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Version: 0.15.50

How to configure a Validation Result Store in Azure Blob Storage

By default, Validation ResultsGenerated when data is Validated against an Expectation or Expectation Suite. are stored in JSON format in the uncommitted/validations/ subdirectory of your great_expectations/ folder. Since Validation Results 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 Validation Results in Azure Blob Storage.

Prerequisites: This how-to guide assumes you have:

Steps​

1. Configure the config_variables.yml file with your Azure Storage credentials​

We recommend that Azure Storage credentials be stored in the config_variables.yml file, which is located in the uncommitted/ folder by default, and is not part of source control. The following lines add Azure Storage credentials under the key AZURE_STORAGE_CONNECTION_STRING. Additional options for configuring the config_variables.yml file or additional environment variables can be found here. 

AZURE_STORAGE_CONNECTION_STRING: "DefaultEndpointsProtocol=https;EndpointSuffix=core.windows.net;AccountName=<YOUR-STORAGE-ACCOUNT-NAME>;AccountKey=<YOUR-STORAGE-ACCOUNT-KEY==>"

2. Identify your Validation Results Store​

As with all StoresA connector to store and retrieve information about metadata in Great Expectations., you can find the configuration for your Validation Results StoreA connector to store and retrieve information about objects generated when data is Validated against an Expectation Suite. through your Data ContextThe primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components.. In your great_expectations.yml, look for the following lines. The configuration tells Great Expectations to look for Validation Results in a store called validations_store. The base_directory for validations_store is set to uncommitted/validations/ by default. 

validations_store_name: validations_store

stores:
  validations_store:
      class_name: ValidationsStore
      store_backend:
          class_name: TupleFilesystemStoreBackend
          base_directory: uncommitted/validations/

3. Update your configuration file to include a new Store for Validation Results on Azure Storage account​

In our case, the name is set to validations_AZ_store, but it can be any name you like. We also need to make some changes to the store_backend settings. The class_name will be set to TupleAzureBlobStoreBackend, container will be set to the name of your blob container (the equivalent of S3 bucket for Azure) you wish to store your Validation Results, prefix will be set to the folder in the container where Validation Result files will be located, and connection_string will be set to ${AZURE_STORAGE_CONNECTION_STRING}, which references the corresponding key in the config_variables.yml file. 

validations_store_name: validations_AZ_store

stores:
  validations_AZ_store:
      class_name: ValidationsStore
      store_backend:
          class_name: TupleAzureBlobStoreBackend
          container: <blob-container>
          prefix: validations
          connection_string: ${AZURE_STORAGE_CONNECTION_STRING}
note

If the container is called $web (for hosting and sharing Data Docs on Azure Blob Storage) then set container: \$web so the escape char will allow us to reach the $webcontainer.

note

Various authentication and configuration options are available as documented in hosting and sharing Data Docs on Azure Blob Storage.

4. Copy existing Validation Results JSON files to the Azure blob (This step is optional)​

One way to copy Validation Results into Azure Blob Storage is by using the az storage blob upload command, which is part of the Azure SDK. The following example will copy one Validation Result from a local folder to the Azure blob. Information on other ways to copy Validation Result JSON files, like the Azure Storage browser in the Azure Portal, can be found in the Documentation for Azure. 

export AZURE_STORAGE_CONNECTION_STRING="DefaultEndpointsProtocol=https;EndpointSuffix=core.windows.net;AccountName=<YOUR-STORAGE-ACCOUNT-NAME>;AccountKey=<YOUR-STORAGE-ACCOUNT-KEY==>"
az storage blob upload -f <local/path/to/validation.json> -c <GREAT-EXPECTATION-DEDICATED-AZURE-BLOB-CONTAINER-NAME> -n <PREFIX>/<validation.json>
example with a validation related to the exp1 expectation:
az storage blob upload -f great_expectations/uncommitted/validations/exp1/20210306T104406.877327Z/20210306T104406.877327Z/8313fb37ca59375eb843adf388d4f882.json -c <blob-container> -n validations/exp1/20210306T104406.877327Z/20210306T104406.877327Z/8313fb37ca59375eb843adf388d4f882.json
Finished[#############################################################]  100.0000%
{
"etag": "\"0x8D8E09F894650C7\"",
"lastModified": "2021-03-06T12:58:28+00:00"
}

5. Confirm that the new Validation Results Store has been added by running great_expectations store list​

Notice the output contains two Validation stores: the original validations_store on the local filesystem and the validations_AZ_store we just configured. This is ok, since Great Expectations will look for Validation Results in Azure Blob as long as we set the validations_store_name variable to validations_AZ_store, and the config for validations_store can be removed if you would like. 

great_expectations store list

- name: validations_store
 class_name: ValidationsStore
 store_backend:
   class_name: TupleFilesystemStoreBackend
   base_directory: uncommitted/validations/

- name: validations_AZ_store
 class_name: ValidationsStore
 store_backend:
   class_name: TupleAzureBlobStoreBackend
   connection_string: "DefaultEndpointsProtocol=https;EndpointSuffix=core.windows.net;AccountName=<YOUR-STORAGE-ACCOUNT-NAME>;AccountKey=<YOUR-STORAGE-ACCOUNT-KEY==>"
   container: <blob-container>
   prefix: validations

6. Confirm that the Validation Results Store has been correctly configured​

Run a Checkpoint to store results in the new Validation Results Store on Azure Blob then visualize the results by re-building Data Docs.