EasyGlue

This project aims to make the usage of AWS Glue's DynamicFrame more similar to that of Apache Spark's DataFrame, so that it's easier to remember and read. Let's take a simple S3 read of a JSON dataset for instance:

In Spark, this would be a DataFrame S3 read:

spark.read().json('s3://test_path/')

In Glue, this would be a DynamicFrame S3 read:

glue.create_dynamic_frame.from_options(connection_type='s3', connection_options={'paths': ['s3://test_path/']}, format='json', transformation_ctx='datasource0')

As you can see, the syntax here is quite different - and in the case of Glue, way more verbose. With EasyGlue, you can turn the DynamicFrame read operation into something way more similar:

glue.read().json('s3://test_path/')

Currently-supported options

The project currently supports:

• Reading/writing from/to:
  • S3, in any of the file formats supported by Glue
  • JDBC
  • RDDs
  • DynamoDB
  • DocumentDB and MongoDB
• Secrets Manager integration for JDBC read/writes

Usage

You can either use the pre-built PyPi package, or build it yourself to a wheel file:

Using from PyPi

To use EasyGlue in your projects, simply add the following properties to your job:

key: --additional-python-modules
value: easyglue

Then add an import easyglue statement at the beginning of your job's code. That's it.

Building to a wheel file

If you prefer to build from source and pass the module as a wheel file, do the following:

1. Download the source code: git clone https://github.com/albertquiroga/EasyGlue.git
2. Go into the project's directory, and build it into a wheel file: python setup.py build bdist_wheel
3. A new dist directory will have been created, inside you'll find the built wheel file. Upload this to S3 and add it as a library to your Glue ETL Job
4. In your ETL Job code, simply add a import easyglue line at the top

How does this work?

This project uses class extension methods to simply add methods to the GlueContext class:

• In Python this is not supported as neatly as in other programming languages, but it's doable through setattr.
• In Scala, this is directly supported.

Roadmap

Check the roadmap in GitHub here