Skip to content

CreateDataLakeDatasetRequest

Source code in docs_src/capo_supplychain/types/create_data_lake_dataset_request.py 
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
class CreateDataLakeDatasetRequest(TypedDict, closed=True):
    instance_id: "capo_supplychain.types.uuid.UUID"
    """<p>The Amazon Web Services Supply Chain instance identifier.</p>"""
    namespace: "capo_supplychain.types.data_lake_namespace_name.DataLakeNamespaceName"
    """<p>The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:</p> <ul> <li> <p> <b>asc</b> - For information on the Amazon Web Services Supply Chain supported datasets see <a href="https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html">https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html</a>.</p> </li> <li> <p> <b>default</b> - For datasets with custom user-defined schemas.</p> </li> </ul>"""
    name: "capo_supplychain.types.data_lake_dataset_name.DataLakeDatasetName"
    """<p>The name of the dataset. For <b>asc</b> name space, the name must be one of the supported data entities under <a href="https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html">https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html</a>.</p>"""
    schema: NotRequired[
        "capo_supplychain.types.data_lake_dataset_schema.DataLakeDatasetSchema"
    ]
    """<p>The custom schema of the data lake dataset and required for dataset in <b>default</b> and custom namespaces.</p>"""
    description: NotRequired[
        "capo_supplychain.types.data_lake_dataset_description.DataLakeDatasetDescription"
    ]
    """<p>The description of the dataset.</p>"""
    partition_spec: NotRequired[
        "capo_supplychain.types.data_lake_dataset_partition_spec.DataLakeDatasetPartitionSpec"
    ]
    """<p>The partition specification of the dataset. Partitioning can effectively improve the dataset query performance by reducing the amount of data scanned during query execution. But partitioning or not will affect how data get ingested by data ingestion methods, such as SendDataIntegrationEvent's dataset UPSERT will upsert records within partition (instead of within whole dataset). For more details, refer to those data ingestion documentations.</p>"""
    tags: NotRequired["capo_supplychain.types.tag_map.TagMap"]
    """<p>The tags of the dataset.</p>"""

description instance-attribute 

description: NotRequired[DataLakeDatasetDescription]

The description of the dataset.

instance_id instance-attribute 

instance_id: UUID

The Amazon Web Services Supply Chain instance identifier.

name instance-attribute 

name: DataLakeDatasetName

The name of the dataset. For asc name space, the name must be one of the supported data entities under https://docs.aws.amazon.com/aws-supply-chain/latest/userguide/data-model-asc.html.

namespace instance-attribute 

namespace: DataLakeNamespaceName

The namespace of the dataset, besides the custom defined namespace, every instance comes with below pre-defined namespaces:

partition_spec instance-attribute 

partition_spec: NotRequired[DataLakeDatasetPartitionSpec]

The partition specification of the dataset. Partitioning can effectively improve the dataset query performance by reducing the amount of data scanned during query execution. But partitioning or not will affect how data get ingested by data ingestion methods, such as SendDataIntegrationEvent's dataset UPSERT will upsert records within partition (instead of within whole dataset). For more details, refer to those data ingestion documentations.

schema instance-attribute 

schema: NotRequired[DataLakeDatasetSchema]

The custom schema of the data lake dataset and required for dataset in default and custom namespaces.

tags instance-attribute 

tags: NotRequired[TagMap]

The tags of the dataset.