Values.DataLakeDatasetSchemaSourceThe schema details of the dataset. Note that for AWS Supply Chain dataset under asc namespace, it may have internal fields like connection_id that will be auto populated by data ingestion methods.
type nonrec t = {name : DataLakeDatasetSchemaName.t;The name of the dataset schema.
*)fields : DataLakeDatasetSchemaFieldList.t;The list of field details of the dataset schema.
*)primaryKeys : DataLakeDatasetPrimaryKeyFieldList.t option;The list of primary key fields for the dataset. Primary keys defined can help data ingestion methods to ensure data uniqueness: CreateDataIntegrationFlow's dedupe strategy will leverage primary keys to perform records deduplication before write to dataset; SendDataIntegrationEvent's UPSERT and DELETE can only work with dataset with primary keys. For more details, refer to those data ingestion documentations. Note that defining primary keys does not necessarily mean the dataset cannot have duplicate records, duplicate records can still be ingested if CreateDataIntegrationFlow's dedupe disabled or through SendDataIntegrationEvent's APPEND operation.
*)}val make :
?primaryKeys:??? ->
name:DataLakeDatasetSchemaName.t ->
fields:DataLakeDatasetSchemaFieldList.t ->
unit ->
tval to_value :
t ->
[> `Structure of
(string
* [> `List of
[> `Structure of
(string
* [> `Boolean of Boolean.t
| `Enum of string
| `String of DataLakeDatasetSchemaFieldName.t ])
list ]
list
| `String of DataLakeDatasetSchemaName.t ])
list ]