Java 9 Functional Data Processing
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Java 9 Functional Data Processing

Learn Data Processing with Java 9
4.0 (1 rating)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
3 students enrolled
Created by Packt Publishing
Last updated 7/2017
English
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Current price: $10 Original price: $125 Discount: 92% off
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Includes:
  • 2 hours on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Add CSV files and maven dependency
  • Work with data structures
  • Create functional programming
  • Find data using sets
  • Parsing CSV files with Apache
View Curriculum
Requirements
  • Should have some prior experience of programming in Java.
Description

The course will introduce viewers to the different data structures available in Java 9, and how they can leverage them to process and manipulate data. We will start with a simple CSV data file, containing information about songs played on a music streaming service.

The Videos will teach you about the data file that will be parsed using the Apache Commons framework, giving the audience exposure to using Maven for dependency management, and we will model the contents of the file using our previous song streaming example. The audience will then learn how to use loops to process, filter, and mutate the data in the file. As a bonus, at the end of the product we will learn how to simplify our processing logic using functional programming.

About The Author

Andrei Ruse, our Author is currently working with Colibri Ltd and has been working as a software developer in the financial services industry for over 3 years, and has over 6 years of experience with Java as a main programming language - both academically and professionally.

Prior to his current role in a FinTech startup in London, he spent three years working for one of the world's largest investment banks, having joined it straight after graduating from Manchester University with a degree in Computer Science

Colibri is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help their clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas like Big Data, Data Science, Machine Learning, and Cloud Computing. Over the past few years they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the world's most popular soft drinks companies, helping each of them to better make sense of their data, and process it in more intelligent ways.

The company lives by their moto: Data -> Intelligence -> Action.


Who is the target audience?
  • Developers with some prior experience of programming in Java, looking to learn how to effectively leverage its data structures for data processing.
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Curriculum For This Course
14 Lectures
01:48:06
+
Loading CSV files and Maven Dependency Management
4 Lectures 34:07

This video provides an overview of the entire course.                    

Preview 01:45

 What is Maven and how do I manage my project’s external libraries?           

Introduction to Maven, Dependency Management, and the Apache Commons Library
09:15

 What is the CSV file format, and how do we use it within Java?           

Parsing Simple CSV Files with Apache Commons
09:24

 How do CSV libraries such as Apache Maven handle files, both when reading and writing data?           

Creating an Object Oriented Representation of a CSV Data File Using Song Inform
13:43
+
Types of Data Structure
5 Lectures 38:13

Which are the data structures provided in Java that can store collections of objects? What are the properties of these data structures?       

Preview 07:52

Which are the advanced properties of Lists, and how can they be used in code?            

Creating a List of Songs from Our CSV File
07:53

Which are the advanced properties of Sets, and how can they be used in code?            

Finding a Unique List of Artists Using Sets
05:36

Which are the properties of Maps, and how can they provide better functionality than Lists and Sets?            

Creating a Map of Artists and Songs and Demonstration
08:00

How can we combine all available data structures to answer complex user queries regarding our music streaming application?            

Finding the Top Five Most Popular Artists
08:52
+
Functional Programming
5 Lectures 35:46

What are streams and how are they different than collections, and how can they improve our code base?           

Preview 07:22

What is the map() function on the Stream interface, and how do we use it in the context of our application?            

Modifying All Songs to Include a Processed Time Field Using a Functional Map
08:25

What is the filter() function on the Stream interface, and how do we use it in the context of our application?            

Searching Songs to Find Songs Using a Functional Filter
07:00

How can we aggregate elements in a stream, and what are the available operations?            

Counting the Number of Songs Using Filters and Aggregates
06:40

What other methods are available on the Stream interface, and how do we combine multiple such methods into a chained call?            

Additional Functional Operators
06:19
About the Instructor
Packt Publishing
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