Big Data Analytics with Hadoop 3: Build highly effective analytics solutions to gain valuable insight into your big data
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Packt Publishing
Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples.
Once you have taken a tour of Hadoop 3s latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with the open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you get acquainted with all this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions on the cloud and an end-to-end pipeline to perform big data analysis using practical use cases.
By the end of this book, you will be well-versed with the analytical capabilities of the Hadoop ecosystem. You will be able to build powerful solutions to perform big data analytics and get insight effortlessly.
- Explore the new features of Hadoop 3 along with HDFS, YARN, and MapReduce
- Get well-versed with the analytical capabilities of Hadoop ecosystem using practical examples
- Integrate Hadoop with R and Python for more efficient big data processing
- Learn to use Hadoop with Apache Spark and Apache Flink for real-time data analytics
- Set up a Hadoop cluster on AWS cloud
- Perform big data analytics on AWS using Elastic Map Reduce
Big Data Analytics with Hadoop 3 is for you if you are looking to build high-performance analytics solutions for your enterprise or business using Hadoop 3s powerful features, or youre new to big data analytics. A basic understanding of the Java programming language is required.
- Introduction to Hadoop
- Overview of Big Data Analytics
- Big Data Processing with MapReduce
- Scientific Computing and Big Data Analysis with Python and Hadoop
- Statistical Big Data Computing with R and Hadoop
- Batch analytics with Apache Spark
- Real time analytics with Apache Spark
- Batch analytics with Apache Flink
- Stream Processing with Apache Flink
- Visualizing Big Data
- Introduction to Cloud Computing
- Using Amazon Web Services
