databricks.getFeatureEngineeringKafkaConfigs

func GetFeatureEngineeringKafkaConfigs(ctx *Context, args *GetFeatureEngineeringKafkaConfigsArgs, opts ...InvokeOption) (*GetFeatureEngineeringKafkaConfigsResult, error)
func GetFeatureEngineeringKafkaConfigsOutput(ctx *Context, args *GetFeatureEngineeringKafkaConfigsOutputArgs, opts ...InvokeOption) GetFeatureEngineeringKafkaConfigsResultOutput

> Note: This function is named GetFeatureEngineeringKafkaConfigs in the Go SDK.

PageSize int

The maximum number of results to return

ProviderConfig GetFeatureEngineeringKafkaConfigsProviderConfig

Configure the provider for management through account provider.

PageSize int

The maximum number of results to return

ProviderConfig GetFeatureEngineeringKafkaConfigsProviderConfig

Configure the provider for management through account provider.

page_size number

The maximum number of results to return

provider_config object

Configure the provider for management through account provider.

pageSize Integer

The maximum number of results to return

providerConfig GetFeatureEngineeringKafkaConfigsProviderConfig

Configure the provider for management through account provider.

pageSize number

The maximum number of results to return

providerConfig GetFeatureEngineeringKafkaConfigsProviderConfig

Configure the provider for management through account provider.

page_size int

The maximum number of results to return

provider_config GetFeatureEngineeringKafkaConfigsProviderConfig

Configure the provider for management through account provider.

pageSize Number

The maximum number of results to return

providerConfig Property Map

Configure the provider for management through account provider.

Id string

The provider-assigned unique ID for this managed resource.

KafkaConfigs List<GetFeatureEngineeringKafkaConfigsKafkaConfig>

PageSize int

ProviderConfig GetFeatureEngineeringKafkaConfigsProviderConfig

Id string

The provider-assigned unique ID for this managed resource.

KafkaConfigs []GetFeatureEngineeringKafkaConfigsKafkaConfig

PageSize int

ProviderConfig GetFeatureEngineeringKafkaConfigsProviderConfig

id string

The provider-assigned unique ID for this managed resource.

kafka_configs list(object)

page_size number

provider_config object

id String

The provider-assigned unique ID for this managed resource.

kafkaConfigs List<GetFeatureEngineeringKafkaConfigsKafkaConfig>

pageSize Integer

providerConfig GetFeatureEngineeringKafkaConfigsProviderConfig

id string

The provider-assigned unique ID for this managed resource.

kafkaConfigs GetFeatureEngineeringKafkaConfigsKafkaConfig[]

pageSize number

providerConfig GetFeatureEngineeringKafkaConfigsProviderConfig

id str

The provider-assigned unique ID for this managed resource.

kafka_configs Sequence[GetFeatureEngineeringKafkaConfigsKafkaConfig]

page_size int

provider_config GetFeatureEngineeringKafkaConfigsProviderConfig

id String

The provider-assigned unique ID for this managed resource.

kafkaConfigs List<Property Map>

pageSize Number

providerConfig Property Map

AuthConfig GetFeatureEngineeringKafkaConfigsKafkaConfigAuthConfig

(AuthConfig) - Authentication configuration for connection to topics

BackfillSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSource

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

BootstrapServers string

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

ExtraOptions Dictionary<string, string>

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

KeySchema GetFeatureEngineeringKafkaConfigsKafkaConfigKeySchema

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

Name string

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

SubscriptionMode GetFeatureEngineeringKafkaConfigsKafkaConfigSubscriptionMode

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

ValueSchema GetFeatureEngineeringKafkaConfigsKafkaConfigValueSchema

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

ProviderConfig GetFeatureEngineeringKafkaConfigsKafkaConfigProviderConfig

Configure the provider for management through account provider.

AuthConfig GetFeatureEngineeringKafkaConfigsKafkaConfigAuthConfig

(AuthConfig) - Authentication configuration for connection to topics

BackfillSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSource

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

BootstrapServers string

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

ExtraOptions map[string]string

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

KeySchema GetFeatureEngineeringKafkaConfigsKafkaConfigKeySchema

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

Name string

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

SubscriptionMode GetFeatureEngineeringKafkaConfigsKafkaConfigSubscriptionMode

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

ValueSchema GetFeatureEngineeringKafkaConfigsKafkaConfigValueSchema

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

ProviderConfig GetFeatureEngineeringKafkaConfigsKafkaConfigProviderConfig

Configure the provider for management through account provider.

auth_config object

(AuthConfig) - Authentication configuration for connection to topics

backfill_source object

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

bootstrap_servers string

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

extra_options map(string)

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

key_schema object

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

name string

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

subscription_mode object

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

value_schema object

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

provider_config object

Configure the provider for management through account provider.

authConfig GetFeatureEngineeringKafkaConfigsKafkaConfigAuthConfig

(AuthConfig) - Authentication configuration for connection to topics

backfillSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSource

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

bootstrapServers String

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

extraOptions Map<String,String>

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

keySchema GetFeatureEngineeringKafkaConfigsKafkaConfigKeySchema

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

name String

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

subscriptionMode GetFeatureEngineeringKafkaConfigsKafkaConfigSubscriptionMode

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

valueSchema GetFeatureEngineeringKafkaConfigsKafkaConfigValueSchema

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

providerConfig GetFeatureEngineeringKafkaConfigsKafkaConfigProviderConfig

Configure the provider for management through account provider.

authConfig GetFeatureEngineeringKafkaConfigsKafkaConfigAuthConfig

(AuthConfig) - Authentication configuration for connection to topics

backfillSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSource

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

bootstrapServers string

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

extraOptions {[key: string]: string}

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

keySchema GetFeatureEngineeringKafkaConfigsKafkaConfigKeySchema

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

name string

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

subscriptionMode GetFeatureEngineeringKafkaConfigsKafkaConfigSubscriptionMode

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

valueSchema GetFeatureEngineeringKafkaConfigsKafkaConfigValueSchema

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

providerConfig GetFeatureEngineeringKafkaConfigsKafkaConfigProviderConfig

Configure the provider for management through account provider.

auth_config GetFeatureEngineeringKafkaConfigsKafkaConfigAuthConfig

(AuthConfig) - Authentication configuration for connection to topics

backfill_source GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSource

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

bootstrap_servers str

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

extra_options Mapping[str, str]

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

key_schema GetFeatureEngineeringKafkaConfigsKafkaConfigKeySchema

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

name str

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

subscription_mode GetFeatureEngineeringKafkaConfigsKafkaConfigSubscriptionMode

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

value_schema GetFeatureEngineeringKafkaConfigsKafkaConfigValueSchema

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

provider_config GetFeatureEngineeringKafkaConfigsKafkaConfigProviderConfig

Configure the provider for management through account provider.

authConfig Property Map

(AuthConfig) - Authentication configuration for connection to topics

backfillSource Property Map

(BackfillSource) - A user-provided and managed source for backfilling data. Historical data is used when creating a training set from streaming features linked to this Kafka config. In the future, a separate table will be maintained by Databricks for forward filling data. The schema for this source must match exactly that of the key and value schemas specified for this Kafka config

bootstrapServers String

(string) - A comma-separated list of host/port pairs pointing to Kafka cluster

extraOptions Map<String>

(object) - Catch-all for miscellaneous options. Keys should be source options or Kafka consumer options (kafka.*)

keySchema Property Map

(SchemaConfig) - Schema configuration for extracting message keys from topics. At least one of keySchema and valueSchema must be provided

name String

(string) - Name that uniquely identifies this Kafka config within the metastore. This will be the identifier used from the Feature object to reference these configs for a feature. Can be distinct from topic name

subscriptionMode Property Map

(SubscriptionMode) - Options to configure which Kafka topics to pull data from

valueSchema Property Map

(SchemaConfig) - Schema configuration for extracting message values from topics. At least one of keySchema and valueSchema must be provided

providerConfig Property Map

Configure the provider for management through account provider.

UcServiceCredentialName string

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

UcServiceCredentialName string

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

uc_service_credential_name string

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

ucServiceCredentialName String

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

ucServiceCredentialName string

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

uc_service_credential_name str

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

ucServiceCredentialName String

(string) - Name of the Unity Catalog service credential. This value will be set under the option databricks.serviceCredential

DeltaTableName string

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

DeltaTableSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSourceDeltaTableSource

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

DeltaTableName string

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

DeltaTableSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSourceDeltaTableSource

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

delta_table_name string

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

delta_table_source object

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

deltaTableName String

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

deltaTableSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSourceDeltaTableSource

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

deltaTableName string

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

deltaTableSource GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSourceDeltaTableSource

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

delta_table_name str

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

delta_table_source GetFeatureEngineeringKafkaConfigsKafkaConfigBackfillSourceDeltaTableSource

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

deltaTableName String

(string) - The full three-part name (catalog, schema, name) of the Delta table containing the historical data to backfill

deltaTableSource Property Map

(DeltaTableSource, deprecated) - Deprecated: Use deltaTableName instead. Kept for backwards compatibility. The Delta table source containing the historical data to backfill. Only the delta table name is used for backfill, other fields are ignored

FullName string

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

DataframeSchema string

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

EntityColumns List<string>

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

FilterCondition string

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

TimeseriesColumn string

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

TransformationSql string

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

FullName string

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

DataframeSchema string

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

EntityColumns []string

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

FilterCondition string

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

TimeseriesColumn string

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

TransformationSql string

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

full_name string

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

dataframe_schema string

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

entity_columns list(string)

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

filter_condition string

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

timeseries_column string

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

transformation_sql string

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

fullName String

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

dataframeSchema String

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

entityColumns List<String>

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

filterCondition String

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

timeseriesColumn String

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

transformationSql String

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

fullName string

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

dataframeSchema string

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

entityColumns string[]

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

filterCondition string

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

timeseriesColumn string

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

transformationSql string

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

full_name str

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

dataframe_schema str

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

entity_columns Sequence[str]

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

filter_condition str

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

timeseries_column str

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

transformation_sql str

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

fullName String

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

dataframeSchema String

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

entityColumns List<String>

(list of string, deprecated) - Deprecated: Use Feature.entity instead. Kept for backwards compatibility. The entity columns of the Delta table

filterCondition String

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

timeseriesColumn String

(string, deprecated) - Deprecated: Use Feature.timeseries_column instead. Kept for backwards compatibility. The timeseries column of the Delta table

transformationSql String

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

JsonSchema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

JsonSchema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

json_schema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

jsonSchema String

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

jsonSchema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

json_schema str

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

jsonSchema String

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

WorkspaceId string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

WorkspaceId string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspace_id string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspaceId String

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspaceId string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspace_id str

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspaceId String

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

Assign string

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

Subscribe string

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

SubscribePattern string

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

Assign string

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

Subscribe string

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

SubscribePattern string

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

assign string

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

subscribe string

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

subscribe_pattern string

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

assign String

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

subscribe String

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

subscribePattern String

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

assign string

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

subscribe string

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

subscribePattern string

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

assign str

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

subscribe str

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

subscribe_pattern str

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

assign String

(string) - A JSON string that contains the specific topic-partitions to consume from. For example, for '{"topicA":[0,1],"topicB":[2,4]}', topicA's 0'th and 1st partitions will be consumed from

subscribe String

(string) - A comma-separated list of Kafka topics to read from. For example, 'topicA,topicB,topicC'

subscribePattern String

(string) - A regular expression matching topics to subscribe to. For example, 'topic.*' will subscribe to all topics starting with 'topic'

JsonSchema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

JsonSchema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

json_schema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

jsonSchema String

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

jsonSchema string

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

json_schema str

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

jsonSchema String

(string) - Schema of the JSON object in standard IETF JSON schema format (https://json-schema.org/)

WorkspaceId string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

WorkspaceId string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspace_id string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspaceId String

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspaceId string

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspace_id str

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.

workspaceId String

Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with.