Though the spark.ml package uses the dataframe for ML workflows, depending on the use case one might need to extract data from raw dataframe or transform the dataframe in a format as required by the ML algorithms or at times one might just need a few selected parameters as feature vectors. All these different types of operations require usage of specially developed APIs that can be clubbed into the following categories.
-
Book Overview & Buying
-
Table Of Contents
-
Feedback & Rating
Apache Spark 2.x for Java Developers
By :
Apache Spark 2.x for Java Developers
By:
Overview of this book
Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing. While Spark is built on Scala, the Spark Java API exposes all the Spark features available in the Scala version for Java developers. This book will show you how you can implement various functionalities of the Apache Spark framework in Java, without stepping out of your comfort zone.
The book starts with an introduction to the Apache Spark 2.x ecosystem, followed by explaining how to install and configure Spark, and refreshes the Java concepts that will be useful to you when consuming Apache Spark's APIs. You will explore RDD and its associated common Action and Transformation Java APIs, set up a production-like clustered environment, and work with Spark SQL. Moving on, you will perform near-real-time processing with Spark streaming, Machine Learning analytics with Spark MLlib, and graph processing with GraphX, all using various Java packages.
By the end of the book, you will have a solid foundation in implementing components in the Spark framework in Java to build fast, real-time applications.
Table of Contents (12 chapters)
Preface
In Progress
| 0 / 7 sections completed |
0%
Free Chapter
Introduction to Spark
In Progress
| 0 / 9 sections completed |
0%
Revisiting Java
In Progress
| 0 / 10 sections completed |
0%
Let Us Spark
In Progress
| 0 / 9 sections completed |
0%
Understanding the Spark Programming Model
In Progress
| 0 / 6 sections completed |
0%
Working with Data and Storage
In Progress
| 0 / 5 sections completed |
0%
Spark on Cluster
In Progress
| 0 / 5 sections completed |
0%
Spark Programming Model - Advanced
In Progress
| 0 / 7 sections completed |
0%
Working with Spark SQL
In Progress
| 0 / 6 sections completed |
0%
Near Real-Time Processing with Spark Streaming
In Progress
| 0 / 9 sections completed |
0%
Machine Learning Analytics with Spark MLlib
In Progress
| 0 / 6 sections completed |
0%
Learning Spark GraphX
In Progress
| 0 / 7 sections completed |
0%
Customer Reviews
