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src/aws_cleanroomsml.erl
%% WARNING: DO NOT EDIT, AUTO-GENERATED CODE!
%% See https://github.com/aws-beam/aws-codegen for more details.
%% @doc Welcome to the Amazon Web Services Clean Rooms ML API Reference.
%%
%% Amazon Web Services Clean Rooms ML provides a privacy-enhancing method for
%% two parties to identify similar users in their data without the need to
%% share their data with each other. The first party brings the training data
%% to Clean Rooms so that they can create and configure an audience model
%% (lookalike model) and associate it with a collaboration. The second party
%% then brings their seed data to Clean Rooms and generates an audience
%% (lookalike segment) that resembles the training data.
%%
%% To learn more about Amazon Web Services Clean Rooms ML concepts,
%% procedures, and best practices, see the Clean Rooms User Guide.
%%
%% To learn more about SQL commands, functions, and conditions supported in
%% Clean Rooms, see the Clean Rooms SQL Reference.
-module(aws_cleanroomsml).
-export([create_audience_model/2,
create_audience_model/3,
create_configured_audience_model/2,
create_configured_audience_model/3,
create_training_dataset/2,
create_training_dataset/3,
delete_audience_generation_job/3,
delete_audience_generation_job/4,
delete_audience_model/3,
delete_audience_model/4,
delete_configured_audience_model/3,
delete_configured_audience_model/4,
delete_configured_audience_model_policy/3,
delete_configured_audience_model_policy/4,
delete_training_dataset/3,
delete_training_dataset/4,
get_audience_generation_job/2,
get_audience_generation_job/4,
get_audience_generation_job/5,
get_audience_model/2,
get_audience_model/4,
get_audience_model/5,
get_configured_audience_model/2,
get_configured_audience_model/4,
get_configured_audience_model/5,
get_configured_audience_model_policy/2,
get_configured_audience_model_policy/4,
get_configured_audience_model_policy/5,
get_training_dataset/2,
get_training_dataset/4,
get_training_dataset/5,
list_audience_export_jobs/1,
list_audience_export_jobs/3,
list_audience_export_jobs/4,
list_audience_generation_jobs/1,
list_audience_generation_jobs/3,
list_audience_generation_jobs/4,
list_audience_models/1,
list_audience_models/3,
list_audience_models/4,
list_configured_audience_models/1,
list_configured_audience_models/3,
list_configured_audience_models/4,
list_tags_for_resource/2,
list_tags_for_resource/4,
list_tags_for_resource/5,
list_training_datasets/1,
list_training_datasets/3,
list_training_datasets/4,
put_configured_audience_model_policy/3,
put_configured_audience_model_policy/4,
start_audience_export_job/2,
start_audience_export_job/3,
start_audience_generation_job/2,
start_audience_generation_job/3,
tag_resource/3,
tag_resource/4,
untag_resource/3,
untag_resource/4,
update_configured_audience_model/3,
update_configured_audience_model/4]).
-include_lib("hackney/include/hackney_lib.hrl").
%%====================================================================
%% API
%%====================================================================
%% @doc Defines the information necessary to create an audience model.
%%
%% An audience model is a machine learning model that Clean Rooms ML trains
%% to measure similarity between users. Clean Rooms ML manages training and
%% storing the audience model. The audience model can be used in multiple
%% calls to the `StartAudienceGenerationJob' API.
create_audience_model(Client, Input) ->
create_audience_model(Client, Input, []).
create_audience_model(Client, Input0, Options0) ->
Method = post,
Path = ["/audience-model"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Defines the information necessary to create a configured audience
%% model.
create_configured_audience_model(Client, Input) ->
create_configured_audience_model(Client, Input, []).
create_configured_audience_model(Client, Input0, Options0) ->
Method = post,
Path = ["/configured-audience-model"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Defines the information necessary to create a training dataset, or
%% seed audience.
%%
%% In Clean Rooms ML, the `TrainingDataset' is metadata that points to a
%% Glue table, which is read only during `AudienceModel' creation.
create_training_dataset(Client, Input) ->
create_training_dataset(Client, Input, []).
create_training_dataset(Client, Input0, Options0) ->
Method = post,
Path = ["/training-dataset"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Deletes the specified audience generation job, and removes all data
%% associated with the job.
delete_audience_generation_job(Client, AudienceGenerationJobArn, Input) ->
delete_audience_generation_job(Client, AudienceGenerationJobArn, Input, []).
delete_audience_generation_job(Client, AudienceGenerationJobArn, Input0, Options0) ->
Method = delete,
Path = ["/audience-generation-job/", aws_util:encode_uri(AudienceGenerationJobArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Specifies an audience model that you want to delete.
%%
%% You can't delete an audience model if there are any configured
%% audience models that depend on the audience model.
delete_audience_model(Client, AudienceModelArn, Input) ->
delete_audience_model(Client, AudienceModelArn, Input, []).
delete_audience_model(Client, AudienceModelArn, Input0, Options0) ->
Method = delete,
Path = ["/audience-model/", aws_util:encode_uri(AudienceModelArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Deletes the specified configured audience model.
%%
%% You can't delete a configured audience model if there are any
%% lookalike models that use the configured audience model. If you delete a
%% configured audience model, it will be removed from any collaborations that
%% it is associated to.
delete_configured_audience_model(Client, ConfiguredAudienceModelArn, Input) ->
delete_configured_audience_model(Client, ConfiguredAudienceModelArn, Input, []).
delete_configured_audience_model(Client, ConfiguredAudienceModelArn, Input0, Options0) ->
Method = delete,
Path = ["/configured-audience-model/", aws_util:encode_uri(ConfiguredAudienceModelArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Deletes the specified configured audience model policy.
delete_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, Input) ->
delete_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, Input, []).
delete_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, Input0, Options0) ->
Method = delete,
Path = ["/configured-audience-model/", aws_util:encode_uri(ConfiguredAudienceModelArn), "/policy"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Specifies a training dataset that you want to delete.
%%
%% You can't delete a training dataset if there are any audience models
%% that depend on the training dataset. In Clean Rooms ML, the
%% `TrainingDataset' is metadata that points to a Glue table, which is
%% read only during `AudienceModel' creation. This action deletes the
%% metadata.
delete_training_dataset(Client, TrainingDatasetArn, Input) ->
delete_training_dataset(Client, TrainingDatasetArn, Input, []).
delete_training_dataset(Client, TrainingDatasetArn, Input0, Options0) ->
Method = delete,
Path = ["/training-dataset/", aws_util:encode_uri(TrainingDatasetArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Returns information about an audience generation job.
get_audience_generation_job(Client, AudienceGenerationJobArn)
when is_map(Client) ->
get_audience_generation_job(Client, AudienceGenerationJobArn, #{}, #{}).
get_audience_generation_job(Client, AudienceGenerationJobArn, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
get_audience_generation_job(Client, AudienceGenerationJobArn, QueryMap, HeadersMap, []).
get_audience_generation_job(Client, AudienceGenerationJobArn, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/audience-generation-job/", aws_util:encode_uri(AudienceGenerationJobArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query_ = [],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns information about an audience model
get_audience_model(Client, AudienceModelArn)
when is_map(Client) ->
get_audience_model(Client, AudienceModelArn, #{}, #{}).
get_audience_model(Client, AudienceModelArn, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
get_audience_model(Client, AudienceModelArn, QueryMap, HeadersMap, []).
get_audience_model(Client, AudienceModelArn, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/audience-model/", aws_util:encode_uri(AudienceModelArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query_ = [],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns information about a specified configured audience model.
get_configured_audience_model(Client, ConfiguredAudienceModelArn)
when is_map(Client) ->
get_configured_audience_model(Client, ConfiguredAudienceModelArn, #{}, #{}).
get_configured_audience_model(Client, ConfiguredAudienceModelArn, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
get_configured_audience_model(Client, ConfiguredAudienceModelArn, QueryMap, HeadersMap, []).
get_configured_audience_model(Client, ConfiguredAudienceModelArn, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/configured-audience-model/", aws_util:encode_uri(ConfiguredAudienceModelArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query_ = [],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns information about a configured audience model policy.
get_configured_audience_model_policy(Client, ConfiguredAudienceModelArn)
when is_map(Client) ->
get_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, #{}, #{}).
get_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
get_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, QueryMap, HeadersMap, []).
get_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/configured-audience-model/", aws_util:encode_uri(ConfiguredAudienceModelArn), "/policy"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query_ = [],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns information about a training dataset.
get_training_dataset(Client, TrainingDatasetArn)
when is_map(Client) ->
get_training_dataset(Client, TrainingDatasetArn, #{}, #{}).
get_training_dataset(Client, TrainingDatasetArn, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
get_training_dataset(Client, TrainingDatasetArn, QueryMap, HeadersMap, []).
get_training_dataset(Client, TrainingDatasetArn, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/training-dataset/", aws_util:encode_uri(TrainingDatasetArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query_ = [],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns a list of the audience export jobs.
list_audience_export_jobs(Client)
when is_map(Client) ->
list_audience_export_jobs(Client, #{}, #{}).
list_audience_export_jobs(Client, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
list_audience_export_jobs(Client, QueryMap, HeadersMap, []).
list_audience_export_jobs(Client, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/audience-export-job"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query0_ =
[
{<<"audienceGenerationJobArn">>, maps:get(<<"audienceGenerationJobArn">>, QueryMap, undefined)},
{<<"maxResults">>, maps:get(<<"maxResults">>, QueryMap, undefined)},
{<<"nextToken">>, maps:get(<<"nextToken">>, QueryMap, undefined)}
],
Query_ = [H || {_, V} = H <- Query0_, V =/= undefined],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns a list of audience generation jobs.
list_audience_generation_jobs(Client)
when is_map(Client) ->
list_audience_generation_jobs(Client, #{}, #{}).
list_audience_generation_jobs(Client, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
list_audience_generation_jobs(Client, QueryMap, HeadersMap, []).
list_audience_generation_jobs(Client, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/audience-generation-job"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query0_ =
[
{<<"collaborationId">>, maps:get(<<"collaborationId">>, QueryMap, undefined)},
{<<"configuredAudienceModelArn">>, maps:get(<<"configuredAudienceModelArn">>, QueryMap, undefined)},
{<<"maxResults">>, maps:get(<<"maxResults">>, QueryMap, undefined)},
{<<"nextToken">>, maps:get(<<"nextToken">>, QueryMap, undefined)}
],
Query_ = [H || {_, V} = H <- Query0_, V =/= undefined],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns a list of audience models.
list_audience_models(Client)
when is_map(Client) ->
list_audience_models(Client, #{}, #{}).
list_audience_models(Client, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
list_audience_models(Client, QueryMap, HeadersMap, []).
list_audience_models(Client, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/audience-model"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query0_ =
[
{<<"maxResults">>, maps:get(<<"maxResults">>, QueryMap, undefined)},
{<<"nextToken">>, maps:get(<<"nextToken">>, QueryMap, undefined)}
],
Query_ = [H || {_, V} = H <- Query0_, V =/= undefined],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns a list of the configured audience models.
list_configured_audience_models(Client)
when is_map(Client) ->
list_configured_audience_models(Client, #{}, #{}).
list_configured_audience_models(Client, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
list_configured_audience_models(Client, QueryMap, HeadersMap, []).
list_configured_audience_models(Client, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/configured-audience-model"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query0_ =
[
{<<"maxResults">>, maps:get(<<"maxResults">>, QueryMap, undefined)},
{<<"nextToken">>, maps:get(<<"nextToken">>, QueryMap, undefined)}
],
Query_ = [H || {_, V} = H <- Query0_, V =/= undefined],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns a list of tags for a provided resource.
list_tags_for_resource(Client, ResourceArn)
when is_map(Client) ->
list_tags_for_resource(Client, ResourceArn, #{}, #{}).
list_tags_for_resource(Client, ResourceArn, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
list_tags_for_resource(Client, ResourceArn, QueryMap, HeadersMap, []).
list_tags_for_resource(Client, ResourceArn, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/tags/", aws_util:encode_uri(ResourceArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query_ = [],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Returns a list of training datasets.
list_training_datasets(Client)
when is_map(Client) ->
list_training_datasets(Client, #{}, #{}).
list_training_datasets(Client, QueryMap, HeadersMap)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap) ->
list_training_datasets(Client, QueryMap, HeadersMap, []).
list_training_datasets(Client, QueryMap, HeadersMap, Options0)
when is_map(Client), is_map(QueryMap), is_map(HeadersMap), is_list(Options0) ->
Path = ["/training-dataset"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false}
| Options0],
Headers = [],
Query0_ =
[
{<<"maxResults">>, maps:get(<<"maxResults">>, QueryMap, undefined)},
{<<"nextToken">>, maps:get(<<"nextToken">>, QueryMap, undefined)}
],
Query_ = [H || {_, V} = H <- Query0_, V =/= undefined],
request(Client, get, Path, Query_, Headers, undefined, Options, SuccessStatusCode).
%% @doc Create or update the resource policy for a configured audience model.
put_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, Input) ->
put_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, Input, []).
put_configured_audience_model_policy(Client, ConfiguredAudienceModelArn, Input0, Options0) ->
Method = put,
Path = ["/configured-audience-model/", aws_util:encode_uri(ConfiguredAudienceModelArn), "/policy"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Export an audience of a specified size after you have generated an
%% audience.
start_audience_export_job(Client, Input) ->
start_audience_export_job(Client, Input, []).
start_audience_export_job(Client, Input0, Options0) ->
Method = post,
Path = ["/audience-export-job"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Information necessary to start the audience generation job.
start_audience_generation_job(Client, Input) ->
start_audience_generation_job(Client, Input, []).
start_audience_generation_job(Client, Input0, Options0) ->
Method = post,
Path = ["/audience-generation-job"],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Adds metadata tags to a specified resource.
tag_resource(Client, ResourceArn, Input) ->
tag_resource(Client, ResourceArn, Input, []).
tag_resource(Client, ResourceArn, Input0, Options0) ->
Method = post,
Path = ["/tags/", aws_util:encode_uri(ResourceArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Removes metadata tags from a specified resource.
untag_resource(Client, ResourceArn, Input) ->
untag_resource(Client, ResourceArn, Input, []).
untag_resource(Client, ResourceArn, Input0, Options0) ->
Method = delete,
Path = ["/tags/", aws_util:encode_uri(ResourceArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
QueryMapping = [
{<<"tagKeys">>, <<"tagKeys">>}
],
{Query_, Input} = aws_request:build_headers(QueryMapping, Input2),
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%% @doc Provides the information necessary to update a configured audience
%% model.
%%
%% Updates that impact audience generation jobs take effect when a new job
%% starts, but do not impact currently running jobs.
update_configured_audience_model(Client, ConfiguredAudienceModelArn, Input) ->
update_configured_audience_model(Client, ConfiguredAudienceModelArn, Input, []).
update_configured_audience_model(Client, ConfiguredAudienceModelArn, Input0, Options0) ->
Method = patch,
Path = ["/configured-audience-model/", aws_util:encode_uri(ConfiguredAudienceModelArn), ""],
SuccessStatusCode = 200,
Options = [{send_body_as_binary, false},
{receive_body_as_binary, false},
{append_sha256_content_hash, false}
| Options0],
Headers = [],
Input1 = Input0,
CustomHeaders = [],
Input2 = Input1,
Query_ = [],
Input = Input2,
request(Client, Method, Path, Query_, CustomHeaders ++ Headers, Input, Options, SuccessStatusCode).
%%====================================================================
%% Internal functions
%%====================================================================
-spec request(aws_client:aws_client(), atom(), iolist(), list(),
list(), map() | undefined, list(), pos_integer() | undefined) ->
{ok, {integer(), list()}} |
{ok, Result, {integer(), list(), hackney:client()}} |
{error, Error, {integer(), list(), hackney:client()}} |
{error, term()} when
Result :: map(),
Error :: map().
request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) ->
RequestFun = fun() -> do_request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) end,
aws_request:request(RequestFun, Options).
do_request(Client, Method, Path, Query, Headers0, Input, Options, SuccessStatusCode) ->
Client1 = Client#{service => <<"cleanrooms-ml">>},
Host = build_host(<<"cleanrooms-ml">>, Client1),
URL0 = build_url(Host, Path, Client1),
URL = aws_request:add_query(URL0, Query),
AdditionalHeaders1 = [ {<<"Host">>, Host}
, {<<"Content-Type">>, <<"application/x-amz-json-1.1">>}
],
Payload =
case proplists:get_value(send_body_as_binary, Options) of
true ->
maps:get(<<"Body">>, Input, <<"">>);
false ->
encode_payload(Input)
end,
AdditionalHeaders = case proplists:get_value(append_sha256_content_hash, Options, false) of
true ->
add_checksum_hash_header(AdditionalHeaders1, Payload);
false ->
AdditionalHeaders1
end,
Headers1 = aws_request:add_headers(AdditionalHeaders, Headers0),
MethodBin = aws_request:method_to_binary(Method),
SignedHeaders = aws_request:sign_request(Client1, MethodBin, URL, Headers1, Payload),
Response = hackney:request(Method, URL, SignedHeaders, Payload, Options),
DecodeBody = not proplists:get_value(receive_body_as_binary, Options),
handle_response(Response, SuccessStatusCode, DecodeBody).
add_checksum_hash_header(Headers, Body) ->
[ {<<"X-Amz-CheckSum-SHA256">>, base64:encode(crypto:hash(sha256, Body))}
| Headers
].
handle_response({ok, StatusCode, ResponseHeaders}, SuccessStatusCode, _DecodeBody)
when StatusCode =:= 200;
StatusCode =:= 202;
StatusCode =:= 204;
StatusCode =:= 206;
StatusCode =:= SuccessStatusCode ->
{ok, {StatusCode, ResponseHeaders}};
handle_response({ok, StatusCode, ResponseHeaders}, _, _DecodeBody) ->
{error, {StatusCode, ResponseHeaders}};
handle_response({ok, StatusCode, ResponseHeaders, Client}, SuccessStatusCode, DecodeBody)
when StatusCode =:= 200;
StatusCode =:= 202;
StatusCode =:= 204;
StatusCode =:= 206;
StatusCode =:= SuccessStatusCode ->
case hackney:body(Client) of
{ok, <<>>} when StatusCode =:= 200;
StatusCode =:= SuccessStatusCode ->
{ok, #{}, {StatusCode, ResponseHeaders, Client}};
{ok, Body} ->
Result = case DecodeBody of
true ->
try
jsx:decode(Body)
catch
Error:Reason:Stack ->
erlang:raise(error, {body_decode_failed, Error, Reason, StatusCode, Body}, Stack)
end;
false -> #{<<"Body">> => Body}
end,
{ok, Result, {StatusCode, ResponseHeaders, Client}}
end;
handle_response({ok, StatusCode, _ResponseHeaders, _Client}, _, _DecodeBody)
when StatusCode =:= 503 ->
%% Retriable error if retries are enabled
{error, service_unavailable};
handle_response({ok, StatusCode, ResponseHeaders, Client}, _, _DecodeBody) ->
{ok, Body} = hackney:body(Client),
try
DecodedError = jsx:decode(Body),
{error, DecodedError, {StatusCode, ResponseHeaders, Client}}
catch
Error:Reason:Stack ->
erlang:raise(error, {body_decode_failed, Error, Reason, StatusCode, Body}, Stack)
end;
handle_response({error, Reason}, _, _DecodeBody) ->
{error, Reason}.
build_host(_EndpointPrefix, #{region := <<"local">>, endpoint := Endpoint}) ->
Endpoint;
build_host(_EndpointPrefix, #{region := <<"local">>}) ->
<<"localhost">>;
build_host(EndpointPrefix, #{region := Region, endpoint := Endpoint}) ->
aws_util:binary_join([EndpointPrefix, Region, Endpoint], <<".">>).
build_url(Host, Path0, Client) ->
Proto = aws_client:proto(Client),
Path = erlang:iolist_to_binary(Path0),
Port = aws_client:port(Client),
aws_util:binary_join([Proto, <<"://">>, Host, <<":">>, Port, Path], <<"">>).
-spec encode_payload(undefined | map()) -> binary().
encode_payload(undefined) ->
<<>>;
encode_payload(Input) ->
jsx:encode(Input).