Returns information about Amazon DocumentDB global clusters. This API supports pagination.
This action only applies to Amazon DocumentDB clusters.
Parameters:
-
global_cluster_identifier
(Optional[GlobalClusterIdentifier], default:
None
)
–
The user-supplied cluster identifier. If this parameter is specified, information from only the specific cluster is returned. This parameter isn't case-sensitive.
-
filters
(Optional[FilterList], default:
None
)
–
A filter that specifies one or more global DB clusters to describe.
Supported filters: db-cluster-id accepts cluster identifiers and cluster Amazon Resource Names (ARNs). The results list will only include information about the clusters identified by these ARNs.
-
max_records
(Optional[IntegerOptional], default:
None
)
–
The maximum number of records to include in the response. If more records exist than the specified MaxRecords value, a pagination token called a marker is included in the response so that you can retrieve the remaining results.
-
marker
(Optional[String], default:
None
)
–
An optional pagination token provided by a previous DescribeGlobalClusters request. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by MaxRecords.
Raises:
Source code in docs_src/capo_docdb/_services/doc_db.py
| def describe_global_clusters(
self,
*,
config_overrides: Optional[DocDBClientConfig] = None,
global_cluster_identifier: Optional[
"capo_docdb.types.global_cluster_identifier.GlobalClusterIdentifier"
] = None,
filters: Optional["capo_docdb.types.filter_list.FilterList"] = None,
max_records: Optional[
"capo_docdb.types.integer_optional.IntegerOptional"
] = None,
marker: Optional["capo_docdb.types.string.String"] = None,
) -> "capo_docdb.types.global_clusters_message.GlobalClustersMessage":
"""<p>Returns information about Amazon DocumentDB global clusters. This API supports pagination.</p> <note> <p>This action only applies to Amazon DocumentDB clusters.</p> </note>
Args:
global_cluster_identifier: <p>The user-supplied cluster identifier. If this parameter is specified, information from only the specific cluster is returned. This parameter isn't case-sensitive.</p>
filters: <p>A filter that specifies one or more global DB clusters to describe.</p> <p>Supported filters: <code>db-cluster-id</code> accepts cluster identifiers and cluster Amazon Resource Names (ARNs). The results list will only include information about the clusters identified by these ARNs.</p>
max_records: <p>The maximum number of records to include in the response. If more records exist than the specified <code>MaxRecords</code> value, a pagination token called a marker is included in the response so that you can retrieve the remaining results. </p>
marker: <p>An optional pagination token provided by a previous <code>DescribeGlobalClusters</code> request. If this parameter is specified, the response includes only records beyond the marker, up to the value specified by <code>MaxRecords</code>.</p>
Raises:
capo_docdb.errors.global_cluster_not_found_fault.GlobalClusterNotFoundFault: <p>The <code>GlobalClusterIdentifier</code> doesn't refer to an existing global cluster.</p>
capo_docdb.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_docdb.types.describe_global_clusters_message.DescribeGlobalClustersMessage]",
) -> OperationResponse[
"capo_docdb.types.global_clusters_message.GlobalClustersMessage"
]:
import capo_docdb._operations.amazon_rd_sv19.describe_global_clusters
output, http_response = (
capo_docdb._operations.amazon_rd_sv19.describe_global_clusters.describe_global_clusters(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("DescribeGlobalClusters")
)
input_: capo_docdb.types.describe_global_clusters_message.DescribeGlobalClustersMessage = {}
if global_cluster_identifier is not None:
input_["global_cluster_identifier"] = global_cluster_identifier
if filters is not None:
input_["filters"] = filters
if max_records is not None:
input_["max_records"] = max_records
if marker is not None:
input_["marker"] = marker
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|