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keyboard_arrow_down AWS Data Engineering
Data Engineering Path  ·  PySpark
AWS CORE PLATFORM CASE STUDY

Amazon EMR (Elastic MapReduce)

Amazon EMR is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark, on AWS to process and analyze vast amounts of data.

Explore the comprehensive topics below:

Architecture Infographic Overview

Amazon EMR Architecture Diagram

Learning Material

  1. 01_EMR_vs_AWS_Glue.md: Conceptual differences, architectural layout, operational comparison, and key decision criteria.
  2. 02_Node_Types_and_Architecture.md: Master node, core node, task node architecture along with fleet configuration options.
  3. 03_Creating_EMR_and_PaaS_API.md: Create EMR using AWS Web Console, AWS CLI, and programmatically via Python Boto3 SDK APIs.
  4. 04_Bootstrap_EMRFS_and_Serverless.md: Deep dive on custom boot steps, utilizing object stores (EMRFS), and using modern Serverless options.
  5. 05_PySpark_Job_Examples.md: Production PySpark template executing reads/writes from/to S3 bucket stores and using submission scripts.
  6. 06_Airflow_Orchestration.md: Full pipeline orchestration patterns utilizing Apache Airflow DAG layouts.
  7. 07_Interview_Q_and_A.md: Standard real-world production interview scenarios and optimized answer explanations.
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