Endpoint requests for time series data - Amazon SageMaker AI

Endpoint requests for time series data

A SageMaker Clarify processing job serializes data into arbitrary JSON structures (with MIME type: application/json). To do this, you must provide a template string to the analysis configuration content_template parameter. This is used by the SageMaker Clarify processing job to construct the JSON query provided to your model. content_template contains a record or multiple records from your dataset. You must also provide a template string for record_template, which is used to construct the JSON structure of each record. These records are then inserted into content_template. For more information about content_type or dataset_type, see Analysis Configuration Files.

Note

Because content_template and record_template are string parameters, any double quote characters (") that are part of the JSON serialized structure should be noted as an escaped character in your configuration. For example, if you want to escape a double quote in Python, you could enter the following value for content_template:

'$record'

The following table shows examples of serialized JSON request payloads and the corresponding content_template and record_template parameters required to construct them.

Use case Endpoint request payload (string representation) content_template record_template

Single record at a time

{"target": [1, 2, 3],"start": "2024-01-01 01:00:00"}

'$record'

'{"start": $start_time, "target": $target_time_series}'

Single record with $related_time_series and $static_covariates

{"target": [1, 2, 3],"start": "2024-01-01 01:00:00","dynamic_feat": [[1.0, 2.0, 3.0],[1.0, 2.0, 3.0],"cat": [0,1]}

'$record'

'{"start": $start_time, "target": $target_time_series, "dynamic_feat": $related_time_series, "cat": $static_covariates}'

Multi-records

{"instances": [{"target": [1, 2, 3],"start": "2024-01-01 01:00:00"}, {"target": [1, 2, 3],"start": "2024-01-01 02:00:00"}]}

'{"instances": $records}'

'{"start": $start_time, "target": $target_time_series}'

Multi-records with $related_time_series and $static_covariates

{"instances": [{"target": [1, 2, 3],"start": "2024-01-01 01:00:00","dynamic_feat": [[1.0, 2.0, 3.0],[1.0, 2.0, 3.0],"cat": [0,1]}, {"target": [1, 2, 3],"start": "2024-01-01 02:00:00","dynamic_feat": [[1.0, 2.0, 3.0],[1.0, 2.0, 3.0],"cat": [0,1]}]}

'{"instances": $records}'

''{"start": $start_time, "target": $target_time_series, "dynamic_feat": $related_time_series, "cat": $static_covariates}'