Category: Analytics
Service: AWS Glue
Answer:
An AWS Glue workflow consists of the following components:
Data Catalog: This is a central metadata repository that stores metadata about data sources and targets. It allows you to define schemas and tables for your data, and enables you to discover, search, and query data assets.
Crawler: This is a program that automatically discovers and extracts metadata from your data sources, such as Amazon S3, JDBC databases, and Amazon DynamoDB. The crawler analyzes the data to infer schema and generates a schema definition for each discovered data source.
ETL Jobs: AWS Glue provides an ETL engine that allows you to transform and load data from a source to a target. ETL jobs are defined using the AWS Glue ETL language or Python. You can also use pre-built transforms and connectors to simplify ETL job creation.
Trigger: AWS Glue triggers allow you to schedule and run ETL jobs automatically. You can define triggers based on time, events, or on-demand.
Development Endpoints: AWS Glue development endpoints are fully managed environments that allow you to author, test, and debug ETL scripts. You can use these endpoints to connect to your data sources and debug ETL jobs using an interactive development environment.
Workflow: An AWS Glue workflow is a sequence of ETL jobs that are executed in a specific order. Workflows allow you to define dependencies between ETL jobs and automate the entire ETL process.
All of these components work together to extract, transform, and load data in an efficient and scalable manner.
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