Feature

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Get a featureGET /api/2.0/feature-engineering/features/{full_name}List featuresGET /api/2.0/feature-engineering/featuresCreate a featurePOST /api/2.0/feature-engineering/featuresUpdate a feature's description (all other fields are immutable)PATCH /api/2.0/feature-engineering/features/{full_name}Delete a featureDELETE /api/2.0/feature-engineering/features/{full_name}

Feature object

full_namestringImmutable

The full three-part name (catalog, schema, name) of the feature.

sourceobjectImmutable

The data source of the feature.

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delta_table_sourceobject

A Delta table data source.

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full_namestring

The full three-part (catalog, schema, table) name of the Delta table.

filter_conditionstring

Single WHERE clause to filter delta table before applying transformations. Will be row-wise evaluated, so should only include conditionals and projections.

transformation_sqlstring

A single SQL SELECT expression applied after filter_condition. Should contains all the columns needed (eg. "SELECT , col_a + col_b AS col_c FROM x.y.z WHERE col_a > 0" would have transformation_sql ", col_a + col_b AS col_c") If transformation_sql is not provided, all columns of the delta table are present in the DataSource dataframe.

Default: *

dataframe_schemastring

Schema of the resulting dataframe after transformations, in Spark StructType JSON format (from df.schema.json()). Required if transformation_sql is specified. Example: {"type":"struct","fields":[{"name":"col_a","type":"integer","nullable":true,"metadata":{}},{"name":"col_c","type":"integer","nullable":true,"metadata":{}}]}

kafka_sourceobject

A Kafka stream data source.

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namestring

Name of the Kafka source, used to identify it. This is used to look up the corresponding KafkaConfig object. Can be distinct from topic name.

filter_conditionstring

The filter condition applied to the source data before aggregation.

request_sourceobject

A request-time data source.

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flat_schemaobject

A flat schema with scalar-typed fields only.

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fieldsarray of object

The list of fields in this schema.

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namestring

The name of the field.

data_typestring

The scalar data type of the field.

Values:

• INTEGER
• FLOAT
• BOOLEAN
• STRING
• DOUBLE
• LONG
• TIMESTAMP
• DATE
• SHORT
• BINARY
• DECIMAL

stream_sourceobject

A Stream data source.

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full_namestring

Three-part full name of the Stream (catalog.schema.stream).

filter_conditionstring

The filter condition applied to the source data before aggregation.

functionobjectImmutable

The function by which the feature is computed.

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aggregation_functionobject

An aggregation function applied over a time window.

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avgobject

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inputstring

The input column from which the average is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

count_functionobject

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inputstring

The input column from which the count is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

sumobject

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inputstring

The input column from which the sum is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

minobject

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inputstring

The input column from which the minimum is computed.

maxobject

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inputstring

The input column from which the maximum is computed.

firstobject

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inputstring

The input column from which the first value is returned.

lastobject

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inputstring

The input column from which the last value is returned.

approx_count_distinctobject

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inputstring

The input column from which the approximate count of distinct values is computed.

relative_sddouble

The maximum relative standard deviation allowed (default defined by Spark). Deprecated: use relative_error. When relative_error is set, reads return the same value here for clients that don't have relative_error, and a request may only send that value.

approx_percentileobject

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inputstring

The input column from which the approximate percentile is computed.

percentiledouble

The percentile value to compute (between 0 and 1).

accuracyint64

The accuracy parameter (higher is more accurate but slower). Deprecated: use relative_error. When relative_error is set, reads return ceil(1 / relative_error) here for clients that don't have relative_error, and a request may only send that value.

stddev_popobject

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inputstring

The input column from which the population standard deviation is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

stddev_sampobject

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inputstring

The input column from which the sample standard deviation is computed.

var_popobject

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inputstring

The input column from which the population variance is computed.

var_sampobject

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inputstring

The input column from which the sample variance is computed.

time_windowobject

The time window over which the aggregation is computed.

Show child attributesHide child attributes

tumblingobject

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window_durationstring

The duration of each tumbling window (non-overlapping, fixed-duration windows).

slidingobject

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window_durationstring

The duration of the sliding window. Must be positive when set; absent means lifetime (aggregate over the entity's entire history).

slide_durationstring

The slide duration (interval by which windows advance, must be positive and less than duration).

rollingobject

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window_durationstring

The duration of the rolling window. Must be positive when set; absent means lifetime (aggregate over the entity's entire history).

delaystring

Non-negative analytic lag that evaluates the window this far in the past. Use this for timing variations unrelated to source lateness, such as a 30-day count as of one week ago. If unset, the analytic lag is zero. It composes with source.lateness when both are set.

column_selectionobject

Selects the latest value of a single column in a data source

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columnstring

Column name from source to select as the feature value.

descriptionstring

The description of the feature.

entitiesarray of objectImmutable

The entity columns for the feature, used as aggregation keys and for query-time lookup. Optional since entities are not set for RequestSource features or on-demand calculated features.

Show child attributesHide child attributes

namestring

The name of the entity column. For Kafka sources, use dot-prefixed path notation to reference fields within the key or value schema (e.g., "value.user_id", "key.partition_key"). For nested fields, the leaf node name (e.g., "user_id" from "value.trip_details.user_id") is what will be present in materialized tables and expected to match at query time. Colon-prefixed notation (e.g., "value:user_id") is supported for backwards compatibility but is deprecated; migrate to dot notation.

timeseries_columnobjectImmutable

Column recording time, used for point-in-time joins, backfills, and aggregations. Optional since a timeseries column is not set for RequestSource features or on-demand calculated features.

Show child attributesHide child attributes

namestring

The name of the timeseries column. For Kafka sources, use dot-prefixed path notation to reference fields within the key or value schema (e.g., "value.event_timestamp"). For nested fields, the leaf node name (e.g., "event_timestamp" from "value.event_details.event_timestamp") is what will be present in materialized tables and expected to match at query time. Colon-prefixed notation (e.g., "value:event_timestamp") is supported for backwards compatibility but is deprecated; migrate to dot notation.

catalog_namestringOutput only

Name of parent catalog.

schema_namestringOutput only

Name of parent schema relative to its parent catalog.

namestringOutput only

Name of the feature, extracted from the full three-part name (catalog.schema.name).

created_atstringOutput only

Time at which this feature was created.

created_bystringOutput only

Username of the feature creator.

View as Markdown

The Feature object

{
  "full_name": "string",
  "source": {
    "delta_table_source": {},
    "kafka_source": {},
    "request_source": {},
    "stream_source": {}
  },
  "function": {
    "aggregation_function": {},
    "column_selection": {}
  },
  "description": "string",
  "entities": [
    {
      "name": "string"
    }
  ],
  "timeseries_column": {
    "name": "string"
  },
  "catalog_name": "string",
  "schema_name": "string",
  "name": "string",
  "created_at": "string",
  "created_by": "string"
}

Get a feature GA

GET /api/2.0/feature-engineering/features/{full_name}

Get a Feature.

API scopes: mlflow

Parameters

full_namestringRequiredpath

Name of the feature to get.

Response

Returns the Feature object.

View as Markdown

Response

{
  "full_name": "string",
  "source": {
    "delta_table_source": {},
    "kafka_source": {},
    "request_source": {},
    "stream_source": {}
  },
  "function": {
    "aggregation_function": {},
    "column_selection": {}
  },
  "description": "string",
  "entities": [
    {
      "name": "string"
    }
  ],
  "timeseries_column": {
    "name": "string"
  },
  "catalog_name": "string",
  "schema_name": "string",
  "name": "string",
  "created_at": "string",
  "created_by": "string"
}

List features GA

GET /api/2.0/feature-engineering/features

List Features.

API scopes: mlflow

Parameters

page_tokenstringquery

Pagination token to go to the next page based on a previous query.

page_sizeint32query

The maximum number of results to return.

catalog_namestringRequiredquery

Name of parent catalog for features of interest.

schema_namestringRequiredquery

Name of parent schema relative to its parent catalog.

Response

Returns a list of Feature objects.

View as Markdown

Response

{
  "features": [
    {
      "full_name": "string",
      "source": {},
      "function": {},
      "description": "string",
      "entities": [
        {}
      ],
      "timeseries_column": {},
      "catalog_name": "string",
      "schema_name": "string",
      "name": "string",
      "created_at": "string",
      "created_by": "string"
    }
  ],
  "next_page_token": "string"
}

Create a feature GA

POST /api/2.0/feature-engineering/features

Create a Feature.

API scopes: mlflow

Request body

Feature to create.

full_namestringRequiredImmutable

The full three-part name (catalog, schema, name) of the feature.

sourceobjectRequiredImmutable

The data source of the feature.

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delta_table_sourceobject

A Delta table data source.

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full_namestringRequired

The full three-part (catalog, schema, table) name of the Delta table.

filter_conditionstring

Single WHERE clause to filter delta table before applying transformations. Will be row-wise evaluated, so should only include conditionals and projections.

transformation_sqlstring

A single SQL SELECT expression applied after filter_condition. Should contains all the columns needed (eg. "SELECT , col_a + col_b AS col_c FROM x.y.z WHERE col_a > 0" would have transformation_sql ", col_a + col_b AS col_c") If transformation_sql is not provided, all columns of the delta table are present in the DataSource dataframe.

Default: *

dataframe_schemastring

Schema of the resulting dataframe after transformations, in Spark StructType JSON format (from df.schema.json()). Required if transformation_sql is specified. Example: {"type":"struct","fields":[{"name":"col_a","type":"integer","nullable":true,"metadata":{}},{"name":"col_c","type":"integer","nullable":true,"metadata":{}}]}

kafka_sourceobject

A Kafka stream data source.

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namestringRequired

Name of the Kafka source, used to identify it. This is used to look up the corresponding KafkaConfig object. Can be distinct from topic name.

filter_conditionstring

The filter condition applied to the source data before aggregation.

request_sourceobject

A request-time data source.

Show child attributesHide child attributes

flat_schemaobject

A flat schema with scalar-typed fields only.

Show child attributesHide child attributes

fieldsarray of objectRequired

The list of fields in this schema.

Show child attributesHide child attributes

namestringRequired

The name of the field.

data_typestringRequired

The scalar data type of the field.

Values:

• INTEGER
• FLOAT
• BOOLEAN
• STRING
• DOUBLE
• LONG
• TIMESTAMP
• DATE
• SHORT
• BINARY
• DECIMAL

stream_sourceobject

A Stream data source.

Show child attributesHide child attributes

full_namestringRequired

Three-part full name of the Stream (catalog.schema.stream).

filter_conditionstring

The filter condition applied to the source data before aggregation.

functionobjectRequiredImmutable

The function by which the feature is computed.

Show child attributesHide child attributes

aggregation_functionobject

An aggregation function applied over a time window.

Show child attributesHide child attributes

avgobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the average is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

count_functionobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the count is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

sumobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the sum is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

minobject

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inputstringRequired

The input column from which the minimum is computed.

maxobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the maximum is computed.

firstobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the first value is returned.

lastobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the last value is returned.

approx_count_distinctobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the approximate count of distinct values is computed.

relative_sddouble

The maximum relative standard deviation allowed (default defined by Spark). Deprecated: use relative_error. When relative_error is set, reads return the same value here for clients that don't have relative_error, and a request may only send that value.

approx_percentileobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the approximate percentile is computed.

percentiledoubleRequired

The percentile value to compute (between 0 and 1).

accuracyint64

The accuracy parameter (higher is more accurate but slower). Deprecated: use relative_error. When relative_error is set, reads return ceil(1 / relative_error) here for clients that don't have relative_error, and a request may only send that value.

stddev_popobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the population standard deviation is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

stddev_sampobject

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inputstringRequired

The input column from which the sample standard deviation is computed.

var_popobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the population variance is computed.

var_sampobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the sample variance is computed.

time_windowobject

The time window over which the aggregation is computed.

Show child attributesHide child attributes

tumblingobject

Show child attributesHide child attributes

window_durationstringRequired

The duration of each tumbling window (non-overlapping, fixed-duration windows).

slidingobject

Show child attributesHide child attributes

window_durationstring

The duration of the sliding window. Must be positive when set; absent means lifetime (aggregate over the entity's entire history).

slide_durationstringRequired

The slide duration (interval by which windows advance, must be positive and less than duration).

rollingobject

Show child attributesHide child attributes

window_durationstring

The duration of the rolling window. Must be positive when set; absent means lifetime (aggregate over the entity's entire history).

delaystring

Non-negative analytic lag that evaluates the window this far in the past. Use this for timing variations unrelated to source lateness, such as a 30-day count as of one week ago. If unset, the analytic lag is zero. It composes with source.lateness when both are set.

column_selectionobject

Selects the latest value of a single column in a data source

Show child attributesHide child attributes

columnstringRequired

Column name from source to select as the feature value.

descriptionstring

The description of the feature.

entitiesarray of objectImmutable

The entity columns for the feature, used as aggregation keys and for query-time lookup. Optional since entities are not set for RequestSource features or on-demand calculated features.

Show child attributesHide child attributes

namestringRequired

The name of the entity column. For Kafka sources, use dot-prefixed path notation to reference fields within the key or value schema (e.g., "value.user_id", "key.partition_key"). For nested fields, the leaf node name (e.g., "user_id" from "value.trip_details.user_id") is what will be present in materialized tables and expected to match at query time. Colon-prefixed notation (e.g., "value:user_id") is supported for backwards compatibility but is deprecated; migrate to dot notation.

timeseries_columnobjectImmutable

Column recording time, used for point-in-time joins, backfills, and aggregations. Optional since a timeseries column is not set for RequestSource features or on-demand calculated features.

Show child attributesHide child attributes

namestringRequired

The name of the timeseries column. For Kafka sources, use dot-prefixed path notation to reference fields within the key or value schema (e.g., "value.event_timestamp"). For nested fields, the leaf node name (e.g., "event_timestamp" from "value.event_details.event_timestamp") is what will be present in materialized tables and expected to match at query time. Colon-prefixed notation (e.g., "value:event_timestamp") is supported for backwards compatibility but is deprecated; migrate to dot notation.

Response

Returns the Feature object.

View as Markdown

Request

{
  "full_name": "string",
  "source": {
    "delta_table_source": {},
    "kafka_source": {},
    "request_source": {},
    "stream_source": {}
  },
  "function": {
    "aggregation_function": {},
    "column_selection": {}
  },
  "description": "string",
  "entities": [
    {
      "name": "string"
    }
  ],
  "timeseries_column": {
    "name": "string"
  }
}

Response

{
  "full_name": "string",
  "source": {
    "delta_table_source": {},
    "kafka_source": {},
    "request_source": {},
    "stream_source": {}
  },
  "function": {
    "aggregation_function": {},
    "column_selection": {}
  },
  "description": "string",
  "entities": [
    {
      "name": "string"
    }
  ],
  "timeseries_column": {
    "name": "string"
  },
  "catalog_name": "string",
  "schema_name": "string",
  "name": "string",
  "created_at": "string",
  "created_by": "string"
}

Update a feature's description (all other fields are immutable) GA

PATCH /api/2.0/feature-engineering/features/{full_name}

Update a Feature.

API scopes: mlflow

Parameters

full_namestringRequiredImmutablepath

The full three-part name (catalog, schema, name) of the feature.

update_maskstringRequiredquery

Fields to update. The only supported path is description.

Request body

Feature whose full_name identifies the target. Only description is mutable.

sourceobjectRequiredImmutable

The data source of the feature.

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delta_table_sourceobject

A Delta table data source.

Show child attributesHide child attributes

full_namestringRequired

The full three-part (catalog, schema, table) name of the Delta table.

filter_conditionstring

Single WHERE clause to filter delta table before applying transformations. Will be row-wise evaluated, so should only include conditionals and projections.

transformation_sqlstring

A single SQL SELECT expression applied after filter_condition. Should contains all the columns needed (eg. "SELECT , col_a + col_b AS col_c FROM x.y.z WHERE col_a > 0" would have transformation_sql ", col_a + col_b AS col_c") If transformation_sql is not provided, all columns of the delta table are present in the DataSource dataframe.

Default: *

dataframe_schemastring

Schema of the resulting dataframe after transformations, in Spark StructType JSON format (from df.schema.json()). Required if transformation_sql is specified. Example: {"type":"struct","fields":[{"name":"col_a","type":"integer","nullable":true,"metadata":{}},{"name":"col_c","type":"integer","nullable":true,"metadata":{}}]}

kafka_sourceobject

A Kafka stream data source.

Show child attributesHide child attributes

namestringRequired

Name of the Kafka source, used to identify it. This is used to look up the corresponding KafkaConfig object. Can be distinct from topic name.

filter_conditionstring

The filter condition applied to the source data before aggregation.

request_sourceobject

A request-time data source.

Show child attributesHide child attributes

flat_schemaobject

A flat schema with scalar-typed fields only.

Show child attributesHide child attributes

fieldsarray of objectRequired

The list of fields in this schema.

Show child attributesHide child attributes

namestringRequired

The name of the field.

data_typestringRequired

The scalar data type of the field.

Values:

• INTEGER
• FLOAT
• BOOLEAN
• STRING
• DOUBLE
• LONG
• TIMESTAMP
• DATE
• SHORT
• BINARY
• DECIMAL

stream_sourceobject

A Stream data source.

Show child attributesHide child attributes

full_namestringRequired

Three-part full name of the Stream (catalog.schema.stream).

filter_conditionstring

The filter condition applied to the source data before aggregation.

functionobjectRequiredImmutable

The function by which the feature is computed.

Show child attributesHide child attributes

aggregation_functionobject

An aggregation function applied over a time window.

Show child attributesHide child attributes

avgobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the average is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

count_functionobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the count is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

sumobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the sum is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

minobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the minimum is computed.

maxobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the maximum is computed.

firstobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the first value is returned.

lastobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the last value is returned.

approx_count_distinctobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the approximate count of distinct values is computed.

relative_sddouble

The maximum relative standard deviation allowed (default defined by Spark). Deprecated: use relative_error. When relative_error is set, reads return the same value here for clients that don't have relative_error, and a request may only send that value.

approx_percentileobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the approximate percentile is computed.

percentiledoubleRequired

The percentile value to compute (between 0 and 1).

accuracyint64

The accuracy parameter (higher is more accurate but slower). Deprecated: use relative_error. When relative_error is set, reads return ceil(1 / relative_error) here for clients that don't have relative_error, and a request may only send that value.

stddev_popobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the population standard deviation is computed. For Kafka sources, use dot-prefixed path notation (e.g., "value.amount"). For nested fields, the leaf node name is used. Colon-prefixed notation (e.g., "value:amount") is supported for backwards compatibility but is deprecated; migrate to dot notation.

stddev_sampobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the sample standard deviation is computed.

var_popobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the population variance is computed.

var_sampobject

Show child attributesHide child attributes

inputstringRequired

The input column from which the sample variance is computed.

time_windowobject

The time window over which the aggregation is computed.

Show child attributesHide child attributes

tumblingobject

Show child attributesHide child attributes

window_durationstringRequired

The duration of each tumbling window (non-overlapping, fixed-duration windows).

slidingobject

Show child attributesHide child attributes

window_durationstring

The duration of the sliding window. Must be positive when set; absent means lifetime (aggregate over the entity's entire history).

slide_durationstringRequired

The slide duration (interval by which windows advance, must be positive and less than duration).

rollingobject

Show child attributesHide child attributes

window_durationstring

The duration of the rolling window. Must be positive when set; absent means lifetime (aggregate over the entity's entire history).

delaystring

Non-negative analytic lag that evaluates the window this far in the past. Use this for timing variations unrelated to source lateness, such as a 30-day count as of one week ago. If unset, the analytic lag is zero. It composes with source.lateness when both are set.

column_selectionobject

Selects the latest value of a single column in a data source

Show child attributesHide child attributes

columnstringRequired

Column name from source to select as the feature value.

descriptionstring

The description of the feature.

entitiesarray of objectImmutable

The entity columns for the feature, used as aggregation keys and for query-time lookup. Optional since entities are not set for RequestSource features or on-demand calculated features.

Show child attributesHide child attributes

namestringRequired

The name of the entity column. For Kafka sources, use dot-prefixed path notation to reference fields within the key or value schema (e.g., "value.user_id", "key.partition_key"). For nested fields, the leaf node name (e.g., "user_id" from "value.trip_details.user_id") is what will be present in materialized tables and expected to match at query time. Colon-prefixed notation (e.g., "value:user_id") is supported for backwards compatibility but is deprecated; migrate to dot notation.

timeseries_columnobjectImmutable

Column recording time, used for point-in-time joins, backfills, and aggregations. Optional since a timeseries column is not set for RequestSource features or on-demand calculated features.

Show child attributesHide child attributes

namestringRequired

The name of the timeseries column. For Kafka sources, use dot-prefixed path notation to reference fields within the key or value schema (e.g., "value.event_timestamp"). For nested fields, the leaf node name (e.g., "event_timestamp" from "value.event_details.event_timestamp") is what will be present in materialized tables and expected to match at query time. Colon-prefixed notation (e.g., "value:event_timestamp") is supported for backwards compatibility but is deprecated; migrate to dot notation.

Response

Returns the Feature object.

View as Markdown

Request

{
  "source": {
    "delta_table_source": {},
    "kafka_source": {},
    "request_source": {},
    "stream_source": {}
  },
  "function": {
    "aggregation_function": {},
    "column_selection": {}
  },
  "description": "string",
  "entities": [
    {
      "name": "string"
    }
  ],
  "timeseries_column": {
    "name": "string"
  }
}

Response

{
  "full_name": "string",
  "source": {
    "delta_table_source": {},
    "kafka_source": {},
    "request_source": {},
    "stream_source": {}
  },
  "function": {
    "aggregation_function": {},
    "column_selection": {}
  },
  "description": "string",
  "entities": [
    {
      "name": "string"
    }
  ],
  "timeseries_column": {
    "name": "string"
  },
  "catalog_name": "string",
  "schema_name": "string",
  "name": "string",
  "created_at": "string",
  "created_by": "string"
}

Delete a feature GA

DELETE /api/2.0/feature-engineering/features/{full_name}

Delete a Feature.

API scopes: mlflow

Parameters

full_namestringRequiredpath

Name of the feature to delete.

View as Markdown

Response

{}