AWS Glue
Developer Guide

Working with Classifiers on the AWS Glue Console

A classifier determines the schema of your data. You can write a custom classifier and point to it from AWS Glue. To see a list of all the classifiers that you have created, open the AWS Glue console at, and choose the Classifiers tab.

The list displays the following properties about each classifier:


The classifier name. When you create a classifier you must provide a name for it.


The classification type of tables inferred by this classifier.

Last updated

The last time this classifier was updated.

From the Classifiers list in the AWS Glue console, you can add, edit, and delete classifiers. To see more details for a classifier, choose the classifier name in the list. Details include the information you defined when you created the classifier.

To add a classifier in the AWS Glue console, choose Add classifier. When you define a classifier, you supply values for the following:

Classifier name

Provide a unique name for your classifier.


Describe the format or type of data that is classified or provide a custom label.

Grok pattern

This is used to parse your data into a structured schema. The grok pattern is composed of named patterns that describe the format of your data store. You write this grok pattern using the named built-in patterns provided by AWS Glue and custom patterns you write and include in the Custom patterns field. Although grok debugger results might not match the results from AWS Glue exactly, we suggest that you try your pattern using some sample data with a grok debugger. You can find grok debuggers on the web. The named built-in patterns provided by AWS Glue are generally compatible with grok patterns that are available on the web.

Build your grok pattern by iteratively adding named patterns and check your results in a debugger. This activity gives you confidence that when the AWS Glue crawler runs your grok pattern, your data can be parsed.

Custom patterns

These are optional building blocks for the Grok pattern that you write. When built-in patterns cannot parse your data, you might need to write a custom pattern. These custom patterns are defined in this field and referenced in the Grok pattern field. Each custom pattern is defined on a separate line. Just like the built-in patterns, it consists of a named pattern definition that uses regular expression (regex) syntax.

For example, the following has the name MESSAGEPREFIX followed by a regular expression definition to apply to your data to determine whether it follows the pattern.

MESSAGEPREFIX .*-.*-.*-.*-.*

For more information, see Writing Custom Classifiers