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Runs an inference against an ML model. There are two methods to evaluate a model:
  • By Query - An ML model can be queried, where the inference is returned as the result set.
  • By Execution - An ML model can be run with the EXECUTE FUNCTION command, where the inference is persisted to a specified table.
EVALUATE_MODEL Table Function Syntax
EVALUATE_MODEL EXECUTE FUNCTION Syntax

Parameters

MODEL

Name of the ML model on which to run an inference

DEPLOYMENT_MODE

Scheme used in making inferences on the ML model:
  • BATCH - inference tests are run against a batch of data in an existing table all at once
  • CONTINUOUS - inference tests are run automatically against records being streamed into an input table; inference results are inserted into an output table, which will be updated upon each subsequent inference
    Continuous deployment mode is only available when using the EXECUTE FUNCTION syntax, as it creates a destination table with the continuously updated results.

REPLICATIONS

The number of replicas to launch on Kubernetes

SOURCE_TABLE

Table or query to use as input to the ML model, specified with either of these two forms:
  • INPUT_TABLE(<table name>) - Use the given table or view as input; e.g.:
  • INPUT_TABLE(<query>) - Use the given query as input; e.g.:

DESTINATION_TABLE

Only applicable when using EXECUTE FUNCTION syntax. Name of the table in which to store the results of the inference, in [schema_name.]table_name format, using standard name resolution rules and meeting table naming criteria

Examples

EVALUATE_MODEL Table Function Example
EVALUATE_MODEL EXECUTE FUNCTION Example