Preface
JVM has become a clear winner in the race between different methods of scalable data analysis. The power of JVM, strong typing, simplicity of code, composability, and availability of highly abstracted distributed and machine learning frameworks make Scala a clear contender for the top position in large-scale data analysis. Thanks to its dynamic-looking, yet static type system, scientists and programmers coming from Python backgrounds feel at ease with Scala.
This book aims to provide easy-to-use recipes in Apache Spark, a massively scalable distributed computation framework, and Breeze, a linear algebra library on which Spark's machine learning toolkit is built. The book will also help you explore data using interactive visualizations in Apache Zeppelin.
Other than the handful of frameworks and libraries that we will see in this book, there's a host of other popular data analysis libraries and frameworks that are available for Scala. They are by no means lesser beasts, and they could actually fit our use cases well. Unfortunately, they aren't covered as part of this book.
Apache Flink
Apache Flink (http://flink.apache.org/), just like Spark, has first-class support for Scala and provides features that are strikingly similar to Spark. Real-time streaming (unlike Spark's mini-batch DStreams) is its distinctive feature. Flink also provides a machine learning and a graph processing library and runs standalone as well as on the YARN cluster.
Scalding
Scalding (https://github.com/twitter/scalding) needs no introduction—Scala's idiomatic approach to writing Hadoop MR jobs.
Saddle
Saddle (https://saddle.github.io/) is the "pandas" (http://pandas.pydata.org/) of Scala, with support for vectors, matrices, and DataFrames.
Spire
Spire (https://github.com/non/spire) has a powerful set of advanced numerical types that are not available in the default Scala library. It aims to be fast and precise in its numerical computations.
Akka
Akka (http://akka.io) is an actor-based concurrency framework that has actors as its foundation and unit of work. Actors are fault tolerant and distributed.
Accord
Accord (https://github.com/wix/accord) is simple, yet powerful, validation library in Scala.
What this book covers
Chapter 1, Getting Started with Breeze, serves as an introduction to the Breeze linear algebra library's API.
Chapter 2, Getting Started with Apache Spark DataFrames, introduces powerful, yet intuitive and relational-table-like, data abstraction.
Chapter 3, Loading and Preparing Data – DataFrame, showcases the loading of datasets into Spark DataFrames from a variety of sources, while also introducing the Parquet serialization format.
Chapter 4, Data Visualization, introduces Apache Zeppelin for interactive data visualization using Spark SQL and Spark UDF functions. We also briefly discuss Bokeh-Scala, which is a Scala port of Bokeh (a highly customizable visualization library).
Chapter 5, Learning from Data, focuses on machine learning using Spark MLlib.
Chapter 6, Scaling Up, walks through various deployment alternatives for Spark applications: standalone, YARN, and Mesos.
Chapter 7, Going Further, briefly introduces Spark Streaming and GraphX.
What you need for this book
The most important installation that your machine needs is the Java Development Kit (JDK 1.7), which can be downloaded from http://www.oracle.com/technetwork/java/javase/downloads/jdk7-downloads-1880260.html.
To run most of the recipes in this book, all you need is SBT. The installation instructions for your favorite operating system are available at http://www.scala-sbt.org/release/tutorial/Setup.html.
There are a few other libraries that we will be using throughout the book, all of which will be imported through SBT. If there is any installation required (for example, HDFS) to run a recipe, the installation URL or the steps themselves will be mentioned in the respective recipe.
Who this book is for
Engineers and scientists who are familiar with Scala and would like to exploit the Spark ecosystem for big data analysis will benefit most from this book.
Sections
In this book, you will find several headings that appear frequently (Getting ready, How to do it…, How it works…, There's more…, and See also).
To give clear instructions on how to complete a recipe, we use these sections as follows:
Getting ready
This section tells you what to expect in the recipe, and describes how to set up any software or any preliminary settings required for the recipe.
How to do it…
This section contains the steps required to follow the recipe.
How it works…
This section usually consists of a detailed explanation of what happened in the previous section.
There's more…
This section consists of additional information about the recipe in order to make the reader more knowledgeable about the recipe.
See also
This section provides helpful links to other useful information for the recipe.
Conventions
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We can include other contexts through the use of the include
directive."
A block of code is set as follows:
organization := "com.packt" name := "chapter1-breeze" scalaVersion := "2.10.4" libraryDependencies ++= Seq( "org.scalanlp" %% "breeze" % "0.11.2", //Optional - the 'why' is explained in the How it works section "org.scalanlp" %% "breeze-natives" % "0.11.2" )
Any command-line input or output is written as follows:
sudo apt-get install libatlas3-base libopenblas-base sudo update-alternatives --config libblas.so.3 sudo update-alternatives --config liblapack.so.3
New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "Now, if we wish to share this chart with someone or link it to an external website, we can do so by clicking on the gear icon in this paragraph and then clicking on Link this paragraph."
Note
Warnings or important notes appear in a box like this.
Tip
Tips and tricks appear like this.
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