Apache Spark Deep Learning Cookbook presents useful tips and tricks to overcome any problem related to building efficient distributed deep learning applications on Apache Spark. With the help of this book, you will leverage powerful deep learning libraries such as TensorFlow to develop your models and ensure their optimum performance.

Machine Learning with Apache Spark Quick Start Guide

Автор: Quddus Jillur
Название: Machine Learning with Apache Spark Quick Start Guide
ISBN: 1789346568 ISBN-13(EAN): 9781789346565
Издательство: Неизвестно
Рейтинг:
Цена: 40480 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Machine Learning with Apache Spark provides a hands-on introduction to Big Data and Advanced Analytics. In a world driven by mass data creation and consumption, this book combines the latest scalable technologies with advanced analytical algorithms using real-world use-cases in order to derive actionable insights from Big Data in real-time.

Hands-On Big Data Analytics with PySpark

Автор: Digital Colibri, Lai Rudy, Potaczek Bartlomiej
Название: Hands-On Big Data Analytics with PySpark
ISBN: 183864413X ISBN-13(EAN): 9781838644130
Издательство: Неизвестно
Рейтинг:
Цена: 32640 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, you`ll learn to implement some practical and proven techniques to improve aspects of programming and administration in Apache Spark. Techniques are demonstrated using practical examples and best practices. You will also learn how to use Spark and its Python API to create performant analytics with large-scale data.


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