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chore: Updating quickstart and fixing roadmap + broken links to old a…
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…lpha docs (#2553)

* chore: Updating quickstart and fixing trailing ) in roadmap + broken link to old alpha docs

Signed-off-by: Danny Chiao <[email protected]>

* fix

Signed-off-by: Danny Chiao <[email protected]>
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adchia committed Apr 15, 2022
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -148,7 +148,7 @@ The list below contains the functionality that contributors are planning to deve
* [x] [Hive (community plugin)](https://github.com/baineng/feast-hive)
* [x] [Postgres (community plugin)](https://github.com/nossrannug/feast-postgres)
* [x] [Spark (community plugin)](https://docs.feast.dev/reference/data-sources/spark)
* [x] Kafka / Kinesis sources (via [push support into the online store](https://docs.feast.dev/reference/data-sources/push)
* [x] Kafka / Kinesis sources (via [push support into the online store](https://docs.feast.dev/reference/data-sources/push))
* [ ] HTTP source
* **Offline Stores**
* [x] [Snowflake](https://docs.feast.dev/reference/offline-stores/snowflake)
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1 change: 0 additions & 1 deletion docs/SUMMARY.md
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Expand Up @@ -85,7 +85,6 @@
* [Go-based feature retrieval](reference/feature-servers/go-feature-retrieval.md)
* [\[Alpha\] Data quality monitoring](reference/dqm.md)
* [\[Alpha\] On demand feature view](reference/alpha-on-demand-feature-view.md)
* [\[Alpha\] Stream ingestion](reference/alpha-stream-ingestion.md)
* [\[Alpha\] AWS Lambda feature server](reference/alpha-aws-lambda-feature-server.md)
* [Feast CLI reference](reference/feast-cli-commands.md)
* [Python API reference](http://rtd.feast.dev)
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2 changes: 1 addition & 1 deletion docs/getting-started/third-party-integrations.md
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Expand Up @@ -21,7 +21,7 @@ Don't see your offline store or online store of choice here? Check out our guide
* [x] [Hive (community plugin)](https://github.com/baineng/feast-hive)
* [x] [Postgres (community plugin)](https://github.com/nossrannug/feast-postgres)
* [x] [Spark (community plugin)](https://docs.feast.dev/reference/data-sources/spark)
* [x] Kafka / Kinesis sources (via [push support into the online store](https://docs.feast.dev/reference/data-sources/push)
* [x] Kafka / Kinesis sources (via [push support into the online store](https://docs.feast.dev/reference/data-sources/push))
* [ ] HTTP source

### Offline Stores
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2 changes: 1 addition & 1 deletion docs/roadmap.md
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Expand Up @@ -16,7 +16,7 @@ The list below contains the functionality that contributors are planning to deve
* [x] [Hive (community plugin)](https://github.com/baineng/feast-hive)
* [x] [Postgres (community plugin)](https://github.com/nossrannug/feast-postgres)
* [x] [Spark (community plugin)](https://docs.feast.dev/reference/data-sources/spark)
* [x] Kafka / Kinesis sources (via [push support into the online store](https://docs.feast.dev/reference/data-sources/push)
* [x] Kafka / Kinesis sources (via [push support into the online store](https://docs.feast.dev/reference/data-sources/push))
* [ ] HTTP source
* **Offline Stores**
* [x] [Snowflake](https://docs.feast.dev/reference/offline-stores/snowflake)
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411 changes: 254 additions & 157 deletions examples/quickstart/quickstart.ipynb

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6 changes: 3 additions & 3 deletions sdk/python/feast/templates/aws/driver_repo.py
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Expand Up @@ -8,7 +8,7 @@
# construction of feature vectors
driver = Entity(
# Name of the entity. Must be unique within a project
name="driver_id",
name="driver",
# The join key of an entity describes the storage level field/column on which
# features can be looked up. The join key is also used to join feature
# tables/views when building feature vectors
Expand Down Expand Up @@ -41,7 +41,7 @@
# The list of entities specifies the keys required for joining or looking
# up features from this feature view. The reference provided in this field
# correspond to the name of a defined entity (or entities)
entities=["driver_id"],
entities=["driver"],
# The timedelta is the maximum age that each feature value may have
# relative to its lookup time. For historical features (used in training),
# TTL is relative to each timestamp provided in the entity dataframe.
Expand All @@ -60,7 +60,7 @@
# Batch sources are used to find feature values. In the case of this feature
# view we will query a source table on Redshift for driver statistics
# features
batch_source=driver_stats_source,
source=driver_stats_source,
# Tags are user defined key/value pairs that are attached to each
# feature view
tags={"team": "driver_performance"},
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6 changes: 3 additions & 3 deletions sdk/python/feast/templates/gcp/driver_repo.py
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Expand Up @@ -8,7 +8,7 @@
# construction of feature vectors
driver = Entity(
# Name of the entity. Must be unique within a project
name="driver_id",
name="driver",
# The join key of an entity describes the storage level field/column on which
# features can be looked up. The join key is also used to join feature
# tables/views when building feature vectors
Expand Down Expand Up @@ -39,7 +39,7 @@
# The list of entities specifies the keys required for joining or looking
# up features from this feature view. The reference provided in this field
# correspond to the name of a defined entity (or entities)
entities=["driver_id"],
entities=["driver"],
# The timedelta is the maximum age that each feature value may have
# relative to its lookup time. For historical features (used in training),
# TTL is relative to each timestamp provided in the entity dataframe.
Expand All @@ -58,7 +58,7 @@
# Batch sources are used to find feature values. In the case of this feature
# view we will query a source table on BigQuery for driver statistics
# features
batch_source=driver_stats_source,
source=driver_stats_source,
# Tags are user defined key/value pairs that are attached to each
# feature view
tags={"team": "driver_performance"},
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6 changes: 3 additions & 3 deletions sdk/python/feast/templates/local/example.py
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Expand Up @@ -16,21 +16,21 @@

# Define an entity for the driver. You can think of entity as a primary key used to
# fetch features.
driver = Entity(name="driver_id", value_type=ValueType.INT64, description="driver id",)
driver = Entity(name="driver", join_key="driver_id", value_type=ValueType.INT64,)

# Our parquet files contain sample data that includes a driver_id column, timestamps and
# three feature column. Here we define a Feature View that will allow us to serve this
# data to our model online.
driver_hourly_stats_view = FeatureView(
name="driver_hourly_stats",
entities=["driver_id"],
entities=["driver"],
ttl=timedelta(days=1),
schema=[
Field(name="conv_rate", dtype=Float32),
Field(name="acc_rate", dtype=Float32),
Field(name="avg_daily_trips", dtype=Int64),
],
online=True,
batch_source=driver_hourly_stats,
source=driver_hourly_stats,
tags={},
)
4 changes: 2 additions & 2 deletions sdk/python/feast/templates/snowflake/driver_repo.py
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Expand Up @@ -10,7 +10,7 @@
# construction of feature vectors
driver = Entity(
# Name of the entity. Must be unique within a project
name="driver_id",
name="driver",
# The join key of an entity describes the storage level field/column on which
# features can be looked up. The join key is also used to join feature
# tables/views when building feature vectors
Expand Down Expand Up @@ -43,7 +43,7 @@
# The list of entities specifies the keys required for joining or looking
# up features from this feature view. The reference provided in this field
# correspond to the name of a defined entity (or entities)
entities=["driver_id"],
entities=["driver"],
# The timedelta is the maximum age that each feature value may have
# relative to its lookup time. For historical features (used in training),
# TTL is relative to each timestamp provided in the entity dataframe.
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12 changes: 6 additions & 6 deletions sdk/python/feast/templates/spark/example.py
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Expand Up @@ -16,9 +16,9 @@


# Entity definitions
driver = Entity(name="driver_id", value_type=ValueType.INT64, description="driver id",)
driver = Entity(name="driver", value_type=ValueType.INT64, description="driver id",)
customer = Entity(
name="customer_id", value_type=ValueType.INT64, description="customer id",
name="customer", value_type=ValueType.INT64, description="customer id",
)

# Sources
Expand All @@ -40,27 +40,27 @@
# Feature Views
driver_hourly_stats_view = FeatureView(
name="driver_hourly_stats",
entities=["driver_id"],
entities=["driver"],
ttl=timedelta(days=7),
schema=[
Field(name="conv_rate", dtype=Float32),
Field(name="acc_rate", dtype=Float32),
Field(name="avg_daily_trips", dtype=Int64),
],
online=True,
batch_source=driver_hourly_stats,
source=driver_hourly_stats,
tags={},
)
customer_daily_profile_view = FeatureView(
name="customer_daily_profile",
entities=["customer_id"],
entities=["customer"],
ttl=timedelta(days=7),
schema=[
Field(name="current_balance", dtype=Float32),
Field(name="avg_passenger_count", dtype=Float32),
Field(name="lifetime_trip_count", dtype=Int64),
],
online=True,
batch_source=customer_daily_profile,
source=customer_daily_profile,
tags={},
)
2 changes: 1 addition & 1 deletion sdk/python/tests/utils/online_write_benchmark.py
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Expand Up @@ -29,7 +29,7 @@ def create_driver_hourly_stats_feature_view(source):
Field(name="acc_rate", dtype=Float32),
Field(name="avg_daily_trips", dtype=Int32),
],
batch_source=source,
source=source,
ttl=timedelta(hours=2),
)
return driver_stats_feature_view
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