Scala Data Analysis Cookbook
eBook - ePub

Scala Data Analysis Cookbook

  1. 254 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Scala Data Analysis Cookbook

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About This Book

Navigate the world of data analysis, visualization, and machine learning with over 100 hands-on Scala recipesAbout This Bookā€¢ Implement Scala in your data analysis using features from Spark, Breeze, and Zeppelinā€¢ Scale up your data anlytics infrastructure with practical recipes for Scala machine learningā€¢ Recipes for every stage of the data analysis process, from reading and collecting data to distributed analyticsWho This Book Is ForThis book shows data scientists and analysts how to leverage their existing knowledge of Scala for quality and scalable data analysis.What You Will Learnā€¢ Familiarize and set up the Breeze and Spark libraries and use data structuresā€¢ Import data from a host of possible sources and create dataframes from CSVā€¢ Clean, validate and transform data using Scala to pre-process numerical and string dataā€¢ Integrate quintessential machine learning algorithms using Scala stackā€¢ Bundle and scale up Spark jobs by deploying them into a variety of cluster managersā€¢ Run streaming and graph analytics in Spark to visualize data, enabling exploratory analysisIn DetailThis book will introduce you to the most popular Scala tools, libraries, and frameworks through practical recipes around loading, manipulating, and preparing your data. It will also help you explore and make sense of your data using stunning and insightfulvisualizations, and machine learning toolkits.Starting with introductory recipes on utilizing the Breeze and Spark libraries, get to grips withhow to import data from a host of possible sources and how to pre-process numerical, string, and date data. Next, you'll get an understanding of concepts that will help you visualize data using the Apache Zeppelin and Bokeh bindings in Scala, enabling exploratory data analysis. iscover how to program quintessential machine learning algorithms using Spark ML library. Work through steps to scale your machine learning models and deploy them into a standalone cluster, EC2, YARN, and Mesos. Finally dip into the powerful options presented by Spark Streaming, and machine learning for streaming data, as well as utilizing Spark GraphX.Style and approachThis book contains a rich set of recipes that covers the full spectrum of interesting data analysis tasks and will help you revolutionize your data analysis skills using Scala and Spark.

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Yes, you can access Scala Data Analysis Cookbook by Arun Manivannan in PDF and/or ePUB format, as well as other popular books in Computer Science & Object Oriented Programming. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Packt Publishing
Year
2015
ISBN
9781784394998
Edition
1
Topic
Computer Science
Subtopic
Object Oriented Programming
Index
Computer Science

Scala Data Analysis Cookbook

Table of Contents

Scala Data Analysis Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why Subscribe?
Free Access for Packt account holders
Preface
Apache Flink
Scalding
Saddle
Spire
Akka
Accord
What this book covers
What you need for this book
Who this book is for
Sections
Getting ready
How to do itā€¦
How it worksā€¦
There's moreā€¦
See also
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Getting Started with Breeze
Introduction
Getting Breeze ā€“ the linear algebra library
How to do it...
There's more...
The org.scalanlp.breeze dependency
The org.scalanlp.breeze-natives package
Working with vectors
Getting ready
How to do it...
Creating vectors
Constructing a vector from values
Creating a zero vector
Creating a vector out of a function
Creating a vector of linearly spaced values
Creating a vector with values in a specific range
Creating an entire vector with a single value
Slicing a sub-vector from a bigger vector
Creating a Breeze Vector from a Scala Vector
Vector arithmetic
Scalar operations
Calculating the dot product of two vectors
Creating a new vector by adding two vectors together
Appending vectors and converting a vector of one type to another
Concatenating two vectors
Converting a vector of Int to a vector of Double
Computing basic statistics
Mean and variance
Standard deviation
Find the largest value in a vector
Finding the sum, square root and log of all the values in the vector
The Sqrt function
The Log function
Working with matrices
How to do it...
Creating matrices
Creating a matrix from values
Creating a zero matrix
Creating a matrix out of a function
Creating an identity matrix
Creating a matrix from random numbers
Creating from a Scala collection
Matrix arithmetic
Addition
Multiplication
Appending and conversion
Concatenating matrices ā€“ vertically
Concatenating matrices ā€“ horizontally
Converting a matrix of Int to a matrix of Double
Data manipulation operations
Getting column vectors out of the matrix
Getting row vectors out of the matrix
Getting values inside the matrix
Getting the inverse and transpose of a matrix
Computing basic statistics
Mean and variance
Standard deviation
Finding the largest value in a matrix
Finding the sum, square root and log of all the values in the matrix
Sqrt
Log
Calculating the eigenvectors and eigenvalues of a matrix
How it works...
Vectors and matrices with randomly distributed values
How it works...
Creating vectors with uniformly distributed random values
Creating vectors with normally distributed random values
Creating vectors with random values that have a Poisson distribution
Creating a matrix with uniformly random values
Creating a matrix with normally distributed random values
Creating a matrix with random values that has a Poisson distribution
Reading and writing CSV files
How it works...
2. Getting Started with Apache Spark DataFrames
Introduction
Getting Apache Spark
How to do it...
Creating a DataFrame from CSV
How to do it...
How it works...
There's moreā€¦
Manipulating DataFrames
How to do it...
Printing the schema of the DataFrame
Sampling the data in the DataFrame
Selecting DataFrame columns
Filtering data by condition
Sorting data in the frame
Renaming columns
Treating the DataFrame as a relational table
Joining two DataFrames
Inner join
Right outer join
Left outer join
Saving the DataFrame as a file
Creating a DataFrame from Scala case classes
How to do it...
How it works...
3. Loading and Preparing Data ā€“ DataFrame
Introduction
Loading more than 22 features into classes
How to do it...
How it works...
There's moreā€¦
Loading JSON into DataFrames
How to do itā€¦
Reading a JSON file using SQLContext.jsonFile
Reading a text file and converting it to JSON RDD
Explicitly specifying your schema
There's moreā€¦
Storing data as Parquet files
How to do itā€¦
Load a simple CSV file, convert it to case classes, and create a DataFrame from it
Save it as a Parquet file
Install Parquet tools
Using the tools to inspect the Parquet file
Enable compression for the Parquet file
Using the Avro data model in Parquet
How to do itā€¦
Creation of the Avro model
Generation of Avro objects using the sbt-avro plugin
Constructing an RDD of our generated object from Students.csv
Saving RDD[StudentAvro] in a Parquet file
Reading the file back for verification
Using Parquet tools for verification
Loading from RDBMS
How to do itā€¦
Preparing data in Dataframes
How to do it...
4. Data Visualization
Introduction
Visualizing using Zeppelin
How to do it...
Installing Zeppelin
Customizing Zeppelin's server and websocket port
Visualizing data on HDFS ā€“ parameterizing inputs
Running custom functions
Adding external dependencies t...

Table of contents

  1. Scala Data Analysis Cookbook