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aws-etl-glue-studio's Introduction

Building an ETL job using Spark and Ray on AWS using AWS Glue

Create an Amazon S3 bucket

Create an Amazon S3 bucket and copy the sample_dataset data-engg-demo

Download the dataset to S3

Copy the data set to the S3 bucket

BUCKET_NAME='s3://data-engg-demo/dataset/covid-data/input/'

aws s3 cp --recursive sample_dataset/ $BUCKET_NAME

Create a Glue Crawler

Open the console and click on Data Catalog -> Crawler

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Click on Add a data source and add the S3 location of the dataset (JSON)

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Add the bucket location s3://data-engg-demo/dataset/covid-data/input/json

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Provide the IAM role, so that Glue can read the data from Amazon S3

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Mention the Database you want to select and add a prefix

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Once this is done just review all the parameters, click on Create and Run the Crawler.

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Create an ETL job using the Glue Studio Visual Interface

We can now create an intractive Glue Studio Notebook. Go to the Glue console and go to Data Integration and ETL -> AWS Glue Studio -> Job and then click on Visual with a blank canvas and click on Create

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And now you can follow this workshop

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