Book Image

Big Data Analytics with Hadoop 3

By : Sridhar Alla
Book Image

Big Data Analytics with Hadoop 3

By: Sridhar Alla

Overview of this book

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 3’s 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.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Packt Upsell
Scientific Computing and Big Data Analysis with Python and Hadoop

Using the Flink cluster UI

Using the Flink cluster UI, you can understand and monitor what's running in your cluster and dig deeply into various jobs and tasks. You can monitor the job statuses, cancel jobs, or debug any problems with the jobs. By looking at logs, you can also diagnose problems with your code, and fix them.

The following is a list of Completed Jobs:

You can drill down into any particular job to see more details about the job's execution:

Figure: Drilling down a particular job to see job's execution

You can look at the Timeline of the job to get more details:

Figure: Screenshot to see Timeline of a job

The following screenshot shows the Task Managers tab, showing all of the task managers. This helps you understand the number and status of the task managers:

You can also check the Logs, as shown in the following screenshot:

The Metrics tab gives you details of the memory and CPU resources:

Figure: Screenshot showing details of the memory and CPU resources in Metrics tab

You can also...