Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Mastering Spark for Data Science
  • Table Of Contents Toc
  • Feedback & Rating feedback
Mastering Spark for Data Science

Mastering Spark for Data Science

By : Bifet, Morgan, Amend, Hallett, George
4 (2)
close
close
Mastering Spark for Data Science

Mastering Spark for Data Science

4 (2)
By: Bifet, Morgan, Amend, Hallett, George

Overview of this book

Data science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries. In order to operate at this level you need to build data science solutions of substance –solutions that solve real problems. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs. This book deep dives into using Spark to deliver production-grade data science solutions. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more. You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.
Table of Contents (15 chapters)
close
close

Summary

In this chapter, we have concluded our journey by discussing aspects of distributed computing performance, and what to exploit when writing your own scalable analytics. Hopefully, you've come away with a sense of some of the challenges involved, and have a better understanding of how Spark works under the covers.

Apache Spark is a constantly evolving framework and new features and improvements are being added every day. No doubt it will become increasingly easier to use as continuous tweaks and refinements are intelligently applied into the framework, automating much of what must be done manually today.

In terms of what's next, who knows what's round the corner? But with Spark beating the competition yet again to win the 2016 CloudSort Benchmark (http://sortbenchmark.org/) and new versions set to be released every four months, one thing is for sure, it's going to be fast-paced. And hopefully, with the solid principles and methodical guidelines that you've...

Visually different images
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Mastering Spark for Data Science
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon