By default, Validations are stored in JSON format in the
uncommitted/validations/ subdirectory of your
great_expectations/ folder. Since Validations may include examples of data (which could be sensitive or regulated) they should not be committed to a source control system. This guide will help you configure a new storage location for Validations in a Google Cloud Storage (GCS) bucket.
Prerequisites: This how-to guide assumes you have:
- Completed the Getting Started Tutorial
- Have a working installation of Great Expectations
- Configured a Data Context.
- Configured an Expectations Suite.
- Configured a Checkpoint.
- Configured a Google Cloud Platform (GCP) service account with credentials that can access the appropriate GCP resources, which include Storage Objects.
- Identified the GCP project, GCS bucket, and prefix where Validations will be stored.
Configure your GCP credentials
Check that your environment is configured with the appropriate authentication credentials needed to connect to the GCS bucket where Validations will be stored.
The Google Cloud Platform documentation describes how to verify your authentication for the Google Cloud API, which includes:
- Creating a Google Cloud Platform (GCP) service account,
- Setting the
- Verifying authentication by running a simple Google Cloud Storage client library script.
Identify your Data Context Validations Store
great_expectations.yml, look for the following lines. The configuration tells Great Expectations to look for Validations in a store called
validations_storeis set to
validations_store_name: validations_store stores: validations_store: class_name: ValidationsStore store_backend: class_name: TupleFilesystemStoreBackend base_directory: uncommitted/validations/
Update your configuration file to include a new store for Validations on GCS
In our case, the name is set to
validations_GCS_store, but it can be any name you like. We also need to make some changes to the
class_namewill be set to
projectwill be set to your GCP project,
bucketwill be set to the address of your GCS bucket, and
prefixwill be set to the folder on GCS where Validation files will be located.
validations_store_name: validations_GCS_storestores: validations_GCS_store: class_name: ValidationsStore store_backend: class_name: TupleGCSStoreBackend project: '<your_GCP_project_name>' bucket: '<your_GCS_bucket_name>' prefix: '<your_GCS_folder_name>'
Copy existing Validation results to the GCS bucket. (This step is optional).
One way to copy Validations into GCS is by using the
gsutil cpcommand, which is part of the Google Cloud SDK. In the example below, two Validation results,
Validation2are copied to the GCS bucket. Information on other ways to copy Validation results, like the Cloud Storage browser in the Google Cloud Console, can be found in the Documentation for Google Cloud.
gsutil cp uncommitted/validations/Validation1.json gs://'<your_GCS_bucket_name>'/'<your_GCS_folder_name>'gsutil cp uncommitted/validations/Validation2.json gs://'<your_GCS_bucket_name>'/'<your_GCS_folder_name>' Operation completed over 2 objects/58.8 KiB.
Confirm that the new Validations store has been added by running
great_expectations --v3-api store list.
Notice the output contains two Validation stores: the original
validations_storeon the local filesystem and the
validations_GCS_storewe just configured. This is ok, since Great Expectations will look for Validations in GCS as long as we set the
validations_GCS_store, and the config for
validations_storecan be removed if you would like.
great_expectations --v3-api store list - name: validations_storeclass_name: ValidationsStorestore_backend: class_name: TupleFilesystemStoreBackend base_directory: uncommitted/validations/ - name: validations_GCS_storeclass_name: ValidationsStorestore_backend: class_name: TupleGCSStoreBackend project: '<your_GCP_project_name>' bucket: '<your_GCS_bucket_name>' prefix: '<your_GCS_folder_name>'
Confirm that the Validations store has been correctly configured.
If it would be useful to you, please comment with a +1 and feel free to add any suggestions or questions below. Also, please reach out to us on Slack if you would like to learn more, or have any questions.