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59c04ced37a8-0 | With IAM identity\-based policies, you can specify allowed or denied actions and resources as well as the conditions under which actions are allowed or denied\. Amazon Personalize supports specific actions, resources, and condition keys\. To learn about all of the elements that you use in a JSON policy, see [IAM JSON Policy Elements Reference](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_elements.html) in the *IAM User Guide*\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
7faf4455994f-0 | The `Action` element of an IAM identity\-based policy describes the specific action or actions that will be allowed or denied by the policy\. Policy actions usually have the same name as the associated AWS API operation\. The action is used in a policy to grant permissions to perform the associated operation\.
Policy actions in Amazon Personalize use the following prefix before the action: `personalize:`\. For example, to create a dataset with the Amazon Personalize `CreateDataset` API operation, you include the `personalize:CreateDataset` action in the policy\. Policy statements must include either an `Action` or `NotAction` element\. Amazon Personalize defines its own set of actions that describe tasks that you can perform with this service\.
To specify multiple actions in a single statement, separate them with commas as shown in the following command\.
```
"Action": [
"personalize:action1",
"personalize:action2"
```
You can specify multiple actions using wildcards \(\*\)\. For example, to specify all actions that begin with the word `Describe`, include the following action\.
```
"Action": "personalize:Describe*"
```
To see a list of Amazon Personalize actions, see [Actions Defined by Amazon Personalize](https://docs.aws.amazon.com/IAM/latest/UserGuide/list_awskeymanagementservice.html#awskeymanagementservice-actions-as-permissions) in the *IAM User Guide*\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
abe76e59d483-0 | The `Resource` element specifies the object or objects to which the action applies\. Statements must include either a `Resource` or a `NotResource` element\. You specify a resource using an ARN or using the wildcard \(\*\) to indicate that the statement applies to all resources\.
An Amazon Personalize dataset resource has the following ARN\.
```
arn:${Partition}:personalize:${Region}:${Account}:dataset/${dataset-name}
```
For more information about the format of ARNs, see [Amazon Resource Names \(ARNs\) and AWS Service Namespaces](https://docs.aws.amazon.com/general/latest/gr/aws-arns-and-namespaces.html)\.
For example, to specify the `MyDataset` dataset in your statement, use the following ARN\.
```
"Resource": "arn:aws:personalize:us-east-1:123456789012:dataset/MyDataset"
```
To specify all datasets that belong to a specific account, use the wildcard \(\*\), as shown in the following example\.
```
"Resource": "arn:aws:personalize:us-east-1:123456789012:dataset/*"
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
abe76e59d483-1 | ```
Some Amazon Personalize actions, such as those for creating resources, cannot be performed on a specific resource\. In those cases, you must use the wildcard \(\*\)\.
```
"Resource": "*"
```
To see a list of Amazon Personalize resource types and their ARNs, see [Resources Defined by Amazon Personalize](https://docs.aws.amazon.com/IAM/latest/UserGuide/list_awskeymanagementservice.html#awskeymanagementservice-resources-for-iam-policies) in the *IAM User Guide*\. To learn about the actions you can use to specify the ARN of each resource, see [Actions Defined by Amazon Personalize](https://docs.aws.amazon.com/IAM/latest/UserGuide/list_awskeymanagementservice.html#awskeymanagementservice-actions-as-permissions)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
82f168487c31-0 | The `Condition` element \(or `Condition` *block*\) lets you specify conditions in which a statement is in effect\. The `Condition` element is optional\. You can create conditional expressions that use [condition operators](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_elements_condition_operators.html), such as equals or less than, to match the condition in the policy with values in the request\.
If you specify multiple `Condition` elements in a statement, or multiple keys in a single `Condition` element, AWS evaluates them using a logical `AND` operation\. If you specify multiple values for a single condition key, AWS evaluates the condition using a logical `OR` operation\. All of the conditions must be met before the statement's permissions are granted\.
You can also use placeholder variables when you specify conditions\. For example, you can grant an IAM user permission to access a resource only if it is tagged with their IAM user name\. For more information, see [IAM Policy Elements: Variables and Tags](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_variables.html) in the *IAM User Guide*\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
7dcfbfba1024-0 | To view examples of Amazon Personalize identity\-based policies, see [Amazon Personalize Identity\-Based Policy Examples](security_iam_id-based-policy-examples.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
58a2f5d891a0-0 | Amazon Personalize does not support resource\-based policies\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
b7bf46e7ba08-0 | Amazon Personalize does not support tagging resources or controlling access based on tags\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
610a83420e26-0 | An [IAM role](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles.html) is an entity within your AWS account that has specific permissions\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
9b0156e009f1-0 | You can use temporary credentials to sign in with federation, assume an IAM role, or to assume a cross\-account role\. You obtain temporary security credentials by calling AWS Security Token Service \(AWS STS\) API operations such as [AssumeRole](https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRole.html) or [GetFederationToken](https://docs.aws.amazon.com/STS/latest/APIReference/API_GetFederationToken.html)\.
Amazon Personalize supports using temporary credentials\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
e10ce594c354-0 | [Service\-linked roles](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_terms-and-concepts.html#iam-term-service-linked-role) allow AWS services to access resources in other services to complete an action on your behalf\. Service\-linked roles appear in your IAM account and are owned by the service\. An IAM administrator can view but not edit the permissions for service\-linked roles\.
Amazon Personalize does not support service\-linked roles\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
503e2fa51c4b-0 | This feature allows a service to assume a [service role](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_terms-and-concepts.html#iam-term-service-role) on your behalf\. This role allows the service to access resources in other services to complete an action on your behalf\. Service roles appear in your IAM account and are owned by the account\. This means that an IAM administrator can change the permissions for this role\. However, doing so might break the functionality of the service\.
Amazon Personalize supports service roles\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security_iam_service-with-iam.md |
d8dcc0fa9da3-0 | Amazon Personalize can make recommendations based on real\-time event data only, historical imported data \(as demonstrated in the [Getting Started](getting-started.md) guides\) only, or a mixture of both\. To import real\-time event data, record user activity \(events\) in real\-time using the AWS SDK, AWS Amplify or AWS CLI\.
**Note**
AWS Amplify includes a JavaScript library for recording events from web client applications, and a library for recording events in server code\. For more information, see [Amplify \- Analytics](https://aws-amplify.github.io/docs/js/analytics)
**Requirements for Recording Events**
To record events, you need the following:
+ A dataset group that includes an `Interactions` dataset, which can be empty\. For a Python example that creates a dataset and a dataset group, see [Importing Your Data](data-prep-importing.md)\.
+ An event tracker\.
+ A call to the [PutEvents](API_UBS_PutEvents.md) operation\.
You can start out with an empty Interactions dataset and, when you have recorded enough data, train the model using only new recorded events\. The minimum data requirements to train a model are:
+ 1000 records of combined interaction data \(after filtering by `eventType` and `eventValueThreshold`, if provided\)
+ 25 unique users with at least 2 interactions each
**How Recorded Events Influence Recommendations** | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
d8dcc0fa9da3-1 | + 25 unique users with at least 2 interactions each
**How Recorded Events Influence Recommendations**
Once you create a campaign, Amazon Personalize automatically uses new recorded event data for existing items \(items you included in the data you used to train the latest model\) when generating recommendations for the user\. This does not require retraining the model \(unless you are using the SIMS or popularity\-count recipes\)\.
Instead, the new recorded event data is added to the user's history\. Amazon Personalize then uses the modified data when generating recommendations for the user \(and this user only\)\.
For recorded events for new items \(items you did not include in the data you used to train the model\), you must re\-train the model for the new records to influence recommendations\. Amazon Personalize stores recorded events for new items and, once you create a new solution version \(train a new model\), this new data will influence Amazon Personalize recommendations for the user\.
For recorded events for new users \(users that were not included in the data you used to train the model\), recommendations will initially be for popular items only\. Recommendations will be more relevant as you record more events for the user\. Amazon Personalize stores the new user data, so you can also retrain the model for more relevant recommendations\.
**Topics**
+ [Creating a Dataset Group](#event-dataset-group)
+ [Getting a Tracking ID](#event-get-tracker)
+ [PutEvents Operation](#event-record-api)
+ [Event Metrics](#event-metrics) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
d8dcc0fa9da3-2 | + [PutEvents Operation](#event-record-api)
+ [Event Metrics](#event-metrics)
+ [Events and Solutions](#event-solutions)
+ [Sample Jupyter Notebook](#recording-events-sample-notebook) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
f278cc92c210-0 | If you went through the [Getting Started](getting-started.md) guide, you can use the same dataset group that you created\. For a Python example that creates a dataset and a dataset group, see [Importing Your Data](data-prep-importing.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
155190fadfe0-0 | A tracking ID associates an event with a dataset group and authorizes you to send data to Amazon Personalize\. You generate a tracking ID by calling the [CreateEventTracker](API_CreateEventTracker.md) API and supplying the dataset group ARN\.
**Note**
Only one event tracker can be associated with a dataset group\. You will get an error if you call `CreateEventTracker` using the same dataset group as an existing event tracker\.
------ | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
1a0ec1a603a1-0 | ```
import boto3
personalize = boto3.client('personalize')
response = personalize.create_event_tracker(
name='MovieClickTracker',
datasetGroupArn='arn:aws:personalize:us-west-2:acct-id:dataset-group/MovieClickGroup'
)
print(response['eventTrackerArn'])
print(response['trackingId'])
```
------ | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
475bae2050f1-0 | ```
aws personalize create-event-tracker \
--name MovieClickTracker \
--dataset-group-arn arn:aws:personalize:us-west-2:acct-id:dataset-group/MovieClickGroup
```
------
The event tracker ARN and tracking ID display, for example:
```
{
"eventTrackerArn": "arn:aws:personalize:us-west-2:acct-id:event-tracker/MovieClickTracker",
"trackingId": "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
2db33e291fae-0 | To record events, you call the [PutEvents](API_UBS_PutEvents.md) operation\. The following example shows a `PutEvents` call that passes one event that contains the minimum required information\. The corresponding Interactions schema is shown, along with an example row from the Interactions dataset\.
Your application generates the `sessionId` when a user first visits your website or uses your application\. Amazon Personalize uses the `sessionId` to associate events with the user before they log in \(is anonymous\)\. After the user logs in and you send an event including the `userId`, Amazon Personalize associates the previously anonymous historical event data with their `userId` by matching the `sessionId`\. This creates a continuous event history that includes events that occurred when the user was anonymous\.
The event list is an array of [Event](API_UBS_Event.md) objects\. An `eventType` is required for each event, but in this example, `eventType` data is not used in training because it is not included in the schema\. The `properties` key is a string map \(key\-value pairs\) of event\-specific data\. In this case, just the item ID is specified\.
The `userId`, `itemId`, and `sentAt` parameters map to the USER\_ID, ITEM\_ID, and TIMESTAMP fields of a corresponding historical `Interactions` dataset\. For more information, see [Datasets and Schemas](how-it-works-dataset-schema.md)\.
**Corresponding Interactions Schema**
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
2db33e291fae-1 | **Corresponding Interactions Schema**
```
Interactions schema: USER_ID, ITEM_ID, TIMESTAMP
Interactions dataset: user123, item-xyz, 1543631760
```
**Code Example**
------ | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
a955f81b1e2a-0 | ```
import boto3
personalize_events = boto3.client(service_name='personalize-events')
personalize_events.put_events(
trackingId = 'tracking_id',
userId= 'USER_ID',
sessionId = 'session_id',
eventList = [{
'sentAt': TIMESTAMP,
'eventType': 'EVENT_TYPE',
'properties': "{\"itemId\": \"ITEM_ID\"}"
}]
)
```
------ | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
744d0fdb51ff-0 | ```
aws personalize-events put-events \
--tracking-id tracking_id \
--user-id USER_ID \
--session-id session_id \
--event-list '[{
"sentAt": "TIMESTAMP",
"eventType": "EVENT_TYPE",
"properties": "{\"itemId\": \"ITEM_ID\"}"
}]'
```
------
After this example, you would proceed to train a model using only the required properties\. The training would not use the `eventValue` property because it wasn't included in the event\.
The next example shows how to submit data that would train on the event value\. It also demonstrates the passing of multiple events of different types \('like' and 'rating'\)\. In this case, you must specify the event type to train on in the [CreateSolution](API_CreateSolution.md) operation \(see **Events and Solutions** below\)\. The example also shows the recording of an extra property, `numRatings`, that is used as metadata by certain recipes\.
```
Interactions schema: USER_ID, ITEM_ID, TIMESTAMP, EVENT_TYPE, EVENT_VALUE, NUM_RATINGS
Interactions dataset: user123, movie_xyz, 1543531139, rating, 5, 12 | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
744d0fdb51ff-1 | Interactions dataset: user123, movie_xyz, 1543531139, rating, 5, 12
user321, choc-ghana, 1543531760, like, 4
user111, choc-fake, 1543557118, like, 3
```
------ | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
2382b65dd5c6-0 | ```
import boto3
import json
personalize_events = boto3.client(service_name='personalize-events')
personalize_events.put_events(
trackingId = 'tracking_id',
userId= 'user555',
sessionId = 'session1',
eventList = [{
'eventId': 'event1',
'sentAt': '1553631760',
'eventType': 'like',
'properties': json.dumps({
'itemId': 'choc-panama',
'eventValue': 4,
'numRatings': 0
})
}, {
'eventId': 'event2',
'sentAt': '1553631782',
'eventType': 'rating',
'properties': json.dumps({
'itemId': 'movie_ten',
'eventValue': 3,
'numRatings': 13
})
}]
)
```
------ | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
bd4405d9131f-0 | ```
aws personalize-events put-events \
--tracking-id tracking_id \
--user-id user555 \
--session-id session1 \
--event-list '[{
"eventId": "event1",
"sentAt": "1553631760",
"eventType": "like",
"properties": "{\"itemId\": \"choc-panama\", \"eventValue\": \"true\"}"
}, {
"eventId": "event2",
"sentAt": "1553631782",
"eventType": "rating",
"properties": "{\"itemId\": \"movie_ten\", \"eventValue\": \"4\", \"numRatings\": \"13\"}"
}]'
```
------
**Note**
The properties keys use camel case names that match the fields in the Interactions schema\. For example, if the fields 'ITEM\_ID', 'EVENT\_VALUE', and 'NUM\_RATINGS,' are defined in the Interactions schema, the property keys should be `itemId, eventValue, and numRatings`\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
693a92268a93-0 | To monitor the type and number of events sent to Amazon Personalize, use Amazon CloudWatch metrics\. For more information, see [Monitoring Amazon Personalize](personalize-monitoring.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
0d3a17878fb3-0 | When training a model that uses event data, two parameters of the [CreateSolution](API_CreateSolution.md) operation are relevant\. The `eventType` parameter must be specified when multiple event types are recorded\. The `eventType` indicates which type of event Amazon Personalize uses as the label for model training\.
The `eventValueThreshold` parameter of the `SolutionConfig` object creates an event filter\. When this parameter is specified, only events with a value greater than or equal to the threshold are used for training the model\. You must specify the event type when using `eventValueThreshold`\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
48c84378e80d-0 | For a sample Jupyter notebook that shows how to use Amazon Personalize to react to real\-time behavior of users using an event tracker and the [PutEvents](API_UBS_PutEvents.md) operation, see [2\.View\_Campaign\_And\_Interactions\.ipynb](https://github.com/aws-samples/amazon-personalize-samples/blob/master/getting_started/notebooks/2.View_Campaign_And_Interactions.ipynb) in the **getting\_started** folder of the [amazon\-personalize\-samples](https://github.com/aws-samples/amazon-personalize-samples) GitHub repository\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/recording-events.md |
8295128fe11a-0 | Amazon Personalize uses data that you provide to train a model\. You can provide data from a source file, or you can collect data from live events, such as user activities on a website\.
If you provide a source file to import your data into Amazon Personalize, you must fulfill these requirements:
+ Format your data as a comma\-separated values \(CSV\) file
+ Provide a schema so that Amazon Personalize can import the data correctly
+ Upload your file into an Amazon Simple Storage Service \(Amazon S3\) bucket that Amazon Personalize can access
You can upload your data by using the AWS SDK\.
This section provides information about formatting and importing your historical data into Amazon Personalize\. For information about recording live event data, see [Recording Events](recording-events.md)\.
**Topics**
+ [Datasets and Schemas](how-it-works-dataset-schema.md)
+ [Formatting Your Input Data](data-prep-formatting.md)
+ [Uploading to an S3 Bucket](data-prep-upload-s3.md)
+ [Importing Your Data](data-prep-importing.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/data-prep.md |
2cfa89e4516d-0 | Updates a campaign by either deploying a new solution or changing the value of the campaign's `minProvisionedTPS` parameter\.
To update a campaign, the campaign status must be ACTIVE or CREATE FAILED\. Check the campaign status using the [DescribeCampaign](API_DescribeCampaign.md) API\.
**Note**
You must wait until the `status` of the updated campaign is `ACTIVE` before asking the campaign for recommendations\.
For more information on campaigns, see [CreateCampaign](API_CreateCampaign.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
7770f88de7a2-0 | ```
{
"campaignArn": "string",
"campaignConfig": {
"itemExplorationConfig": {
"string" : "string"
}
},
"minProvisionedTPS": number,
"solutionVersionArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
0cd084f24638-0 | The request accepts the following data in JSON format\.
** [campaignArn](#API_UpdateCampaign_RequestSyntax) ** <a name="personalize-UpdateCampaign-request-campaignArn"></a>
The Amazon Resource Name \(ARN\) of the campaign\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: Yes
** [campaignConfig](#API_UpdateCampaign_RequestSyntax) ** <a name="personalize-UpdateCampaign-request-campaignConfig"></a>
The configuration details of a campaign\.
Type: [CampaignConfig](API_CampaignConfig.md) object
Required: No
** [minProvisionedTPS](#API_UpdateCampaign_RequestSyntax) ** <a name="personalize-UpdateCampaign-request-minProvisionedTPS"></a>
Specifies the requested minimum provisioned transactions \(recommendations\) per second that Amazon Personalize will support\.
Type: Integer
Valid Range: Minimum value of 1\.
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
0cd084f24638-1 | Type: Integer
Valid Range: Minimum value of 1\.
Required: No
** [solutionVersionArn](#API_UpdateCampaign_RequestSyntax) ** <a name="personalize-UpdateCampaign-request-solutionVersionArn"></a>
The ARN of a new solution version to deploy\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
c54dcbdb6086-0 | ```
{
"campaignArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
ad1a2a38e6c6-0 | If the action is successful, the service sends back an HTTP 200 response\.
The following data is returned in JSON format by the service\.
** [campaignArn](#API_UpdateCampaign_ResponseSyntax) ** <a name="personalize-UpdateCampaign-response-campaignArn"></a>
The same campaign ARN as given in the request\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
6025b51e7f7d-0 | **InvalidInputException**
Provide a valid value for the field or parameter\.
HTTP Status Code: 400
**ResourceInUseException**
The specified resource is in use\.
HTTP Status Code: 400
**ResourceNotFoundException**
Could not find the specified resource\.
HTTP Status Code: 400 | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
906804a00330-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS Command Line Interface](https://docs.aws.amazon.com/goto/aws-cli/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for \.NET](https://docs.aws.amazon.com/goto/DotNetSDKV3/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for JavaScript](https://docs.aws.amazon.com/goto/AWSJavaScriptSDK/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for PHP V3](https://docs.aws.amazon.com/goto/SdkForPHPV3/personalize-2018-05-22/UpdateCampaign) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
906804a00330-1 | + [AWS SDK for Python](https://docs.aws.amazon.com/goto/boto3/personalize-2018-05-22/UpdateCampaign)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/UpdateCampaign) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_UpdateCampaign.md |
755699346807-0 | Provides a summary of the properties of a recipe\. For a complete listing, call the [DescribeRecipe](API_DescribeRecipe.md) API\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_RecipeSummary.md |
9507a7e1c208-0 | **creationDateTime** <a name="personalize-Type-RecipeSummary-creationDateTime"></a>
The date and time \(in Unix time\) that the recipe was created\.
Type: Timestamp
Required: No
**lastUpdatedDateTime** <a name="personalize-Type-RecipeSummary-lastUpdatedDateTime"></a>
The date and time \(in Unix time\) that the recipe was last updated\.
Type: Timestamp
Required: No
**name** <a name="personalize-Type-RecipeSummary-name"></a>
The name of the recipe\.
Type: String
Length Constraints: Minimum length of 1\. Maximum length of 63\.
Pattern: `^[a-zA-Z0-9][a-zA-Z0-9\-_]*`
Required: No
**recipeArn** <a name="personalize-Type-RecipeSummary-recipeArn"></a>
The Amazon Resource Name \(ARN\) of the recipe\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_RecipeSummary.md |
9507a7e1c208-1 | Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No
**status** <a name="personalize-Type-RecipeSummary-status"></a>
The status of the recipe\.
Type: String
Length Constraints: Maximum length of 256\.
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_RecipeSummary.md |
1b0180d0a221-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/RecipeSummary)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/RecipeSummary)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/RecipeSummary)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/RecipeSummary) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_RecipeSummary.md |
c188f58f7c23-0 | Creates an empty dataset group\. A dataset group contains related datasets that supply data for training a model\. A dataset group can contain at most three datasets, one for each type of dataset:
+ Interactions
+ Items
+ Users
To train a model \(create a solution\), a dataset group that contains an `Interactions` dataset is required\. Call [CreateDataset](API_CreateDataset.md) to add a dataset to the group\.
A dataset group can be in one of the following states:
+ CREATE PENDING > CREATE IN\_PROGRESS > ACTIVE \-or\- CREATE FAILED
+ DELETE PENDING
To get the status of the dataset group, call [DescribeDatasetGroup](API_DescribeDatasetGroup.md)\. If the status shows as CREATE FAILED, the response includes a `failureReason` key, which describes why the creation failed\.
**Note**
You must wait until the `status` of the dataset group is `ACTIVE` before adding a dataset to the group\.
You can specify an AWS Key Management Service \(KMS\) key to encrypt the datasets in the group\. If you specify a KMS key, you must also include an AWS Identity and Access Management \(IAM\) role that has permission to access the key\.
**APIs that require a dataset group ARN in the request**
+ [CreateDataset](API_CreateDataset.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
c188f58f7c23-1 | **APIs that require a dataset group ARN in the request**
+ [CreateDataset](API_CreateDataset.md)
+ [CreateEventTracker](API_CreateEventTracker.md)
+ [CreateSolution](API_CreateSolution.md)
**Related APIs**
+ [ListDatasetGroups](API_ListDatasetGroups.md)
+ [DescribeDatasetGroup](API_DescribeDatasetGroup.md)
+ [DeleteDatasetGroup](API_DeleteDatasetGroup.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
d7e18a0c1b2c-0 | ```
{
"kmsKeyArn": "string",
"name": "string",
"roleArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
223fc2a78a5a-0 | The request accepts the following data in JSON format\.
** [kmsKeyArn](#API_CreateDatasetGroup_RequestSyntax) ** <a name="personalize-CreateDatasetGroup-request-kmsKeyArn"></a>
The Amazon Resource Name \(ARN\) of a KMS key used to encrypt the datasets\.
Type: String
Required: No
** [name](#API_CreateDatasetGroup_RequestSyntax) ** <a name="personalize-CreateDatasetGroup-request-name"></a>
The name for the new dataset group\.
Type: String
Length Constraints: Minimum length of 1\. Maximum length of 63\.
Pattern: `^[a-zA-Z0-9][a-zA-Z0-9\-_]*`
Required: Yes
** [roleArn](#API_CreateDatasetGroup_RequestSyntax) ** <a name="personalize-CreateDatasetGroup-request-roleArn"></a>
The ARN of the IAM role that has permissions to access the KMS key\. Supplying an IAM role is only valid when also specifying a KMS key\.
Type: String
Length Constraints: Maximum length of 256\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
223fc2a78a5a-1 | Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+`
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
3a5d23ec8ee3-0 | ```
{
"datasetGroupArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
9ad9d671e259-0 | If the action is successful, the service sends back an HTTP 200 response\.
The following data is returned in JSON format by the service\.
** [datasetGroupArn](#API_CreateDatasetGroup_ResponseSyntax) ** <a name="personalize-CreateDatasetGroup-response-datasetGroupArn"></a>
The Amazon Resource Name \(ARN\) of the new dataset group\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
b823bf3c3008-0 | **InvalidInputException**
Provide a valid value for the field or parameter\.
HTTP Status Code: 400
**LimitExceededException**
The limit on the number of requests per second has been exceeded\.
HTTP Status Code: 400
**ResourceAlreadyExistsException**
The specified resource already exists\.
HTTP Status Code: 400 | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
597f76d15f36-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS Command Line Interface](https://docs.aws.amazon.com/goto/aws-cli/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for \.NET](https://docs.aws.amazon.com/goto/DotNetSDKV3/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for JavaScript](https://docs.aws.amazon.com/goto/AWSJavaScriptSDK/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for PHP V3](https://docs.aws.amazon.com/goto/SdkForPHPV3/personalize-2018-05-22/CreateDatasetGroup) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
597f76d15f36-1 | + [AWS SDK for Python](https://docs.aws.amazon.com/goto/boto3/personalize-2018-05-22/CreateDatasetGroup)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/CreateDatasetGroup) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDatasetGroup.md |
cde5b061b696-0 | Provides information about an event tracker\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_EventTracker.md |
a4c5365a7b0c-0 | **accountId** <a name="personalize-Type-EventTracker-accountId"></a>
The Amazon AWS account that owns the event tracker\.
Type: String
Length Constraints: Maximum length of 256\.
Required: No
**creationDateTime** <a name="personalize-Type-EventTracker-creationDateTime"></a>
The date and time \(in Unix format\) that the event tracker was created\.
Type: Timestamp
Required: No
**datasetGroupArn** <a name="personalize-Type-EventTracker-datasetGroupArn"></a>
The Amazon Resource Name \(ARN\) of the dataset group that receives the event data\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No
**eventTrackerArn** <a name="personalize-Type-EventTracker-eventTrackerArn"></a>
The ARN of the event tracker\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_EventTracker.md |
a4c5365a7b0c-1 | Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No
**lastUpdatedDateTime** <a name="personalize-Type-EventTracker-lastUpdatedDateTime"></a>
The date and time \(in Unix time\) that the event tracker was last updated\.
Type: Timestamp
Required: No
**name** <a name="personalize-Type-EventTracker-name"></a>
The name of the event tracker\.
Type: String
Length Constraints: Minimum length of 1\. Maximum length of 63\.
Pattern: `^[a-zA-Z0-9][a-zA-Z0-9\-_]*`
Required: No
**status** <a name="personalize-Type-EventTracker-status"></a>
The status of the event tracker\.
An event tracker can be in one of the following states:
+ CREATE PENDING > CREATE IN\_PROGRESS > ACTIVE \-or\- CREATE FAILED
+ DELETE PENDING > DELETE IN\_PROGRESS
Type: String
Length Constraints: Maximum length of 256\.
Required: No
**trackingId** <a name="personalize-Type-EventTracker-trackingId"></a> | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_EventTracker.md |
a4c5365a7b0c-2 | Required: No
**trackingId** <a name="personalize-Type-EventTracker-trackingId"></a>
The ID of the event tracker\. Include this ID in requests to the [PutEvents](https://docs.aws.amazon.com/personalize/latest/dg/API_UBS_PutEvents.html) API\.
Type: String
Length Constraints: Maximum length of 256\.
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_EventTracker.md |
3131f6d38fb2-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/EventTracker)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/EventTracker)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/EventTracker)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/EventTracker) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_EventTracker.md |
05faa9ad8828-0 | Cloud security at AWS is the highest priority\. As an AWS customer, you benefit from a data center and network architecture that is built to meet the requirements of the most security\-sensitive organizations\.
Security is a shared responsibility between AWS and you\. The [shared responsibility model](http://aws.amazon.com/compliance/shared-responsibility-model/) describes this as security *of* the cloud and security *in* the cloud:
+ **Security of the cloud** – AWS is responsible for protecting the infrastructure that runs AWS services in the AWS Cloud\. AWS also provides you with services that you can use securely\. Third\-party auditors regularly test and verify the effectiveness of our security as part of the [AWS Compliance Programs](http://aws.amazon.com/compliance/programs/)\. To learn about the compliance programs that apply to Amazon Personalize, see [AWS Services in Scope by Compliance Program](http://aws.amazon.com/compliance/services-in-scope/)\.
+ **Security in the cloud** – Your responsibility is determined by the AWS service that you use\. You are also responsible for other factors including the sensitivity of your data, your company’s requirements, and applicable laws and regulations\.
This documentation helps you understand how to apply the shared responsibility model when using Amazon Personalize\. The following topics show you how to configure Amazon Personalize to meet your security and compliance objectives\. You also learn how to use other AWS services that help you to monitor and secure your Amazon Personalize resources\.
**Topics**
+ [Data Protection in Amazon Personalize](data-protection.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security.md |
05faa9ad8828-1 | **Topics**
+ [Data Protection in Amazon Personalize](data-protection.md)
+ [Identity and Access Management for Amazon Personalize](security-iam.md)
+ [Logging and Monitoring in Amazon Personalize](logging-monitoring.md)
+ [Compliance Validation for Amazon Personalize](SERVICENAME-compliance.md)
+ [Resilience in Amazon Personalize](disaster-recovery-resiliency.md)
+ [Infrastructure Security in Amazon Personalize](infrastructure-security.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/security.md |
5a3f813ee420-0 | To make recommendations, Amazon Personalize uses a machine learning model that is trained with your data\. The data used to train the model is stored in related datasets in a dataset group\. Each model is trained by using a recipe that contains an algorithm for a specific use case\. In Amazon Personalize, a trained model is known as a solution version\. A solution version is deployed for use in a campaign\. Users of your applications can receive recommendations through the campaign\. For example, a campaign can show movie recommendations on a website or application where the title shown is based on viewing habits that were part of the dataset\.
A dataset can grow over time and your models can be retrained on the new data\. The data can come from new metadata and the consumption of real\-time user event data\. In the previous movie recommendations example, you could add new movies as they are released, and add a movie that is chosen by the signed\-in user\.
Amazon Personalize has an AWS console that you can use to create, manage, and deploy solution versions\. Alternatively, you can use the AWS Command Line Interface \(AWS CLI\) or one of the Amazon Personalize SDKs\.
Amazon Personalize consists of three related components:
+ Amazon Personalize – Use this to create, manage, and deploy solution versions\.
+ Amazon Personalize Events – Use this to record [events](API_UBS_Event.md) to add to your training data\. For more information, see [Recording Events](recording-events.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
5a3f813ee420-1 | + Amazon Personalize Runtime – Use this to get recommendations from a campaign \(deployed solution version\)\. For more information, see [Getting Recommendations](getting-recommendations.md)\.
**Topics**
+ [Amazon Personalize Workflow](#how-it-works-workflow)
+ [Datasets and Dataset Groups](#how-it-works-dataset)
+ [User Events](#how-it-works-events)
+ [Recipes and Solutions](#how-it-works-personalize-service-training)
+ [Metrics](#how-it-works-evaluation)
+ [Campaigns](#how-it-works-campaigns)
+ [Recommendations](#how-it-works-personalize-recommendations) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
686084e4566b-0 | The workflow for training, deploying, and getting recommendations from a campaign is:
1. Create related datasets and a dataset group\.
1. Get training data\.
+ Import historical data to the dataset group\.
+ Record user events to the dataset group\.
1. Create a solution version \(trained model\) using a recipe\.
1. Evaluate the solution version using metrics\.
1. Create a campaign \(deploy the solution version\)\.
1. Provide recommendations for users\.
The following sections provide a brief overview of the above workflow\. Each section includes a link to the main topic that describes the step in depth and which provides a Python example\.
The [Getting Started](getting-started.md) guides provide step\-by\-step procedures using the Amazon Personalize console, the AWS CLI, and a Jupyter \(iPython\) notebook\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
d68fca0307fe-0 | Amazon Personalize requires data, stored in Amazon Personalize datasets, in order to train a model\.
There are two ways to provide the training data\. You can import historical data from an Amazon S3 bucket, and you can record event data as it is created\.
A dataset group contains related datasets\. Three types of historical datasets are created by the customer \(users, items, and interactions\), and one type is created by Amazon Personalize for live\-event interactions\. A dataset group can contain only one of each kind of dataset\.
You can create dataset groups to serve different purposes\. For example, you might have an application that provides recommendations for purchasing shoes and another that provides recommendations for places to visit in Europe\. In Amazon Personalize, each application would have its own dataset group\.
Historical data must be provided in a CSV file\. Each dataset type has a unique schema that specifies the contents of the CSV file\.
The minimum data requirements to train a model are as follows:
+ 1000 records of combined interaction data \(after filtering by `eventType` and `eventValueThreshold`, if provided\)\.
+ 25 unique users with at least 2 interactions each\.
**Note**
Using existing data allows you to immediately start training a model\. If you rely on recorded data as it is created, and there is no historical data, it can take a while before training can begin\.
For more information, see [Preparing and Importing Data](data-prep.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
d0fa7f0180d0-0 | Amazon Personalize can consume real time [user events](API_UBS_Event.md) to be used for model training either alone or combined with historical data\.
For more information, see [Recording Events](recording-events.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
6fe4c21f5c3d-0 | After enough data is available in the interactions datasets \(historical and live events\), the data can be used to train a model\. A trained model is known as a solution version\. The model is trained using a recipe\. The recipes available in Amazon Personalize are made of an algorithm and the data processing steps that optimize a solution for a certain type of recommendation based on your input data\.
Amazon Personalize supports a number of predefined recipes\. Amazon Personalize can automatically choose the most appropriate recipe based on its analysis of the training data\. Alternatively, you can choose which recipe to train the model with\. Each recipe has its own use case and you should choose the recipe that best fits your needs\.
Each time you train a model, it is assigned a new solution version\. Use the solution version ARN to identify which version of the solution you want to use for your campaign\.
For more information, see [Creating a Solution](training-deploying-solutions.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
cbefbe3ee63c-0 | After you have created your solution version, you evaluate the metrics that were created during training\. The metrics give an indication of the solution version's performance\. The console shows you the metrics and allows you to create a new solution version, as necessary\. Alternatively, you can call the [GetSolutionMetrics](API_GetSolutionMetrics.md) API\. Typically, you train your model with multiple recipes and use the recipe that results in the metrics that show the best performance\. After you have created a solution version based on your chosen recipe, the solution version is ready for deployment as a campaign\.
For more information, see [Evaluating a Solution Version](working-with-training-metrics.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
e3fd32e635fb-0 | A deployed solution version is known as a campaign\. A campaign allows Amazon Personalize to make recommendations for your users\. To deploy a solution version, you create a campaign in the console or by calling the [CreateCampaign](API_CreateCampaign.md) API\. You choose which version of the solution to use\.
For more information, see [Creating a Campaign](campaigns.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
37726817e015-0 | After you create a campaign, you are able to get recommendations in real\-time or as part of a batch workflow with purely historical data\. For more information, see [Getting Recommendations](getting-recommendations.md)\.
**Real\-Time Recommendations**
Get real\-time recommendations in situations where you want to update recommendations as customers use your application\. For example, say you provide movie recommendations to users signed into your application, and you want recommendations to update as they choose different movies\.
You are able to get two different types of real\-time recommendations:
+ For user\-personalization and related\-items recipes, use the [GetRecommendations](API_RS_GetRecommendations.md) API to get a list of recommended items\. For example, movies can be recommended for users who are signed\-in to a website\.
+ For personalized\-ranking recipes, use the [GetPersonalizedRanking](API_RS_GetPersonalizedRanking.md) API to have Amazon Personalize re\-rank a list of recommended items based on a specified query\.
For more information see [Getting Real\-Time Recommendations](getting-real-time-recommendations.md)\.
**Batch Recommendations**
Get batch recommendations in situations where you have large datasets that do not require real\-time updates\. For instance, you might create a batch inference job to get product recommendations for all users on an email list, or to get [item\-to\-item similarities \(SIMS\)](native-recipe-sims.md) across an inventory\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
37726817e015-1 | For more information see [Getting Batch Recommendations](recommendations-batch.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/how-it-works.md |
ee2bc3772bd8-0 | The output configuration parameters of a batch inference job\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_BatchInferenceJobOutput.md |
9d080c2a4d7a-0 | **s3DataDestination** <a name="personalize-Type-BatchInferenceJobOutput-s3DataDestination"></a>
Information on the Amazon S3 bucket in which the batch inference job's output is stored\.
Type: [S3DataConfig](API_S3DataConfig.md) object
Required: Yes | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_BatchInferenceJobOutput.md |
39789d8cf353-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/BatchInferenceJobOutput)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/BatchInferenceJobOutput)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/BatchInferenceJobOutput)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/BatchInferenceJobOutput) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_BatchInferenceJobOutput.md |
84900969e3dc-0 | Gets the metrics for the specified solution version\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
f5c742eb7bfe-0 | ```
{
"solutionVersionArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
17d3e5b137f2-0 | The request accepts the following data in JSON format\.
** [solutionVersionArn](#API_GetSolutionMetrics_RequestSyntax) ** <a name="personalize-GetSolutionMetrics-request-solutionVersionArn"></a>
The Amazon Resource Name \(ARN\) of the solution version for which to get metrics\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: Yes | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
98d6a21bb84f-0 | ```
{
"metrics": {
"string" : number
},
"solutionVersionArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
bc705be01a6a-0 | If the action is successful, the service sends back an HTTP 200 response\.
The following data is returned in JSON format by the service\.
** [metrics](#API_GetSolutionMetrics_ResponseSyntax) ** <a name="personalize-GetSolutionMetrics-response-metrics"></a>
The metrics for the solution version\.
Type: String to double map
Map Entries: Maximum number of 100 items\.
Key Length Constraints: Maximum length of 256\.
** [solutionVersionArn](#API_GetSolutionMetrics_ResponseSyntax) ** <a name="personalize-GetSolutionMetrics-response-solutionVersionArn"></a>
The same solution version ARN as specified in the request\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
03970a9309d1-0 | **InvalidInputException**
Provide a valid value for the field or parameter\.
HTTP Status Code: 400
**ResourceInUseException**
The specified resource is in use\.
HTTP Status Code: 400
**ResourceNotFoundException**
Could not find the specified resource\.
HTTP Status Code: 400 | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
b43cda6b628d-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS Command Line Interface](https://docs.aws.amazon.com/goto/aws-cli/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for \.NET](https://docs.aws.amazon.com/goto/DotNetSDKV3/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for JavaScript](https://docs.aws.amazon.com/goto/AWSJavaScriptSDK/personalize-2018-05-22/GetSolutionMetrics) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
b43cda6b628d-1 | + [AWS SDK for PHP V3](https://docs.aws.amazon.com/goto/SdkForPHPV3/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for Python](https://docs.aws.amazon.com/goto/boto3/personalize-2018-05-22/GetSolutionMetrics)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/GetSolutionMetrics) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_GetSolutionMetrics.md |
d96d796c50e8-0 | Before using Amazon Personalize, you must have an Amazon Web Services \(AWS\) account\. After you have an AWS account, you can access Amazon Personalize through the Amazon Personalize console, the AWS Command Line Interface \(AWS CLI\), or the AWS SDKs\.
This guide includes examples for AWS CLI, Python, and JavaScript with AWS Amplify\.
**Topics**
+ [Sign Up for AWS](#aws-personalize-set-up-aws-account)
+ [Regions and Endpoints](#endpoints)
+ [Setting Up Permissions](aws-personalize-set-up-permissions.md)
+ [Setting Up the AWS CLI](aws-personalize-set-up-aws-cli.md)
+ [Setting Up the AWS SDKs](aws-personalize-set-up-sdks.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/setup.md |
7b3575223056-0 | When you sign up for Amazon Web Services \(AWS\), your account is automatically signed up for all services in AWS, including Amazon Personalize\. You are charged only for the services that you use\.
If you have an AWS account already, skip to the next task\. If you don't have an AWS account, use the following procedure to create one\.<a name="proc-set-up-aws-account"></a>
**To sign up for AWS**
1. Open [https://aws\.amazon\.com](https://aws.amazon.com), and then choose **Create an AWS Account**\.
1. Follow the on\-screen instructions to complete the account creation\. Note your 12\-digit AWS account number\. Part of the sign\-up procedure involves receiving a phone call and entering a PIN using the phone keypad\.
1. Create an AWS Identity and Access Management \(IAM\) admin user\. See [Creating Your First IAM User and Group](https://docs.aws.amazon.com/IAM/latest/UserGuide/getting-started_create-admin-group.html) in the *AWS Identity and Access Management User Guide* for instructions\.
An IAM user with administrator permissions has unrestricted access to the AWS services in your account\. For information about restricting access to Amazon Personalize operations, see [Amazon Personalize Identity\-Based Policies](security_iam_service-with-iam.md#security_iam_service-with-iam-id-based-policies) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/setup.md |
7b3575223056-1 | 1. Create an IAM user for use with Amazon Personalize\. The account requires certain permissions\. For more information, see [Setting Up Permissions](aws-personalize-set-up-permissions.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/setup.md |
4513bb30196e-0 | An endpoint is a URL that is the entry point for a web service\. Each endpoint is associated with a specific AWS region\. Pay attention to the default regions of the Amazon Personalize console, the AWS CLI, and the Amazon Personalize SDKs, as all Amazon Personalize components of a given campaign \(dataset, solution, campaign, event tracker\) must be created in the same region\. For the regions and endpoints supported by Amazon Personalize, see [Regions | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/setup.md |
4513bb30196e-1 | endpoints supported by Amazon Personalize, see [Regions and Endpoints](https://docs.aws.amazon.com/general/latest/gr/rande.html#personalize_region)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/setup.md |
4f28a8626897-0 | The RELATED\_ITEMS recipe, SIMS, returns items similar to a given item\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/related-items-recipes.md |
e96d666cbc77-0 | The item\-to\-item similarities \(SIMS\) recipe generates items similar to a given item based on the co\-occurrence of the item in user history in the user\-item interaction dataset\. If sufficient user behavior data for an item isn't available, or if the specified item ID isn't found, the recipe returns popular items as recommendations\. Use the SIMS recipe to improve item discovery\. Training is faster with the SIMS recipe compared to other recipes\.
To train a model, the SIMS recipe uses the Interactions dataset from a dataset group\. A dataset group is a set of related datasets, which can include the Users, Items, and Interactions datasets\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/related-items-recipes.md |
c628a56860bb-0 | Returns a list of solutions that use the given dataset group\. When a dataset group is not specified, all the solutions associated with the account are listed\. The response provides the properties for each solution, including the Amazon Resource Name \(ARN\)\. For more information on solutions, see [CreateSolution](API_CreateSolution.md)\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
2b3650e0890a-0 | ```
{
"datasetGroupArn": "string",
"maxResults": number,
"nextToken": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
e79381323cc9-0 | The request accepts the following data in JSON format\.
** [datasetGroupArn](#API_ListSolutions_RequestSyntax) ** <a name="personalize-ListSolutions-request-datasetGroupArn"></a>
The Amazon Resource Name \(ARN\) of the dataset group\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: No
** [maxResults](#API_ListSolutions_RequestSyntax) ** <a name="personalize-ListSolutions-request-maxResults"></a>
The maximum number of solutions to return\.
Type: Integer
Valid Range: Minimum value of 1\. Maximum value of 100\.
Required: No
** [nextToken](#API_ListSolutions_RequestSyntax) ** <a name="personalize-ListSolutions-request-nextToken"></a>
A token returned from the previous call to `ListSolutions` for getting the next set of solutions \(if they exist\)\.
Type: String
Length Constraints: Maximum length of 1300\.
Required: No | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
93d568418305-0 | ```
{
"nextToken": "string",
"solutions": [
{
"creationDateTime": number,
"lastUpdatedDateTime": number,
"name": "string",
"solutionArn": "string",
"status": "string"
}
]
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
d5a17b770c37-0 | If the action is successful, the service sends back an HTTP 200 response\.
The following data is returned in JSON format by the service\.
** [nextToken](#API_ListSolutions_ResponseSyntax) ** <a name="personalize-ListSolutions-response-nextToken"></a>
A token for getting the next set of solutions \(if they exist\)\.
Type: String
Length Constraints: Maximum length of 1300\.
** [solutions](#API_ListSolutions_ResponseSyntax) ** <a name="personalize-ListSolutions-response-solutions"></a>
A list of the current solutions\.
Type: Array of [SolutionSummary](API_SolutionSummary.md) objects
Array Members: Maximum number of 100 items\. | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
0cc09be104a8-0 | **InvalidInputException**
Provide a valid value for the field or parameter\.
HTTP Status Code: 400
**InvalidNextTokenException**
The token is not valid\.
HTTP Status Code: 400 | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
6320e5bfcab7-0 | For more information about using this API in one of the language\-specific AWS SDKs, see the following:
+ [AWS Command Line Interface](https://docs.aws.amazon.com/goto/aws-cli/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for \.NET](https://docs.aws.amazon.com/goto/DotNetSDKV3/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for C\+\+](https://docs.aws.amazon.com/goto/SdkForCpp/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for Go](https://docs.aws.amazon.com/goto/SdkForGoV1/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for Java](https://docs.aws.amazon.com/goto/SdkForJava/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for JavaScript](https://docs.aws.amazon.com/goto/AWSJavaScriptSDK/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for PHP V3](https://docs.aws.amazon.com/goto/SdkForPHPV3/personalize-2018-05-22/ListSolutions) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
6320e5bfcab7-1 | + [AWS SDK for Python](https://docs.aws.amazon.com/goto/boto3/personalize-2018-05-22/ListSolutions)
+ [AWS SDK for Ruby V3](https://docs.aws.amazon.com/goto/SdkForRubyV3/personalize-2018-05-22/ListSolutions) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_ListSolutions.md |
82cadbfd8d11-0 | Creates an empty dataset and adds it to the specified dataset group\. Use [CreateDatasetImportJob](API_CreateDatasetImportJob.md) to import your training data to a dataset\.
There are three types of datasets:
+ Interactions
+ Items
+ Users
Each dataset type has an associated schema with required field types\. Only the `Interactions` dataset is required in order to train a model \(also referred to as creating a solution\)\.
A dataset can be in one of the following states:
+ CREATE PENDING > CREATE IN\_PROGRESS > ACTIVE \-or\- CREATE FAILED
+ DELETE PENDING > DELETE IN\_PROGRESS
To get the status of the dataset, call [DescribeDataset](API_DescribeDataset.md)\.
**Related APIs**
+ [CreateDatasetGroup](API_CreateDatasetGroup.md)
+ [ListDatasets](API_ListDatasets.md)
+ [DescribeDataset](API_DescribeDataset.md)
+ [DeleteDataset](API_DeleteDataset.md) | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDataset.md |
3d0d823db845-0 | ```
{
"datasetGroupArn": "string",
"datasetType": "string",
"name": "string",
"schemaArn": "string"
}
``` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDataset.md |
e4b33499a641-0 | The request accepts the following data in JSON format\.
** [datasetGroupArn](#API_CreateDataset_RequestSyntax) ** <a name="personalize-CreateDataset-request-datasetGroupArn"></a>
The Amazon Resource Name \(ARN\) of the dataset group to add the dataset to\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: Yes
** [datasetType](#API_CreateDataset_RequestSyntax) ** <a name="personalize-CreateDataset-request-datasetType"></a>
The type of dataset\.
One of the following \(case insensitive\) values:
+ Interactions
+ Items
+ Users
Type: String
Length Constraints: Maximum length of 256\.
Required: Yes
** [name](#API_CreateDataset_RequestSyntax) ** <a name="personalize-CreateDataset-request-name"></a>
The name for the dataset\.
Type: String
Length Constraints: Minimum length of 1\. Maximum length of 63\.
Pattern: `^[a-zA-Z0-9][a-zA-Z0-9\-_]*` | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDataset.md |
e4b33499a641-1 | Pattern: `^[a-zA-Z0-9][a-zA-Z0-9\-_]*`
Required: Yes
** [schemaArn](#API_CreateDataset_RequestSyntax) ** <a name="personalize-CreateDataset-request-schemaArn"></a>
The ARN of the schema to associate with the dataset\. The schema defines the dataset fields\.
Type: String
Length Constraints: Maximum length of 256\.
Pattern: `arn:([a-z\d-]+):personalize:.*:.*:.+`
Required: Yes | https://github.com/siagholami/aws-documentation/tree/main/documents/amazon-personalize-developer-guide/doc_source/API_CreateDataset.md |
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