Descriptions
Mastering AWS Elastic Map Reduce (EMR) for Data Engineers, AWS Elastic Map Reduce (EMR) is one of the key AWS Services used in building large-scale data processing leveraging Big Data Technologies such as Apache Hadoop, Apache Spark, Hive, etc. In this course, you will learn AWS EMR by building end-to-end data pipelines with Apache Spark and AWS Step Functions. You start by creating and managing EMR clusters using the AWS Web Console, connecting to the master node, and validating CLI interfaces like spark-shell, pyspark, hive, hdfs, and aws CLI. You will set up development clusters, understand their advantages, and use Visual Studio Code Remote Development for Spark application lifecycle management. The course covers deploying Spark applications on EMR clusters, troubleshooting with logs, and running applications programmatically. You will manage EMR clusters and deploy Spark applications as steps using Python Boto3. End-to-end data pipelines are built with AWS Step Functions, including cluster creation, Spark application deployment, and cluster termination in state machines. You will enhance pipelines with validations, build data processing applications using Spark SQL, and deploy pipelines with AWS Step Functions and Boto3 Waiters for linear execution.
What you’ll learn
- Creating Clusters using AWS Elastic Map Reduce Web Console
- Setup Remote Application Development using AWS Elastic Map Reduce (EMR) and Visual Studio Code
- Develop and Validate Simple Spark Application using Visual Studio Code and AWS Elastic Map Reduce (EMR)
- Deploy Spark Application as Step to AWS Elastic Map Reduce (EMR)
- Manage AWS Elastic Map Reduce (EMR) based Pipelines using Boto3 and Python
- Build End to End AWS Elastic Map Reduce (EMR) based Pipelines using AWS Step Functions
- Develop Applications using Spark SQL on AWS EMR Cluster
- Build State Machine or Pipeline using AWS Step Functions using Spark SQL Script on AWS EMR Cluster
- Understand how to pass parameters to Spark SQL Scripts deployed on EMR
Who this course is for
- University Students who want to learn AWS Elastic Map Reduce to process heavy volumes of data with hands on and real time examples
- Aspiring Data Engineers and Data Scientists who want to master building data pipelines using AWS Elastic Map Reduce for large scale Data Processing
- Experienced Application Developers who would like to explore how to build end to end Data Pipelines using Python and AWS Services such as AWS Elastic Map Reduce
- Experienced Data Engineers to build end to end data pipelines using Python and AWS Elastic Map Reduce
- Any IT Professional who is keen to deep dive into AWS Elastic Map Reduce (EMR) for heavy weight Data Processing
Specificatoin of Mastering AWS Elastic Map Reduce (EMR) for Data Engineers
- Publisher : Udemy
- Teacher : Durga Viswanatha Raju Gadiraju , Pratik Kumar , Madhuri Gadiraju , Phani Bhushan Bozzam
- Language : English
- Level : Intermediate
- Number of Course : 150
- Duration : 11 hours and 18 minutes
Content of Mastering AWS Elastic Map Reduce (EMR) for Data Engineers
Requirements
- A computer science or IT Degree or 1 or 2 years of IT Experience
- Basic Linux Skills with ability to run commands using Terminal
- Programming Skills using Python is required
- Valid AWS Account to use the AWS Services to learn how to build Data Pipelines using AWS Lambda Functions
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720
Download Links
Downloadly
Rapidgator
Password file(s): www.downloadly.ir
File size
3.35 GB
