Cleaned up some comments, edited cell metadata, and commented out som… (

#2781)

* Cleaned up some comments, edited cell metadata, and commented out some code using better materialization.

* Fixed code formatting errors.

* Updated code snippet for attaching Redis instance to feature store as online store.

sdk/python/featurestore_sample/notebooks/sdk_only/2. Experiment and train models using features.ipynb

@@ -647,7 +647,7 @@
      "outputs_hidden": false,
      "source_hidden": false
     },
-    "name": "gen-training-data-locally",
+    "name": "load-obs-data",
     "nteract": {
      "transient": {
       "deleting": false
@@ -668,6 +668,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "name": "gen-training-data-locally",
     "tags": [
      "active-ipynb"
     ]

sdk/python/featurestore_sample/notebooks/sdk_only/4. Enable online store and run online inference.ipynb

@@ -473,11 +473,6 @@
     "\n",
     "online_store = MaterializationStore(type=\"redis\", target=redis_arm_id)\n",
     "\n",
-    "materialization_identity1 = ManagedIdentityConfiguration(\n",
-    "    client_id=uai_client_id, principal_id=uai_principal_id, resource_id=uai_arm_id\n",
-    ")\n",
-    "\n",
-    "\n",
     "ml_client = MLClient(\n",
     "    AzureMLOnBehalfOfCredential(),\n",
     "    subscription_id=featurestore_subscription_id,\n",
@@ -487,7 +482,6 @@
     "fs = FeatureStore(\n",
     "    name=featurestore_name,\n",
     "    online_store=online_store,\n",
-    "    materialization_identity=materialization_identity1,\n",
     ")\n",
     "\n",
     "fs_poller = ml_client.feature_stores.begin_create(fs)\n",
@@ -594,9 +588,10 @@
     "    version=\"1\",\n",
     "    feature_window_start_time=st,\n",
     "    feature_window_end_time=ed,\n",
-    "    data_status=[\"None\"],\n",
+    "    # data_status=[\"None\"],\n",
     ")\n",
-    "print(poller.result().job_ids)"
+    "# print(poller.result().job_ids)\n",
+    "print(poller.result().job_id)"
    ]
   },
   {
@@ -627,7 +622,8 @@
     "# Get the job URL, and stream the job logs.\n",
     "# With PREMIUM Redis SKU, SKU family \"P\", and cache capacity 2,\n",
     "# it takes approximately 10 minutes to complete.\n",
-    "fs_client.jobs.stream(poller.result().job_ids[0])"
+    "# fs_client.jobs.stream(poller.result().job_ids[0])\n",
+    "fs_client.jobs.stream(poller.result().job_id)"
    ]
   },
   {

sdk/python/featurestore_sample/notebooks/sdk_only/5. Develop a feature set with custom source.ipynb

@@ -188,7 +188,7 @@
    "metadata": {},
    "source": [
     "## Custom source definition\n",
-    "Custom source definition enables you to define your own source loading logic from any data storage. For using this feature, implement a a source processor user-defined function (UDF) class (`CustomerTransactionsTransformer` in this tutorial). This class should define an `__init__(self, **kwargs)` function and a `process(self, start_time, end_time, **kwargs)` function. The `kwargs` dictionary is supplied as a part of the feature set specification definition, which is passed to the UDF. The `start_time` and `end_time` parameters are calculated and passed to the UDF function.\n",
+    "Custom source definition enables you to define your own source loading logic from any data storage. For using this feature, implement a a source processor user-defined function (UDF) class (`CustomSourceTransformer` in this tutorial). This class should define an `__init__(self, **kwargs)` function and a `process(self, start_time, end_time, **kwargs)` function. The `kwargs` dictionary is supplied as a part of the feature set specification definition, which is passed to the UDF. The `start_time` and `end_time` parameters are calculated and passed to the UDF function.\n",
     "\n",
     "Below is a sample code of source processor UDF class:\n",
     "\n",