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docs: Change feature view docs to reflect new parameters (#3023)
Fix docs Signed-off-by: Felix Wang <[email protected]>
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‎docs/getting-started/concepts/feature-view.md‎

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@@ -23,12 +23,14 @@ Feature views allow Feast to model your existing feature data in a consistent wa
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{% tabs %}
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{% tab title="driver_trips_feature_view.py" %}
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```python
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from feast import BigQuerySource, FeatureView, Field
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from feast import BigQuerySource, Entity, FeatureView, Field
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from feast.types import Float32, Int64
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driver = Entity(name="driver", join_keys=["driver_id"])
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driver_stats_fv = FeatureView(
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name="driver_activity",
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entities=["driver"],
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entities=[driver],
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schema=[
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Field(name="trips_today", dtype=Int64),
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Field(name="rating", dtype=Float32),
@@ -93,7 +95,7 @@ location = Entity(name="location", join_keys=["location_id"])
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location_stats_fv= FeatureView(
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name="location_stats",
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entities=["location"],
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entities=[location],
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schema=[
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Field(name="temperature", dtype=Int32),
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Field(name="location_id", dtype=Int64),

‎docs/getting-started/concepts/point-in-time-joins.md‎

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@@ -7,13 +7,15 @@ Feature values in Feast are modeled as time-series records. Below is an example
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The above table can be registered with Feast through the following feature view:
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```python
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from feast import FeatureView, Field, FileSource
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from feast import Entity, FeatureView, Field, FileSource
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from feast.types import Float32, Int64
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from datetime import timedelta
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driver = Entity(name="driver", join_keys=["driver_id"])
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driver_stats_fv = FeatureView(
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name="driver_hourly_stats",
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entities=["driver"],
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entities=[driver],
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schema=[
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Field(name="trips_today", dtype=Int64),
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Field(name="earnings_today", dtype=Float32),

‎docs/getting-started/quickstart.md‎

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@@ -105,7 +105,7 @@ driver = Entity(name="driver", join_keys=["driver_id"], description="driver id",
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# data to our model online.
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driver_hourly_stats_view = FeatureView(
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name="driver_hourly_stats",
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entities=["driver"], # reference entity by name
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entities=[driver],
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ttl=timedelta(seconds=86400 * 1),
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schema=[
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Field(name="conv_rate", dtype=Float32),
@@ -189,7 +189,7 @@ driver = Entity(name="driver", join_keys=["driver_id"], description="driver id",
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# data to our model online.
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driver_hourly_stats_view = FeatureView(
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name="driver_hourly_stats",
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entities=["driver"], # reference entity by name
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entities=[driver],
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ttl=timedelta(seconds=86400 * 1),
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schema=[
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Field(name="conv_rate", dtype=Float32),

‎docs/how-to-guides/automated-feast-upgrade.md‎

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@@ -56,7 +56,7 @@ $ feast repo-upgrade --write
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--- /Users/achal/feast/prompt_dory/example.py
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+++ /Users/achal/feast/prompt_dory/example.py
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@@ -28,9 +29,9 @@
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entities=["driver_id"],
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entities=[driver_id],
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ttl=Duration(seconds=86400 * 365),
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features=[
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- Feature(name="conv_rate", dtype=ValueType.FLOAT),

‎docs/reference/data-sources/push.md‎

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@@ -27,17 +27,19 @@ Feast allows users to push features previously registered in a feature view to t
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Note that the push schema needs to also include the entity.
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```python
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from feast import PushSource, ValueType, BigQuerySource, FeatureView, Feature, Field
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from feast import Entity, PushSource, ValueType, BigQuerySource, FeatureView, Feature, Field
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from feast.types import Int64
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push_source = PushSource(
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name="push_source",
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batch_source=BigQuerySource(table="test.test"),
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)
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user = Entity(name="user", join_keys=["user_id"])
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fv = FeatureView(
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name="feature view",
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entities=["user_id"],
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entities=[user],
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schema=[Field(name="life_time_value", dtype=Int64)],
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source=push_source,
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)

‎docs/reference/feature-repository.md‎

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@@ -105,7 +105,7 @@ driver = Entity(
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driver_locations = FeatureView(
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name="driver_locations",
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entities=["driver"],
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entities=[driver],
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ttl=timedelta(days=1),
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schema=[
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Field(name="lat", dtype=Float32),

‎docs/reference/feature-repository/README.md‎

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@@ -110,7 +110,7 @@ driver = Entity(
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driver_locations = FeatureView(
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name="driver_locations",
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entities=["driver"],
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entities=[driver],
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ttl=timedelta(days=1),
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schema=[
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Field(name="lat", dtype=Float32),

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