Creating a Glue Crawler

Introduction

In the previous tutorial, we manually wrote a CREATE EXTERNAL TABLE SQL statement in Amazon Athena to define the schema of our CSV files. However, what if you have a data lake with thousands of S3 buckets containing complex JSON, Parquet, and CSV files, and the schemas are constantly changing?

Writing DDL statements manually is impossible at scale. AWS Glue Crawlers automate this entirely.

What is a Glue Crawler?

An AWS Glue Crawler connects to a data store (like an S3 bucket or an RDS database), progresses through a prioritized list of classifiers to determine the schema of your data, and automatically creates metadata tables in the AWS Glue Data Catalog.

Amazon Athena uses this Data Catalog to understand the structure of the data when you run your SQL queries.

Creating a Crawler

1. Navigate to the AWS Glue Console.
2. Click on Crawlers and then Add crawler.
3. Name: Give your crawler a descriptive name (e.g., production_logs_crawler).
4. Data Store: Choose S3 and provide the s3:// path to the folder containing your raw data files.
5. IAM Role: Create a new IAM Role that grants the crawler permission to read from that specific S3 bucket.
6. Schedule: You can run the crawler on-demand, or set it to run on a cron schedule (e.g., every night at midnight) to automatically detect if the developers added a new column to the log files.
7. Database: Select an existing Glue database or create a new one to store the generated tables.

Once you run the crawler, it spins up, scans your S3 files, infers the data types (string, int, boolean), and magically creates the tables. You can immediately open Amazon Athena and start querying!

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