AWS Glue - Crawlers

ETL jobs that we define in AWS Glue use Data Catalog tables as sources and targets. These data catalog tables should be updated always.

The role of Crawlers in AWS Glue is to automatically discover new data, identify its schema, and update the Data Catalog accordingly. They ensure that the metadata is always up to date by automatically discovering and cataloging data.

How Crawlers Automate Data Discovery and Cataloging?

AWS Glue Crawlers provide us with an efficient way to automate data discovery and cataloging. By scanning data sources, identifying schemas, generating metadata, and organizing it in the Glue Data Catalog, they eliminate the need for manual data management. This automation helps businesses ensure that their data is always available and up to date for analysis.

Lets see how crawlers automate data discovery and cataloging −

Data Format Recognition

After creating and configuring AWS crawlers, they first recognize the data format. They are intelligent enough to recognize various data formats such as JSON, CSV, Avro, Parquet, and ORC. The Crawler examines the format and structure of the files in the defined data source to classify data types, schema, and tables.

Generate Metadata

Once the data format is recognized, the Crawler generates metadata for each table and dataset. This metadata includes information about the schema, such as column names, data types, and relationships between tables.

Cataloging the Data

After generating metadata, the Crawler automatically catalogs the data by storing the schema information in the Glue Data Catalog. The Data Catalog organizes the metadata into databases and tables, which can be accessed by other AWS services such as Athena, Redshift, and SageMaker for analyses and machine learning.

Automated Scheduling

We can also schedule the crawlers to run automatically at regular intervals. This ensures that new or updated data is continuously discovered and cataloged without manual efforts. It allows businesses to keep their data catalog up-to-date and ready for analysis.

Data Transformation

AWS crawlers automate data discovery and cataloging. The metadata generated by crawlers is important for setting up AWS Glue jobs to transform data. Once cataloged, data can be cleaned, enriched, and transformed using Glues ETL capabilities.