AWS sagemaker documentation change
Summary
Removed legacy SageMaker Python SDK v2 code examples and retained only SDK v3 examples throughout the notebook
Security assessment
Changes involve removing outdated code samples without any security context. No security vulnerabilities, encryption, or access control modifications are mentioned.
Diff
diff --git a/sagemaker/latest/dg/feature-store-introduction-notebook.md b/sagemaker/latest/dg/feature-store-introduction-notebook.md index 0c8e76b50..a48998b84 100644 --- a//sagemaker/latest/dg/feature-store-introduction-notebook.md +++ b//sagemaker/latest/dg/feature-store-introduction-notebook.md @@ -49,3 +48,0 @@ The role that you use to run the notebook must have the following managed polici -SageMaker Python SDK v3 - - @@ -67,18 +63,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - import boto3 - import pandas as pd - import numpy as np - import io - from sagemaker.session import Session - from sagemaker import get_execution_role - - prefix = 'sagemaker-featurestore-introduction' - role = get_execution_role() - - sagemaker_session = sagemaker.Session() - region = sagemaker_session.boto_region_name - s3_bucket_name = sagemaker_session.default_bucket() - @@ -112,3 +90,0 @@ In V3, `FeatureGroup.create()` is a classmethod that directly creates and return -SageMaker Python SDK v3 - - @@ -120,13 +95,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - from sagemaker.feature_store.feature_group import FeatureGroup - - customers_feature_group = FeatureGroup( - name=customers_feature_group_name, sagemaker_session=sagemaker_session - ) - orders_feature_group = FeatureGroup( - name=orders_feature_group_name, sagemaker_session=sagemaker_session - ) - @@ -146,3 +108,0 @@ Load feature definitions to your feature group: -SageMaker Python SDK v3 - - @@ -155,7 +114,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - customers_feature_group.load_feature_definitions(data_frame=customer_data) - orders_feature_group.load_feature_definitions(data_frame=orders_data) - @@ -164,3 +116,0 @@ The following calls `create` to create two feature groups, `customers_feature_gr -SageMaker Python SDK v3 - - @@ -194,20 +143,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - customers_feature_group.create( - s3_uri=f"s3://{s3_bucket_name}/{prefix}", - record_identifier_name=record_identifier_feature_name, - event_time_feature_name="EventTime", - role_arn=role, - enable_online_store=True - ) - - orders_feature_group.create( - s3_uri=f"s3://{s3_bucket_name}/{prefix}", - record_identifier_name=record_identifier_feature_name, - event_time_feature_name="EventTime", - role_arn=role, - enable_online_store=True - ) - @@ -216,3 +145,0 @@ To confirm that your feature group was created, we display it by using `Describe -SageMaker Python SDK v3 - - @@ -225,9 +151,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - customers_feature_group.describe() - - - orders_feature_group.describe() - @@ -253,3 +170,0 @@ After feature groups are created, we can put data into them. If you're using the -SageMaker Python SDK v3 - - @@ -268,13 +182,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - customers_feature_group.ingest( - data_frame=customer_data, max_workers=3, wait=True - ) - - - orders_feature_group.ingest( - data_frame=orders_data, max_workers=3, wait=True - ) - @@ -315,3 +216,0 @@ Here we remove the Feature Groups that we created. -SageMaker Python SDK v3 - - @@ -322,7 +220,0 @@ SageMaker Python SDK v3 -SageMaker Python SDK v2 (Legacy) - - - - customers_feature_group.delete() - orders_feature_group.delete() -