Batch write and discover records in Amazon SageMaker Feature Store
Amazon SageMaker Feature Store has introduced two new APIs to improve data ingestion and exploration. The BatchWriteRecord function allows users to save up to 25 records across multiple feature groups in one operation. Meanwhile, the ListRecords function lists record identifiers stored within a feature group.
Key Takeaways
- AWS Machine Learning has updated Amazon SageMaker Feature Store to support two new APIs focused on record management.
The newly introduced BatchWriteRecord feature allows users to write up to 25 records across multiple feature groups through a single request.
- In addition, the ListRecords feature enables developers to enumerate and inspect record identifiers present inside a specific feature group.
These updates improve the efficiency of managing features and inspecting data structures in machine learning workflows.
- Allowing multi-group batch updates reduces the number of API calls needed to refresh feature datasets.
Easy record enumeration helps practitioners verify data contents and trace record identifiers while building machine learning pipelines.
- Amazon SageMaker Feature Store has introduced two new APIs called BatchWriteRecord and ListRecords.
The BatchWriteRecord API allows writing up to 25 records across multiple feature groups in a single call.
- The ListRecords API provides a way to enumerate record identifiers within a designated feature group.
Stats & Key Facts
- #The BatchWriteRecord function allows users to save up to 25 records across multiple feature groups in one operation.
- #The newly introduced BatchWriteRecord feature allows users to write up to 25 records across multiple feature groups through a single request.
AWS Machine Learning has updated Amazon SageMaker Feature Store to support two new APIs focused on record management. The newly introduced BatchWriteRecord feature allows users to write up to 25 records across multiple feature groups through a single request. In addition, the ListRecords feature enables developers to enumerate and inspect record identifiers present inside a specific feature group.
These updates improve the efficiency of managing features and inspecting data structures in machine learning workflows. Allowing multi-group batch updates reduces the number of API calls needed to refresh feature datasets. Easy record enumeration helps practitioners verify data contents and trace record identifiers while building machine learning pipelines.
Amazon SageMaker Feature Store has introduced two new APIs called BatchWriteRecord and ListRecords. The BatchWriteRecord API allows writing up to 25 records across multiple feature groups in a single call. The ListRecords API provides a way to enumerate record identifiers within a designated feature group.
For more details please read the original article at AWS Machine Learning.
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