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ml_input_channels

Creates, updates, deletes, gets or lists a ml_input_channels resource.

Overview​

Nameml_input_channels
TypeResource
Idaws.cleanroomsml.ml_input_channels

Fields​

The following fields are returned by SELECT queries:

NameDatatypeDescription
namestringThe name of the ML input channel. (pattern: <code>(?!\s*$)[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDBFF-\uDC00\uDFFF\t]*</code>)
collaboration_identifierstringThe collaboration ID of the collaboration that contains the ML input channel. (pattern: <code>[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}</code>)
configured_model_algorithm_associationsarrayThe configured model algorithm associations that were used to create the ML input channel.
create_timestring (date-time)The time at which the ML input channel was created.
descriptionstringThe description of the ML input channel. (pattern: <code>[\u0020-\uD7FF\uE000-\uFFFD\uD800\uDBFF-\uDC00\uDFFF\t\r\n]*</code>)
input_channelobjectProvides information about the data source that is used to create an ML input channel.
kms_key_arnstringThe Amazon Resource Name (ARN) of the KMS key that was used to create the ML input channel. (pattern: <code>arn:aws[-a-z]*:kms:[-a-z0-9]+:[0-9]{12}:key/.+</code>)
membership_identifierstringThe membership ID of the membership that contains the ML input channel. (pattern: <code>[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}</code>)
ml_input_channel_arnstringThe Amazon Resource Name (ARN) of the ML input channel. (pattern: <code>arn:aws[-a-z]*:cleanrooms-ml:[-a-z0-9]+:[0-9]{12}:membership/[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}/ml-input-channel/[-a-zA-Z0-9_/.]+</code>)
number_of_filesnumber (double)The number of files in the ML input channel.
number_of_recordsinteger (int64)The number of records in the ML input channel.
payer_configurationobjectSpecifies which member accounts are responsible for paying for compute and synthetic data generation costs in a Clean Rooms ML collaboration.
privacy_budgetsobjectReturns the privacy budgets that control access to this Clean Rooms ML input channel. Use these budgets to monitor and limit resource consumption over specified time periods.
protected_query_identifierstringThe ID of the protected query that was used to create the ML input channel. (pattern: <code>[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}</code>)
retention_in_daysintegerThe number of days to keep the data in the ML input channel.
size_in_gbnumber (double)The size, in GB, of the ML input channel.
statusstringThe status of the ML input channel. (CREATE_PENDING, CREATE_IN_PROGRESS, CREATE_FAILED, ACTIVE, DELETE_PENDING, DELETE_IN_PROGRESS, DELETE_FAILED, INACTIVE)
status_detailsobjectDetails about the status of a resource.
synthetic_data_configurationobjectThe synthetic data configuration for this ML input channel, including parameters for generating privacy-preserving synthetic data and evaluation scores for measuring the privacy of the generated data.
tagsobjectThe optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. The following basic restrictions apply to tags: Maximum number of tags per resource - 50. For each resource, each tag key must be unique, and each tag key can have only one value. Maximum key length - 128 Unicode characters in UTF-8. Maximum value length - 256 Unicode characters in UTF-8. If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @. Tag keys and values are case sensitive. Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.
update_timestring (date-time)The most recent time at which the ML input channel was updated.

Methods​

The following methods are available for this resource:

NameAccessible byRequired ParamsOptional ParamsDescription
get_ml_input_channelselectml_input_channel_arn, membership_identifier, regionReturns information about an ML input channel.
list_ml_input_channelsselectmembership_identifier, regionnextToken, maxResultsReturns a list of ML input channels.
create_ml_input_channelinsertmembership_identifier, region, configuredModelAlgorithmAssociations, inputChannel, name, retentionInDaysProvides the information to create an ML input channel. An ML input channel is the result of a query that can be used for ML modeling.
delete_ml_input_channel_datadeleteml_input_channel_arn, membership_identifier, regionProvides the information necessary to delete an ML input channel.

Parameters​

Parameters can be passed in the WHERE clause of a query. Check the Methods section to see which parameters are required or optional for each operation.

NameDatatypeDescription
membership_identifierstringThe membership ID of the membership that contains the ML input channel you want to delete.
ml_input_channel_arnstringThe Amazon Resource Name (ARN) of the ML input channel that you want to delete.
regionstringAWS region (default: us-east-1)
maxResultsintegerThe maximum number of ML input channels to return.
nextTokenstringThe token value retrieved from a previous call to access the next page of results.

SELECT examples​

Returns information about an ML input channel.

SELECT
name,
collaboration_identifier,
configured_model_algorithm_associations,
create_time,
description,
input_channel,
kms_key_arn,
membership_identifier,
ml_input_channel_arn,
number_of_files,
number_of_records,
payer_configuration,
privacy_budgets,
protected_query_identifier,
retention_in_days,
size_in_gb,
status,
status_details,
synthetic_data_configuration,
tags,
update_time
FROM aws.cleanroomsml.ml_input_channels
WHERE ml_input_channel_arn = '{{ ml_input_channel_arn }}' -- required
AND membership_identifier = '{{ membership_identifier }}' -- required
AND region = '{{ region }}' -- required
;

INSERT examples​

Provides the information to create an ML input channel. An ML input channel is the result of a query that can be used for ML modeling.

INSERT INTO aws.cleanroomsml.ml_input_channels (
configuredModelAlgorithmAssociations,
inputChannel,
name,
retentionInDays,
description,
kmsKeyArn,
tags,
payerConfiguration,
membership_identifier,
region
)
SELECT 
'{{ configuredModelAlgorithmAssociations }}' /* required */,
'{{ inputChannel }}' /* required */,
'{{ name }}' /* required */,
{{ retentionInDays }} /* required */,
'{{ description }}',
'{{ kmsKeyArn }}',
'{{ tags }}',
'{{ payerConfiguration }}',
'{{ membership_identifier }}',
'{{ region }}'
RETURNING
ml_input_channel_arn
;

DELETE examples​

Provides the information necessary to delete an ML input channel.

DELETE FROM aws.cleanroomsml.ml_input_channels
WHERE ml_input_channel_arn = '{{ ml_input_channel_arn }}' --required
AND membership_identifier = '{{ membership_identifier }}' --required
AND region = '{{ region }}' --required
;
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