GitBook: [master] 62 pages modified

felixwang9817 · gitbook-bot · commit 1b809a73e7e5 · 2021-09-10T18:52:12.000Z
diff --git a/docs/getting-started/concepts/data-model-and-concepts/feature-view.md b/docs/getting-started/concepts/data-model-and-concepts/feature-view.md
@@ -1,8 +1,8 @@
 # Feature view
 
-## Feature View
+## Feature views
 
-A feature view is an object that represents a logical group of time-series feature data as it is found in a [data source](data-source.md). Feature views consist of zero or more [entities](entity.md), one or more [features](feature-view.md#feature), and a [data source](data-source.md). Feature views allow Feast to model your existing feature data in a consistent way in both an offline \(training\) and online \(serving\) environment. If a feature view contains features that are properties of a specific object, that object is typically defined as an entity and included in the feature view. If a feature view contains features that are not related to a specific entity, for example global features, the feature view can be defined without entities.
+A feature view is an object that represents a logical group of time-series feature data as it is found in a [data source](data-source.md). Feature views consist of zero or more [entities](entity.md), one or more [features](feature-view.md#feature), and a [data source](data-source.md). Feature views allow Feast to model your existing feature data in a consistent way in both an offline \(training\) and online \(serving\) environment. Feature views generally contain features that are properties of a specific object, in which case that object is defined as an entity and included in the feature view. If the features are not related to a specific object, the feature view might not have entities; see [feature views without entities](feature-view.md#feature-views-without-entities) below.
 
 {% tabs %}
 {% tab title="driver\_trips\_feature\_view.py" %}
@@ -20,14 +20,30 @@ driver_stats_fv = FeatureView(
 )
 ```
 {% endtab %}
+{% endtabs %}
+
+Feature views are used during
+
+* The generation of training datasets by querying the data source of feature views in order to find historical feature values. A single training dataset may consist of features from multiple feature views.
+* Loading of feature values into an online store. Feature views determine the storage schema in the online store.
+* Retrieval of features from the online store. Feature views provide the schema definition to Feast in order to look up features from the online store.
+
+{% hint style="info" %}
+Feast does not generate feature values. It acts as the ingestion and serving system. The data sources described within feature views should reference feature values in their already computed form.
+{% endhint %}
+
+## Feature views without entities
 
-{% tab title="global\_feature\_view.py" %}
+If a feature view contains features that are not related to a specific entity, the feature view can be defined without entities.
+
+{% tabs %}
+{% tab title="global\_stats.py" %}
 ```python
 global_stats_fv = FeatureView(
     name="global_stats",
     entities=[],
     features=[
-        Feature(name="total_trips_today", dtype=ValueType.INT64),
+        Feature(name="total_trips_today_by_all_drivers", dtype=ValueType.INT64),
     ],
     batch_source=BigQuerySource(
         table_ref="feast-oss.demo_data.global_stats"
@@ -37,16 +53,6 @@ global_stats_fv = FeatureView(
 {% endtab %}
 {% endtabs %}
 
-Feature views are used during
-
-* The generation of training datasets by querying the data source of feature views in order to find historical feature values. A single training dataset may consist of features from multiple feature views.
-* Loading of feature values into an online store. Feature views determine the storage schema in the online store.
-* Retrieval of features from the online store. Feature views provide the schema definition to Feast in order to look up features from the online store.
-
-{% hint style="info" %}
-Feast does not generate feature values. It acts as the ingestion and serving system. The data sources described within feature views should reference feature values in their already computed form.
-{% endhint %}
-
 ## Feature
 
 A feature is an individual measurable property. It is typically a property observed on a specific entity, but does not have to be associated with an entity. For example, a feature of a `customer` entity could be the number of transactions they have made on an average month, while a feature that is not observed on a specific entity could be the total number of posts made by all users in the last month.
diff --git a/docs/getting-started/faq.md b/docs/getting-started/faq.md
@@ -12,6 +12,10 @@ The [quickstart](quickstart.md) is the easiest way to learn about Feast. For mor
 
 Feature tables from Feast 0.9 have been renamed to feature views in Feast 0.10+. For more details, please see the discussion [here](https://github.com/feast-dev/feast/issues/1583).
 
+### Do feature views have to include entities?
+
+No, there are [feature views without entities](concepts/data-model-and-concepts/feature-view.md#feature-views-without-entities).
+
 ## Functionality
 
 ### Does Feast provide security or access control?
