Configure Expectation Stores
An Expectation Store is a connector to store and retrieve information about collections of verifiable assertions about data.
By default, new ExpectationsA verifiable assertion about data. are stored as Expectation SuitesA collection of verifiable assertions about data. in JSON format in the expectations/ subdirectory of your gx/ folder. Use the information provided here to configure a store for your Expectations.
- Amazon S3
- Microsoft Azure Blob Storage
- Google Cloud Service
- Filesystem
- PostgreSQL
Amazon S3
Use the information provided here to configure a new storage location for Expectations in Amazon S3.
Prerequisites
- A Data Context.
- An Expectations Suite.
- Permissions to install boto3 in your local environment.
- An S3 bucket and prefix to store Expectations.
Install boto3 with pip
Python interacts with AWS through the boto3 library. Great Expectations makes use of this library in the background when working with AWS. Although you won't use boto3 directly, you'll need to install it in your virtual environment.
Run one of the following pip commands to install boto3 in your virtual environment:
python -m pip install boto3
or
python3 -m pip install boto3
To set up boto3 with AWS, and use boto3 within Python, see the Boto3 documentation.
Verify your AWS credentials
Run the following command in the AWS CLI to verify that your AWS credentials are properly configured:
aws sts get-caller-identity
When your credentials are properly configured, your UserId, Account, and Arn are returned. If your credentials are not configured correctly, an error message appears. If you received an error message, or you couldn't verify your credentials, see Configuring the AWS CLI.
Identify your Data Context Expectations Store
Your Expectation StoreA connector to store and retrieve information about collections of verifiable assertions about data. configuration is in your Data ContextThe primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components..
The following section in your Data ContextThe primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components. great_expectations.yml file tells Great Expectations to look for Expectations in a Store named expectations_store:
stores:
expectations_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleFilesystemStoreBackend
base_directory: expectations/
expectations_store_name: expectations_store
The default base_directory for expectations_store is expectations/.
Update your configuration file to include a new Store for Expectations
To manually add an Expectations StoreA connector to store and retrieve information about collections of verifiable assertions about data. to your configuration, add the following configuration to the stores section of your great_expectations.yml file:
stores:
expectations_S3_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleS3StoreBackend
bucket: '<your>'
prefix: '<your>' # Bucket and prefix in combination must be unique across all stores
expectations_store_name: expectations_S3_store
Change the default store_backend settings to make the Store work with S3. The class_name is set to TupleS3StoreBackend, bucket is the address of your S3 bucket, and prefix is the folder in your S3 bucket where Expectations are located.
The following example shows the additional options that are available to customize TupleS3StoreBackend:
class_name: ExpectationsStore
store_backend:
class_name: TupleS3StoreBackend
bucket: '<your_s3_bucket_name>'
prefix: '<your_s3_bucket_folder_name>' # Bucket and prefix in combination must be unique across all stores
boto3_options:
endpoint_url: ${S3_ENDPOINT} # Uses the S3_ENDPOINT environment variable to determine which endpoint to use.
region_name: '<your_aws_region_name>'
In the previous example, the Store name is expectations_S3_store. If you use a personalized Store name, you must also update the value of the expectations_store_name key to match the Store name. For example:
expectations_store_name: expectations_S3_store
When you update the expectations_store_name key value, Great Expectations uses the new Store for Validation Results.
Add the following code to great_expectations.yml to configure the IAM user:
class_name: ExpectationsStore
store_backend:
class_name: TupleS3StoreBackend
bucket: '<your_s3_bucket_name>'
prefix: '<your_s3_bucket_folder_name>'
boto3_options:
aws_access_key_id: ${AWS_ACCESS_KEY_ID} # Uses the AWS_ACCESS_KEY_ID environment variable to get aws_access_key_id.
aws_secret_access_key: ${AWS_ACCESS_KEY_ID}
aws_session_token: ${AWS_ACCESS_KEY_ID}
Add the following code to great_expectations.yml to configure the IAM Assume Role:
class_name: ExpectationsStore
store_backend:
class_name: TupleS3StoreBackend
bucket: '<your_s3_bucket_name>'
prefix: '<your_s3_bucket_folder_name>' # Bucket and prefix in combination must be unique across all stores
boto3_options:
assume_role_arn: '<your_role_to_assume>'
region_name: '<your_aws_region_name>'
assume_role_duration: session_duration_in_seconds
If you're storing Validations in S3 or DataDocs in S3, make sure that the prefix values are disjoint and one is not a substring of the other.
Copy existing Expectation JSON files to the S3 bucket (Optional)
If you are converting an existing local Great Expectations deployment to one that works in AWS, you might have Expectations saved that you want to transfer to your S3 bucket.
Run the following aws s3 synccommand to copy Expectations into Amazon S3:
aws s3 sync '<base_directory>' s3://'<your_s3_bucket_name>'/'<your_s3_bucket_folder_name>'
The base_directory is set to expectations/ by default.
In the following example, the Expectations exp1 and exp2 are copied to Amazon S3 and a confirmation message is returned:
upload: ./exp1.json to s3://'<your_s3_bucket_name>'/'<your_s3_bucket_folder_name>'/exp1.json
upload: ./exp2.json to s3://'<your_s3_bucket_name>'/'<your_s3_bucket_folder_name>'/exp2.json
Confirm Expectation Suite availability
If you copied your existing Expectation Suites to the S3 bucket, run the following Python code to confirm that Great Expectations can find them:
import great_expectations as gx
context = gx.get_context()
context.list_expectation_suite_names()
The Expectations you copied to S3 are returned as a list. Expectations that weren't copied to the new Store aren't listed.
Microsoft Azure Blob Storage
Use the information provided here to configure a new storage location for Expectations in Microsoft Azure Blob Storage.
Prerequisites
- A Data Context.
- An Expectations Suite.
- An Azure Storage account.
- An Azure Blob container. If you need to host and share Data Docs on Azure Blob Storage, then you can set this up first and then use the
$webexisting container to store your Expectations. - A prefix (folder) where to store Expectations. You don't need to create the folder, the prefix is just part of the Azure Blob name.
Configure the config_variables.yml file with your Azure Storage credentials
GX recommends that you store Azure Storage credentials in the config_variables.yml file, which is located in the uncommitted/ folder by default, and is not part of source control. The following code adds Azure Storage credentials below the AZURE_STORAGE_CONNECTION_STRING key:
AZURE_STORAGE_CONNECTION_STRING: "DefaultEndpointsProtocol=https;EndpointSuffix=core.windows.net;AccountName=<YOUR-STORAGE-ACCOUNT-NAME>;AccountKey=<YOUR-STORAGE-ACCOUNT-KEY==>"
To learn more about the additional options for configuring the config_variables.yml file, or additional environment variables, see How to configure credentials
Identify your Data Context Expectations Store
Your Expectations Store configuration is provided in your Data ContextThe primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components.. Open great_expectations.yml and find the following entry:
expectations_store_name: expectations_store
stores:
expectations_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleFilesystemStoreBackend
base_directory: expectations/
This configuration tells Great Expectations to look for Expectations in a Store named expectations_store. The default base_directory for expectations_store is expectations/.
Update your configuration file to include a new Store for Expectations
In the following example, expectations_store_name is set to expectations_AZ_store, but it can be personalized. You also need to change the store_backend settings. The class_name is TupleAzureBlobStoreBackend, container is the name of your blob container where Expectations are stored, prefix is the folder in the container where Expectations are located, and connection_string is ${AZURE_STORAGE_CONNECTION_STRING} to reference the corresponding key in the config_variables.yml file.
expectations_store_name: expectations_AZ_store
stores:
expectations_AZ_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleAzureBlobStoreBackend
container: <blob-container>
prefix: expectations
connection_string: ${AZURE_STORAGE_CONNECTION_STRING}
If the container for hosting and sharing Data Docs on Azure Blob Storage is named $web, use container: \$web to allow access to the $webcontainer.
Additional authentication and configuration options are available. See Hosting and sharing Data Docs on Azure Blob Storage.
Copy existing Expectation JSON files to the Azure blob (Optional)
You can use the az storage blob upload command to copy Expectations into Azure Blob Storage. The following command copies the Expectation exp1 from a local folder to Azure Blob Storage:
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/expectation.json> -c <GREAT-EXPECTATION-DEDICATED-AZURE-BLOB-CONTAINER-NAME> -n <PREFIX>/<expectation.json>
example :
az storage blob upload -f gx/expectations/exp1.json -c <blob-container> -n expectations/exp1.json
Finished[#############################################################] 100.0000%
{
"etag": "\"0x8D8E08E5DA47F84\"",
"lastModified": "2021-03-06T10:55:33+00:00"
}
To learn more about other methods that are available to copy Expectation JSON files into Azure Blob Storage, see Introduction to Azure Blob Storage.
Confirm that the new Expectation Suites have been added
If you copied your existing Expectation Suites to Azure Blob Storage, run the following Python command to confirm that Great Expectations can find them:
import great_expectations as gx
context = gx.get_context()
context.list_expectation_suite_names()
A list of Expectations you copied to Azure Blob Storage is returned. Expectations that weren't copied to the new folder are not listed.
Confirm that Expectations can be accessed from Azure Blob Storage
Run the following command to confirm your Expectations have been copied to Azure Blob Storage:
great_expectations suite list
If your Expectations have not been copied to Azure Blob Storage, the message "No Expectations were found" is returned.
GCS
Use the information provided here to configure a new storage location for Expectations in GCS.
To view all the code used in this topic, see how_to_configure_an_expectation_store_in_gcs.py.
Prerequisites
- A Data Context.
- An Expectations Suite.
- A GCP service account with credentials that allow access to GCP resources such as Storage Objects.
- A GCP project, GCS bucket, and prefix to store Expectations.
Configure your GCP credentials
Confirm that your environment is configured with the appropriate authentication credentials needed to connect to the GCS bucket where Expectations will be stored. This includes the following:
- A GCP service account.
- Setting the
GOOGLE_APPLICATION_CREDENTIALSenvironment variable. - Verifying authentication by running a Google Cloud Storage client library script.
For more information about validating your GCP authentication credentials, see Authenticate to Cloud services using client libraries.
Identify your Data Context Expectations Store
The configuration for your Expectations StoreA connector to store and retrieve information about metadata in Great Expectations. is available in your Data ContextThe primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components.. Open great_expectations.yml and find the following entry:
stores:
expectations_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleFilesystemStoreBackend
base_directory: expectations/
expectations_store_name: expectations_store
This configuration tells Great Expectations to look for Expectations in the expectations_store Store. The default base_directory for expectations_store is expectations/.
Update your configuration file to include a new store for Expectations
In the following example, expectations_store_name is set to expectations_GCS_store, but it can be personalized. You also need to change the store_backend settings. The class_name is TupleGCSStoreBackend, project is your GCP project, bucket is the address of your GCS bucket, and prefix is the folder on GCS where Expectations are stored.
stores:
expectations_GCS_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleGCSStoreBackend
project: <your>
bucket: <your>
prefix: <your>
expectations_store_name: expectations_GCS_store
If you are also storing Validations in GCS or DataDocs in GCS, make sure that the prefix values are disjoint and one is not a substring of the other.
Copy existing Expectation JSON files to the GCS bucket (Optional)
Use the gsutil cp command to copy Expectations into GCS. For example, the following command copies the Expectation ```my_expectation_suite`` from a local folder into a GCS bucket:
gsutil cp expectations/my_expectation_suite.json gs://<your>/<your>/my_expectation_suite.json
The following confirmation message is returned:
Operation completed over 1 objects
Additional methods for copying Expectations into GCS are available. See Upload objects from a filesystem.
Confirm that the new Expectation Suites have been added
If you copied your existing Expectation Suites to GCS, run the following Python command to confirm that Great Expectations can find them:
import great_expectations as gx
context = gx.get_context()
context.list_expectation_suite_names()
A list of Expectation Suites you copied to GCS is returned. Expectation Suites that weren't copied to the new Store aren't listed.
Confirm that Expectations can be accessed from GCS
Run the following command to confirm your Expectations were copied to GCS:
great_expectations suite list
If your Expectations were not copied to Azure Blob Storage, a message indicating no Expectations were found is returned.
Filesystem
Use the information provided here to configure a new storage location for Expectations on your Filesystem.
Prerequisites
- A Data Context.
- An Expectation Suite.
- A storage location for Expectations. This can be a local path, or a path to a network filesystem.
Create a new folder for Expectations
Run the following command to create a new folder for your Expectations and move your existing Expectations to the new folder:
# in the gx/ folder
mkdir shared_expectations
mv expectations/npi_expectations.json shared_expectations/
In this example, the name of the Expectation is npi_expectations and the path to the new storage location is /shared_expectations.
Identify your Data Context Expectations Store
The configuration for your Expectations StoreA connector to store and retrieve information about metadata in Great Expectations. is available in your Data ContextThe primary entry point for a Great Expectations deployment, with configurations and methods for all supporting components.. Open great_expectations.ymland find the following entry:
expectations_store_name: expectations_store
stores:
expectations_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleFilesystemStoreBackend
base_directory: expectations/
This configuration tells Great Expectations to look for Expectations in the expectations_store Store. The default base_directory for expectations_store is expectations/.
Update your configuration file to include a new Store for Expectations results
In the following example, expectations_store_name is set to shared_expectations_filesystem_store, but it can be personalized. Also, base_directory is set to shared_expectations/, but you can set it to another path that is accessible by Great Expectations.
expectations_store_name: shared_expectations_filesystem_store
stores:
shared_expectations_filesystem_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleFilesystemStoreBackend
base_directory: shared_expectations/
Confirm that the new Expectation Suites have been added
If you copied your existing Expectation Suites to your filesystem, run the following Python command to confirm that Great Expectations can find them:
import great_expectations as gx
context = gx.get_context()
context.list_expectation_suite_names()
A list of Expectation Suites you copied your filesystem is returned. Expectation Suites that weren't copied to the new Store aren't listed.
Version control systems
GX recommends that you store Expectations in a version control system such as Git. The JSON format of Expectations allows for informative diff-statements and modification tracking. In the following example, the ```expect_table_column_count_to_equalvalue changes from333to331, and then to 330``:
git log -p npi_expectations.json
commit cbc127fb27095364c3c1fcbf6e7f078369b07455
changed expect_table_column_count_to_equal to 331
diff --git a/gx/expectations/npi_expectations.json b/great_expectations/expectations/npi_expectations.json
--- a/gx/expectations/npi_expectations.json
+++ b/gx/expectations/npi_expectations.json
@@ -17,7 +17,7 @@
{
"expectation_type": "expect_table_column_count_to_equal",
"kwargs": {
- "value": 333
+ "value": 331
}
commit 05b3c8c1ed35d183bac1717d4877fe13bc574963
changed expect_table_column_count_to_equal to 333
diff --git a/gx/expectations/npi_expectations.json b/great_expectations/expectations/npi_expectations.json
--- a/gx/expectations/npi_expectations.json
+++ b/gx/expectations/npi_expectations.json
{
"expectation_type": "expect_table_column_count_to_equal",
"kwargs": {
- "value": 330
+ "value": 333
}
PostgreSQL
Use the information provided here to configure an Expectations store in a PostgreSQL database.
Prerequisites
- A Data Context.
- An Expectations Suite.
- A PostgreSQL database with appropriate credentials.
Configure the config_variables.yml file with your database credentials
GX recommends storing database credentials in the config_variables.yml file, which is located in the uncommitted/ folder by default, and not part of source control.
To add database credentials, open config_variables.yml and add the following entry below the db_creds key:
db_creds:
drivername: postgresql
host: '<your_host_name>'
port: '<your_port>'
username: '<your_username>'
password: '<your_password>'
database: '<your_database_name>'
To configure the config_variables.yml file, or additional environment variables, see How to configure credentials.
Identify your Data Context Expectations Store
Open great_expectations.ymland find the following entry:
expectations_store_name: expectations_store
stores:
expectations_store:
class_name: ExpectationsStore
store_backend:
class_name: TupleFilesystemStoreBackend
base_directory: expectations/
This configuration tells Great Expectations to look for Expectations in the expectations_store Store. The default base_directory for expectations_store is expectations/.
Update your configuration file to include a new Store for Expectations
In the following example, expectations_store_name is set to expectations_postgres_store, but it can be personalized. You also need to make some changes to the store_backend settings. The class_name is DatabaseStoreBackend, and credentials is ${db_creds} to reference the corresponding key in the config_variables.yml file.
expectations_store_name: expectations_postgres_store
stores:
expectations_postgres_store:
class_name: ExpectationsStore
store_backend:
class_name: DatabaseStoreBackend
credentials: ${db_creds}