Building AWS Glue ETL Pipelines with Python Shell for S3 and Redshift Integration
Learn how to develop AWS Glue ETL scripts using Python shell to extract data from S3 and load it into Redshift, enabling efficient data pipelines for small to medium-sized datasets.
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About this video
In this video, we will develop AWS Glue ETL script using Python shell. We can now use Python scripts in AWS Glue to run small to medium-sized ETL (extract, transform, and load) workflow. Previously, AWS Glue jobs were limited to Apache Spark environment.
Python shell jobs in AWS Glue support scripts that are compatible with Python 2 and 3 and come pre-loaded with libraries such as the Boto3, Numpy, SciPy, pandas, and others. We can also, install other libraries via .whl file.
Link to medium article on the topic: https://blog.devgenius.io/develop-aws-glue-etl-pipeline-with-python-shell-fe6f66763e9d
Link to code, GitHub: https://github.com/hnawaz007/pythondataanalysis/tree/main/AWS%20Glue%20ETL%20Python%20Shell
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#Python #ETL #AWS
Topics covered in this video:
0:00 - Introduction ETL with Python shell
0:53 - Pre-Requisites
1:30 - Create Python .whl file
2:35 - Python ETL script
4:15 - Upload scripts to AWS
5:11 - AWS Glue ETL Job
6:33 - AWS Redshift table
6:49 - Execute Glue ETL Job
7:17 - Review Data & logs
Video Information
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22.1K
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285
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Duration
8:07
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Published
Jun 30, 2022
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Quality
hd
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This video is tagged with the following topics. Click any tag to explore more related content and discover similar videos:
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