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Apache Spark 2: Data Processing and Real-Time Analytics
Apache Spark 2: Data Processing and Real-Time Analytics

Apache Spark 2: Data Processing and Real-Time Analytics: Master complex big data processing, stream analytics, and machine learning with Apache Spark

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Profile Icon Romeo Kienzler Profile Icon Shuen Mei Profile Icon Broderick Hall Profile Icon Meenakshi Rajendran Profile Icon Siamak Amirghodsi Profile Icon Sridhar Alla Profile Icon Md. Rezaul Karim +3 more Show less
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Course Dec 2018 616 pages 1st Edition
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Profile Icon Romeo Kienzler Profile Icon Shuen Mei Profile Icon Broderick Hall Profile Icon Meenakshi Rajendran Profile Icon Siamak Amirghodsi Profile Icon Sridhar Alla Profile Icon Md. Rezaul Karim +3 more Show less
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Course Dec 2018 616 pages 1st Edition

Key benefits

  • Master the art of real-time big data processing and machine learning
  • Explore a wide range of use-cases to analyze large data
  • Discover ways to optimize your work by using many features of Spark 2.x and Scala

Description

Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: • Mastering Apache Spark 2.x by Romeo Kienzler • Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla • Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook

Who is this book for?

If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.

What you will learn

  • Get to grips with all the features of Apache Spark 2.x
  • Perform highly optimized real-time big data processing
  • Use ML and DL techniques with Spark MLlib and third-party tools
  • Analyze structured and unstructured data using SparkSQL and GraphX
  • Understand tuning, debugging, and monitoring of big data applications
  • Build scalable and fault-tolerant streaming applications
  • Develop scalable recommendation engines

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Dec 21, 2018
Length: 616 pages
Edition : 1st
Language : English
ISBN-13 : 9781789959208
Category :
Languages :
Concepts :

Product Details

Publication date : Dec 21, 2018
Length: 616 pages
Edition : 1st
Language : English
ISBN-13 : 9781789959208
Category :
Languages :
Concepts :

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Table of Contents

16 Chapters
A First Taste and What's New in Apache Spark V2 Chevron down icon Chevron up icon
Apache Spark Streaming Chevron down icon Chevron up icon
Structured Streaming Chevron down icon Chevron up icon
Apache Spark MLlib Chevron down icon Chevron up icon
Apache SparkML Chevron down icon Chevron up icon
Apache SystemML Chevron down icon Chevron up icon
Apache Spark GraphX Chevron down icon Chevron up icon
Spark Tuning Chevron down icon Chevron up icon
Testing and Debugging Spark Chevron down icon Chevron up icon
Practical Machine Learning with Spark Using Scala Chevron down icon Chevron up icon
Spark's Three Data Musketeers for Machine Learning - Perfect Together Chevron down icon Chevron up icon
Common Recipes for Implementing a Robust Machine Learning System Chevron down icon Chevron up icon
Recommendation Engine that Scales with Spark Chevron down icon Chevron up icon
Unsupervised Clustering with Apache Spark 2.0 Chevron down icon Chevron up icon
Implementing Text Analytics with Spark 2.0 ML Library Chevron down icon Chevron up icon
Spark Streaming and Machine Learning Library Chevron down icon Chevron up icon
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