Amazon SageMaker Feature Store offline store data format - Amazon SageMaker

Amazon SageMaker Feature Store offline store data format

Amazon SageMaker Feature Store supports the AWS Glue and Apache Iceberg table formats for the offline store. You can choose the table format when you’re creating a new feature group. AWS Glue is the default format.

Amazon SageMaker Feature Store offline store data is stored in an Amazon S3 bucket within your account. When you call PutRecord, your data is buffered, batched, and written into Amazon S3 within 15 minutes. Feature Store only supports the Parquet file format when writing your data to your offline store. Specifically, when your data is written to your offline store, the data can be retrieved from your Amazon S3 bucket in Parquet format. Each file can contain multiple Records.

For the Iceberg format, Feature Store saves the table’s metadata in the same Amazon S3 bucket that you’re using to store the offline store data. You can find it under the metadata prefix.

Feature Store also exposes the OfflineStoreConfig.S3StorageConfig.ResolvedOutputS3Uri field, which can be found from in the DescribeFeatureGroup API call. This is the S3 path under which the files for the specific feature group are written.

The following additional fields are added by Feature Store to each record when they persist in the offline store:

  • api_invocation_time – The timestamp when the service receives the PutRecord or DeleteRecord call. If using managed ingestion (e.g. Data Wrangler), this is the timestamp when data was written into the offline store.

  • write_time – The timestamp when data was written into the offline store. Can be used for constructing time-travel related queries.

  • is_deletedFalse by default. If DeleteRecord is called, a new Record is inserted into RecordIdentifierValue and set to True in the offline store.

Amazon SageMaker Feature Store offline store URI structures

In the following examples DOC-EXAMPLE-BUCKET is the Amazon S3 bucket within your account, example-prefix is your example prefix, 111122223333 is your account ID, AWS Region is your region, feature-group-name is the name of your feature group.

AWS Glue table format

Records in the offline store stored using the AWS Glue table format are partitioned by event time into hourly partitions. You can’t configure the partitioning scheme. The following URI structure shows the organization of a Parquet file using the AWS Glue format:

s3://DOC-EXAMPLE-BUCKET/example-prefix/111122223333/sagemaker/AWS Region/offline-store/feature-group-name-feature-group-creation-time/data/year=year/month=month/day=day/hour=hour/timestamp_of_latest_event_time_in_file_16-random-alphanumeric-digits.parquet

The following example is the output location of a Parquet file for a file with feature-group-name as customer-purchase-history-patterns:

s3://DOC-EXAMPLE-BUCKET/example-prefix/111122223333/sagemaker/AWS Region/offline-store/customer-purchase-history-patterns-1593511200/data/year=2020/month=06/day=31/hour=00/20200631T064401Z_108934320012Az11.parquet

Iceberg table format

Records in the offline store stored in the Iceberg table format are partitioned by event time into daily partitions. You can’t configure the partitioning scheme. The following URI structure shows the organization of the data files saved in the Iceberg table format:

s3://DOC-EXAMPLE-BUCKET/example-prefix/111122223333/sagemaker/AWS Region/offline-store/feature-group-name-feature-group-creation-time/data/8-random-alphanumeric-digits/event-time-feature-name_trunc=event-time-year-event-time-month-event-time-day/timestamp-of-latest-event-time-in-file_16-random-alphanumeric-digits.parquet

The following example is the output location of a Parquet file for a file with feature-group-name as customer-purchase-history-patterns, and the event-time-feature-name is EventTime:

s3://DOC-EXAMPLE-BUCKET/example-prefix/111122223333/sagemaker/AWS Region/offline-store/customer-purchase-history-patterns-1593511200/data/0aec19ca/EventTime_trunc=2022-11-09/20221109T215231Z_yolTtpyuWbkaeGIl.parquet

The following example is the location of a metadata file for data files saved in the Iceberg table format.

s3://DOC-EXAMPLE-BUCKET/example-prefix/111122223333/sagemaker/AWS Region/offline-store/feature-group-name-feature-group-creation-time/metadata/