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Simplify Big Data Analytics with Amazon EMR

You're reading from   Simplify Big Data Analytics with Amazon EMR A beginner's guide to learning and implementing Amazon EMR for building data analytics solutions

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Product type Paperback
Published in Mar 2022
Publisher Packt
ISBN-13 9781801071079
Length 430 pages
Edition 1st Edition
Concepts
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Author (1):
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Sakti Mishra Sakti Mishra
Author Profile Icon Sakti Mishra
Sakti Mishra
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Table of Contents (19) Chapters Close

Preface 1. Section 1: Overview, Architecture, Big Data Applications, and Common Use Cases of Amazon EMR
2. Chapter 1: An Overview of Amazon EMR FREE CHAPTER 3. Chapter 2: Exploring the Architecture and Deployment Options 4. Chapter 3: Common Use Cases and Architecture Patterns 5. Chapter 4: Big Data Applications and Notebooks Available in Amazon EMR 6. Section 2: Configuration, Scaling, Data Security, and Governance
7. Chapter 5: Setting Up and Configuring EMR Clusters 8. Chapter 6: Monitoring, Scaling, and High Availability 9. Chapter 7: Understanding Security in Amazon EMR 10. Chapter 8: Understanding Data Governance in Amazon EMR 11. Section 3: Implementing Common Use Cases and Best Practices
12. Chapter 9: Implementing Batch ETL Pipeline with Amazon EMR and Apache Spark 13. Chapter 10: Implementing Real-Time Streaming with Amazon EMR and Spark Streaming 14. Chapter 11: Implementing UPSERT on S3 Data Lake with Apache Spark and Apache Hudi 15. Chapter 12: Orchestrating Amazon EMR Jobs with AWS Step Functions and Apache Airflow/MWAA 16. Chapter 13: Migrating On-Premises Hadoop Workloads to Amazon EMR 17. Chapter 14: Best Practices and Cost-Optimization Techniques 18. Other Books You May Enjoy

Understanding clusters and nodes

The primary construct or component of Amazon EMR is the cluster, and the cluster is a collection of Amazon EC2 instances, which are called nodes. Each node within the cluster has a type, depending on the role it plays or the job it does in the cluster. Based on the node type, respective Hadoop libraries are installed and configured on that instance.

The following are the node types available in EMR:

  • Master node: Master nodes are responsible for managing cluster instances, monitoring health, coordinating job execution, tracking the status of tasks, and so on. This is a must-have node type when you create a cluster and you can have a single node cluster with just a master node in it.
  • Core node: This node type is responsible for storing data in the HDFS on your cluster and runs Hadoop application services such as Hive, Pig, HBase, and Hue. If you have a multi-node cluster, then you should have at least one core node.
  • Task node: This...
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