Book Image

Simplify Big Data Analytics with Amazon EMR

By : Sakti Mishra
Book Image

Simplify Big Data Analytics with Amazon EMR

By: Sakti Mishra

Overview of this book

Amazon EMR, formerly Amazon Elastic MapReduce, provides a managed Hadoop cluster in Amazon Web Services (AWS) that you can use to implement batch or streaming data pipelines. By gaining expertise in Amazon EMR, you can design and implement data analytics pipelines with persistent or transient EMR clusters in AWS. This book is a practical guide to Amazon EMR for building data pipelines. You'll start by understanding the Amazon EMR architecture, cluster nodes, features, and deployment options, along with their pricing. Next, the book covers the various big data applications that EMR supports. You'll then focus on the advanced configuration of EMR applications, hardware, networking, security, troubleshooting, logging, and the different SDKs and APIs it provides. Later chapters will show you how to implement common Amazon EMR use cases, including batch ETL with Spark, real-time streaming with Spark Streaming, and handling UPSERT in S3 Data Lake with Apache Hudi. Finally, you'll orchestrate your EMR jobs and strategize on-premises Hadoop cluster migration to EMR. In addition to this, you'll explore best practices and cost optimization techniques while implementing your data analytics pipeline in EMR. By the end of this book, you'll be able to build and deploy Hadoop- or Spark-based apps on Amazon EMR and also migrate your existing on-premises Hadoop workloads to AWS.
Table of Contents (19 chapters)
1
Section 1: Overview, Architecture, Big Data Applications, and Common Use Cases of Amazon EMR
6
Section 2: Configuration, Scaling, Data Security, and Governance
11
Section 3: Implementing Common Use Cases and Best Practices

Security best practices

Security is one of the important aspects when you move to the AWS cloud. It includes authentication, authorization on cluster resources, protecting data at rest and in transit, and finally, protecting infrastructure from unauthorized access. We have discussed these topics in detail in Chapter 7, Understanding Security in Amazon EMR.

The following are a few of the general best practices that you can follow while implementing security:

  • Follow the least privilege principle of AWS and provide the minimal required access to your cluster.
  • Avoid using the same AWS IAM role for multiple clusters; rather, create use case or cluster-specific roles to reduce the blast radius.
  • If you do not have a specific EMR release dependency, then prefer to use the latest EMR release, which has all the security patches integrated.
  • It's better to consider all security aspects from the very beginning, as implementing it later is more complex and expensive...