From 213b5e3a95aacdcea154e9d0871eed989f150c37 Mon Sep 17 00:00:00 2001 From: awstools Date: Tue, 16 Jan 2024 19:18:32 +0000 Subject: [PATCH] docs(client-personalize): Documentation updates for Amazon Personalize. --- .../src/commands/CreateCampaignCommand.ts | 31 +++++++++---------- .../client-personalize/src/models/models_0.ts | 16 ++++++---- .../sdk-codegen/aws-models/personalize.json | 10 +++--- 3 files changed, 30 insertions(+), 27 deletions(-) diff --git a/clients/client-personalize/src/commands/CreateCampaignCommand.ts b/clients/client-personalize/src/commands/CreateCampaignCommand.ts index 8dec1391e78fc..d7bbf6c17d77a 100644 --- a/clients/client-personalize/src/commands/CreateCampaignCommand.ts +++ b/clients/client-personalize/src/commands/CreateCampaignCommand.ts @@ -37,27 +37,26 @@ export interface CreateCampaignCommandOutput extends CreateCampaignResponse, __M * Minimum Provisioned TPS and Auto-Scaling *

* - *

A high minProvisionedTPS will increase your bill. We recommend starting with 1 for minProvisionedTPS (the default). Track + *

A high minProvisionedTPS will increase your cost. We recommend starting with 1 for minProvisionedTPS (the default). Track * your usage using Amazon CloudWatch metrics, and increase the minProvisionedTPS * as necessary.

* - *

A transaction is a single GetRecommendations or - * GetPersonalizedRanking call. Transactions per second (TPS) is the throughput - * and unit of billing for Amazon Personalize. The minimum provisioned TPS - * (minProvisionedTPS) specifies the baseline throughput provisioned by - * Amazon Personalize, and thus, the minimum billing charge. - *

*

- * If your TPS increases beyond - * minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up and down, - * but never below minProvisionedTPS. - * There's a short time delay while the capacity is increased that might cause loss of - * transactions.

- *

The actual TPS used is calculated as the average requests/second within a 5-minute window. - * You pay for maximum of either the minimum provisioned TPS or the actual TPS. + * When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second + * (minProvisionedTPS) for the campaign. This is the baseline transaction throughput for the campaign provisioned by + * Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A transaction is a single GetRecommendations or + * GetPersonalizedRanking request. The default minProvisionedTPS is 1.

+ *

If your TPS increases beyond the minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up + * and down, but never below minProvisionedTPS. + * There's a short time delay while the capacity is increased + * that might cause loss of transactions. When your traffic reduces, capacity returns to the minProvisionedTPS. + *

+ *

You are charged for the + * the minimum provisioned TPS or, if your requests exceed the minProvisionedTPS, the actual TPS. + * The actual TPS is the total number of recommendation requests you make. * We recommend starting with a low minProvisionedTPS, track - * your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS - * as necessary.

+ * your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS as necessary.

+ *

For more information about campaign costs, see Amazon Personalize pricing.

*

* Status *

diff --git a/clients/client-personalize/src/models/models_0.ts b/clients/client-personalize/src/models/models_0.ts index 93a47934b781b..7cf9f8710313d 100644 --- a/clients/client-personalize/src/models/models_0.ts +++ b/clients/client-personalize/src/models/models_0.ts @@ -641,7 +641,8 @@ export interface CampaignConfig { /** * @public *

Whether metadata with recommendations is enabled for the campaign. - * If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response.

+ * If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. + * For information about enabling metadata for a campaign, see Enabling metadata in recommendations for a campaign.

*

* If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing. *

@@ -1243,7 +1244,8 @@ export interface RecommenderConfig { /** * @public *

Whether metadata with recommendations is enabled for the recommender. - * If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response.

+ * If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. + * For information about enabling metadata for a recommender, see Enabling metadata in recommendations for a recommender.

*

* If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing. *

@@ -1641,8 +1643,7 @@ export interface CreateSolutionRequest { * @public * *

We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize - * recipes. For more information, see Determining your use case. - *

+ * recipes. For more information, see Choosing a recipe.

* *

Whether to perform automated machine learning (AutoML). The default is false. * For this case, you must specify recipeArn.

@@ -1656,8 +1657,11 @@ export interface CreateSolutionRequest { /** * @public - *

The ARN of the recipe to use for model training. This is required when - * performAutoML is false.

+ *

The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when + * performAutoML is false. For information about different Amazon Personalize recipes and their ARNs, + * see Choosing a recipe. + * + *

*/ recipeArn?: string; diff --git a/codegen/sdk-codegen/aws-models/personalize.json b/codegen/sdk-codegen/aws-models/personalize.json index d0310b59ba5e4..fcb0de9820bdb 100644 --- a/codegen/sdk-codegen/aws-models/personalize.json +++ b/codegen/sdk-codegen/aws-models/personalize.json @@ -1649,7 +1649,7 @@ "enableMetadataWithRecommendations": { "target": "com.amazonaws.personalize#Boolean", "traits": { - "smithy.api#documentation": "

Whether metadata with recommendations is enabled for the campaign. \n If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response.

\n

\n If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing.\n

" + "smithy.api#documentation": "

Whether metadata with recommendations is enabled for the campaign. \n If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response.\n For information about enabling metadata for a campaign, see Enabling metadata in recommendations for a campaign.

\n

\n If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing.\n

" } } }, @@ -2153,7 +2153,7 @@ } ], "traits": { - "smithy.api#documentation": "

Creates a campaign that deploys a solution version. When a client calls the\n GetRecommendations\n and\n GetPersonalizedRanking\n APIs, a campaign is specified in the request.

\n

\n Minimum Provisioned TPS and Auto-Scaling\n

\n \n

A high minProvisionedTPS will increase your bill. We recommend starting with 1 for minProvisionedTPS (the default). Track\n your usage using Amazon CloudWatch metrics, and increase the minProvisionedTPS\n as necessary.

\n \n

A transaction is a single GetRecommendations or\n GetPersonalizedRanking call. Transactions per second (TPS) is the throughput\n and unit of billing for Amazon Personalize. The minimum provisioned TPS\n (minProvisionedTPS) specifies the baseline throughput provisioned by\n Amazon Personalize, and thus, the minimum billing charge. \n

\n

\n If your TPS increases beyond\n minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up and down,\n but never below minProvisionedTPS.\n There's a short time delay while the capacity is increased that might cause loss of\n transactions.

\n

The actual TPS used is calculated as the average requests/second within a 5-minute window.\n You pay for maximum of either the minimum provisioned TPS or the actual TPS.\n We recommend starting with a low minProvisionedTPS, track\n your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS\n as necessary.

\n

\n Status\n

\n

A campaign can be in one of the following states:

\n \n

To get the campaign status, call DescribeCampaign.

\n \n

Wait until the status of the campaign\n is ACTIVE before asking the campaign for recommendations.

\n \n

\n Related APIs\n

\n ", + "smithy.api#documentation": "

Creates a campaign that deploys a solution version. When a client calls the\n GetRecommendations\n and\n GetPersonalizedRanking\n APIs, a campaign is specified in the request.

\n

\n Minimum Provisioned TPS and Auto-Scaling\n

\n \n

A high minProvisionedTPS will increase your cost. We recommend starting with 1 for minProvisionedTPS (the default). Track\n your usage using Amazon CloudWatch metrics, and increase the minProvisionedTPS\n as necessary.

\n \n

\n When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second\n (minProvisionedTPS) for the campaign. This is the baseline transaction throughput for the campaign provisioned by\n Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A transaction is a single GetRecommendations or\n GetPersonalizedRanking request. The default minProvisionedTPS is 1.

\n

If your TPS increases beyond the minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up\n and down, but never below minProvisionedTPS. \n There's a short time delay while the capacity is increased\n that might cause loss of transactions. When your traffic reduces, capacity returns to the minProvisionedTPS.\n

\n

You are charged for the\n the minimum provisioned TPS or, if your requests exceed the minProvisionedTPS, the actual TPS. \n The actual TPS is the total number of recommendation requests you make.\n We recommend starting with a low minProvisionedTPS, track\n your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS as necessary.

\n

For more information about campaign costs, see Amazon Personalize pricing.

\n

\n Status\n

\n

A campaign can be in one of the following states:

\n \n

To get the campaign status, call DescribeCampaign.

\n \n

Wait until the status of the campaign\n is ACTIVE before asking the campaign for recommendations.

\n \n

\n Related APIs\n

\n ", "smithy.api#idempotent": {} } }, @@ -3024,13 +3024,13 @@ "target": "com.amazonaws.personalize#PerformAutoML", "traits": { "smithy.api#default": false, - "smithy.api#documentation": "\n

We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize \n recipes. For more information, see Determining your use case.\n

\n \n

Whether to perform automated machine learning (AutoML). The default is false.\n For this case, you must specify recipeArn.

\n

When set to true, Amazon Personalize analyzes your training data and selects\n the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit\n recipeArn. Amazon Personalize determines the optimal recipe by running tests with\n different values for the hyperparameters.\n AutoML lengthens the training process as compared to selecting a specific recipe.

" + "smithy.api#documentation": "\n

We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize \n recipes. For more information, see Choosing a recipe.

\n \n

Whether to perform automated machine learning (AutoML). The default is false.\n For this case, you must specify recipeArn.

\n

When set to true, Amazon Personalize analyzes your training data and selects\n the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit\n recipeArn. Amazon Personalize determines the optimal recipe by running tests with\n different values for the hyperparameters.\n AutoML lengthens the training process as compared to selecting a specific recipe.

" } }, "recipeArn": { "target": "com.amazonaws.personalize#Arn", "traits": { - "smithy.api#documentation": "

The ARN of the recipe to use for model training. This is required when\n performAutoML is false.

" + "smithy.api#documentation": "

The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when\n performAutoML is false. For information about different Amazon Personalize recipes and their ARNs, \n see Choosing a recipe.\n \n

" } }, "datasetGroupArn": { @@ -7706,7 +7706,7 @@ "enableMetadataWithRecommendations": { "target": "com.amazonaws.personalize#Boolean", "traits": { - "smithy.api#documentation": "

Whether metadata with recommendations is enabled for the recommender. \n If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response.

\n

\n If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing.\n

" + "smithy.api#documentation": "

Whether metadata with recommendations is enabled for the recommender. \n If enabled, you can specify the columns from your Items dataset in your request for recommendations. Amazon Personalize returns this data for each item in the recommendation response. \n For information about enabling metadata for a recommender, see Enabling metadata in recommendations for a recommender.

\n

\n If you enable metadata in recommendations, you will incur additional costs. For more information, see Amazon Personalize pricing.\n

" } } },