Azure Machine Learning Feature Store SDK
Project description
# Azure Machine Learning Feature Store Python SDK
The azureml-featurestore package is the core SDK interface for Azure ML Feature Store. This SDK works along the azure-ai-ml SDK to provide the managed feature store experience.
## Main features in the azureml-featurestore package - Develop feature set specification in Spark with the ability for feature transformation. - List and get feature sets defined in Azure ML Feature Store. - Generate and resolve feature retrieval specification. - Run offline feature retrieval with point-in-time join.
## Getting started
You can install the package via ` pip install azureml-featurestore `
To learn more about Azure ML managed feature store visit https://aka.ms/featurestore-get-started
# Change Log
## 1.1.0 (2024.03.13)
New Features:
[Public Preview] Support for DSL (Domain Specific Language) for feature definition. The DSL is a simplified way to define feature set transformations using a declarative syntax. - DSL feature set supports custom source - DSL feature set supports temporal join lookback, source delay and source lookback - DSL feature set supports load from materialized store - get_offline_features supports feature sets with different transformations(dsl, udf or none).
## 1.0.1 (2023.12.28)
Update dependencies
## 1.0.0 (2023.11.14)
[GA] Custom feature source: Custom feature source supports customized source process code script with a user defined dictionary as input.
[GA] International regions and sovereign cloud support.
[GA] Offline backfill materialization now replaces all data within a feature window instead of doing upsert based on timestamp.
[GA] Added bootstrap option for materialization, which enables materializing data from offline store into online store.
Re-enabling materialization in a feature set now invalidates all previously materialized data.
Feature set spec dump now accepts a file path or a folder path as dump target, and an overwrite option to control whether to override the target.
Various bug fixes
## 0.1.0b6 (2023.11.1)
Various bug fixes
## 0.1.0b5 (2023.10.4)
Various bug fixes
## 0.1.0b4 (2023.08.28)
New Features:
[Public preview] Added custom feature source. Custom feature source supports customized source process code script with a user defined dictionary as input.
[Public preview] Added csv feature source, deltatable feature source, mltable feature source, parquet feature source as new feature source experience. Previous feature source usage compatibility will be deprecated in 6 months.
Bug fixes
Breaking changes: - Moved init_online_lookup, shutdown_online_lookup and get_online_features out of FeatureStoreClient, and into the module as standalone functions. - get_online_features contract changed from accepting (for the observation_data argument) and returning pandas.DataFrame to accepting (as the observation_data argument) and returning pyarrow.Table.
Other changes: - Moved online feature store support into public preview.
## 0.1.0b3 (2023.07.10)
Various bug fixes
## 0.1.0b2 (2023.06.13)
New Features:
[Private preview] Added online store support. Online store supports materialization and online feature values retrieval from Redis cache for batch scoring.
Various bug fixes
## 0.1.0b1 (2023.05.15)
New Features:
Initial release.
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