Book Image

Big Data Analytics

By : Venkat Ankam
Book Image

Big Data Analytics

By: Venkat Ankam

Overview of this book

Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data.
Table of Contents (18 chapters)
Big Data Analytics
About the Author
About the Reviewers


Web-based notebooks are really helpful because they provide rich visualizations and high developer productivity and make it easy to share with others. While there are many open source-based notebooks available, the most popular notebooks are Jupyter and Apache Zeppelin. The Jupyter Notebook is very mature, supports over 40 languages, and integrates with Spark and Hadoop to query interactively and visualize results. Apache Zeppelin is a web-based notebook that enables data-driven, interactive analytics with built-in visualizations. There are many similarities between Jupyter and Zeppelin, but Zeppelin is tightly integrated with Spark and Hadoop, and it is also possible to include multiple languages in the same notebook.

Hue 3.8 introduced Spark-based notebooks, which are inspired by IPython Notebooks that provide built-in visualizations. The Spark Notebook works on the Livy REST job server backend to provide Spark as a service to end users. The Livy job server exposes both batch and...