Guides you to use AWS Glue to perform vertical partitioning of JSON documents when migrating document data from Amazon S3 to Amazon DynamoDB. Implement vertical partitioning in Amazon DynamoDB using AWS Glue
AWS GLUE ICEBERG HOW TO
Shows how to use a combination of Amazon MSK, the AWS Glue Schema Registry, AWS Glue streaming ETL jobs, and Amazon S3 to create a robust and reliable real-time data processing platform. Guides you to setup Change data capture (CDC) from relational databases to Amazon Redshift with enriching data using Glue Streaming job.ĪWS Glue streaming application to process Amazon MSK data using AWS Glue Schema Registry Stream data from relational databases to Amazon Redshift with upserts using AWS Glue streaming jobs Guides you to create an AWS Glue job that identifies sensitive data at the row level, and create a custom identification pattern to identify case-specific entities.Įnable self-service visual data integration and analysis for fund performance using AWS Glue Studio and Amazon QuickSightĭemonstrates how AWS Glue Studio helps you perform near-real-time analytics, and how to build visualizations and quickly get business insights using Amazon QuickSight.
Introduces the process of writing AWS Glue scripts.ĭetect and process sensitive data using AWS Glue Studio In this comprehensive series, you'll learn everything from the basics of Glue to advanced optimization techniques. Helps you get started using the many ETL capabilities of AWS Glue, and answers some of the more common questions people have. You can find the AWS Glue open-source Python libraries in a separate repository at: awslabs/aws-glue-libs. This repository has samples that demonstrate various aspects of the AWS Glue service, as well as various AWS Glue utilities. AWS Glue is a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development.
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