Send partial row updates to Real-Time Customer Profile using Data Prep

WARNING
Ingestion on Experience Data Model (XDM) Entity Update messages (with JSON PATCH operations) for Profile updates via the DCS inlet has been deprecated. As an alternative, you can ingest raw data into the DCS inlet and specify the necessary data mappings to transform your data into XDM-compliant messages for Profile updates.

Streaming upserts in Data Prep allows you to send partial row updates to Real-Time Customer Profile data while also creating and establishing new identity links with a single API request.

By streaming upserts, you can retain the format of your data while translating that data to Real-Time Customer Profile PATCH requests during ingestion. Based on the inputs you provide, Data Prep allows you to send a single API payload and translate the data to both Real-Time Customer Profile PATCH and Identity Service CREATE requests.

NOTE
To leverage upsert functionality, it is recommended that you turn off XDM-compatible configurations during data ingestion and re-map the incoming payload using Data Prep Mapper.

This document provides information on how to stream upserts in Data Prep.

Getting started

This overview requires a working understanding of the following components of Adobe Experience Platform:

  • Data Prep: Data Prep allows data engineers to map, transform, and validate data to and from Experience Data Model (XDM).
  • Identity Service: Gain a better view of individual customers and their behavior by bridging identities across devices and systems.
  • Real-Time Customer Profile: Provides a unified, customer profile in real-time based on aggregated data from multiple sources.
  • Sources: Experience Platform allows data to be ingested from various sources while providing you with the ability to structure, label, and enhance incoming data using Platform services.

Use streaming upserts in Data Prep streaming-upserts-in-data-prep

NOTE
The following sources support the use of streaming upserts:

Streaming upserts high-level workflow

Streaming upserts in Data Prep works as follows:

  • You must first create and enable a dataset for Profile consumption. See the guide on enabling a dataset for Profile for more information.

  • If new identities must be linked, then you must also create an additional dataset with the same schema as your Profile dataset.

  • Once your dataset(s) are prepared, you must create a dataflow to map your incoming request to the Profile dataset;

  • Next, you must update the incoming request to include the necessary headers. These headers define:

    • The data operation that is needed to be performed with Profile: create, merge, and delete.
    • The optional identity operation to be performed with Identity Service: create.

Configure the identity dataset

If new identities must be linked, then you must create and pass an additional dataset in the incoming payload. When creating an identity dataset, you must ensure that the following requirements are met:

  • The identity dataset must have its associated schema as the Profile dataset. A mismatch of schemas may lead to inconsistent system behavior.
  • However, you must ensure that the identity dataset is different from the Profile dataset. If the datasets are the same, then data will be overwritten instead of updated.
  • While the initial dataset must be enabled for Profile, the identity dataset should not be enabled for Profile. Otherwise, data will also be overwritten instead of updated. However, the identity dataset should be enabled for Identity Service.

Required fields in the schemas associated with the identity dataset identity-dataset-required-fileds

If your schema contains required fields, validation of the dataset must be suppressed in order to enable Identity Service to only receive the identities. You can suppress validation by applying the disabled value to the acp_validationContext parameter. See the example below:

curl -X POST 'https://platform.adobe.io/data/foundation/catalog/dataSets/62257bef7a75461948ebcaaa' \
  -H 'Authorization: Bearer {ACCESS_TOKEN}' \
  -H 'Content-Type: application/json' \
  -H 'x-api-key: {API_KEY}' \
  -H 'x-gw-ims-org-id: {IMS_ORG}' \
  -H 'x-sandbox-name: {SANDBOX_NAME}' \
  -d '{
    "tags": {
        "acp_validationContext": [
            "disabled"
        ],
        "unifiedProfile": [
            "enabled:false"
        ],
        "unifiedIdentity": [
            "enabled:true"
        ]
    }
}'
TIP
You do not need to do any additional configuration if the schema associated with the identity dataset does not have any required fields.

Incoming payload structure

The following displays an example of an incoming payload structure that establishes new identity links.

Payload with identity configuration

{
  "header": {
    "flowId": "923e2ac3-3869-46ec-9e6f-7012c4e23f69",
    "imsOrgId": "{ORG_ID}",
    "datasetId": "621fc19ab33d941949af16c8",
    "operations": {
        "data": "create" (default)/"merge"/"delete",
        "identity": "create",
        "identityDatasetId": "621fc19ab33d941949af16d9"
    }
  }
... //The raw data attributes are included here as the key/value pairs of the "body" property.
}
Parameter
Description
flowId
A unique ID to identify a dataflow. This dataflow ID should correspond to the source connection created with Amazon Kinesis, Azure Event Hubs, or HTTP API. This dataflow should also have a Profile-enabled dataset as the target dataset. Note: The ID of the Profile-enabled target dataset is also used as your datasetId parameter.
imsOrgId
The ID that corresponds with your organization.
datasetId
The ID of the Profile-enabled target dataset of your dataflow. Note: This is the same ID as the Profile-enabled target dataset ID found in your dataflow.
operations
This parameter outlines the actions that Data Prep will take based on the incoming request.
operations.data
Defines the actions that must be performed in Real-Time Customer Profile.
operations.identity
Defines the operations permitted on the data by Identity Service.
operations.identityDatasetId
(Optional) The ID of the identity dataset that is required only if new identities must be linked.

Supported operations

The following operations are supported by Real-Time Customer Profile:

Operations
Description
create
The default operation. This generates an XDM entity create method for Real-Time Customer Profile.
merge
This generates an XDM entity update method for Real-Time Customer Profile.
delete
This generates an XDM entity delete method for Real-Time Customer Profile and permanently removes the data from the Profile store.

The following operations are supported by Identity Service:

Operations
Descriptions
create
The only permitted operation for this parameter. If create is passed as a value for operations.identity, then Data Prep generates an XDM entity create request for Identity Service. If the identity already exists, then the identity is ignored. Note: If operations.identity is set to create, then the identityDatasetId must also be specified. The XDM entity create message generated internally by Data Prep component will be generated for this dataset id.

Payload without identity configuration

If new identities do not need to be linked, then you can omit the identity and identityDatasetId parameters in the operations. Doing so sends data only to Real-Time Customer Profile and skips the Identity Service. See the payload below for an example:


{
  "header": {
    "flowId": "923e2ac3-3869-46ec-9e6f-7012c4e23f69",
    "imsOrgId": "{ORG_ID}",
    "datasetId": "621fc19ab33d941949af16c8",
    "operations": {
        "data": "create"/"merge"/"delete",
    }
  }
... //The raw data attributes are included here as the key/value pairs of the "body" property.
}

Dynamically pass primary identities

For XDM updates, the schema must be enabled for Profile and contain a primary identity. You can specify the primary identity of an XDM schema in two ways:

  • Designate a static field as the primary identity in the XDM schema;
  • Designate one of the identity fields as the primary identity through the identity map field group in the XDM schema.

Designate a static field as the primary identity field in the XDM schema

In the example below, state, homePhone.number and other attributes are upserted with their respective given values into the Profile with the primary identity of sampleEmail@gmail.com. An XDM entity update message is then generated by the streaming Data Prep component. Real-Time Customer Profile then confirms that XDM update message to upsert the profile record.

NOTE
In this example, identities will not get linked together as there are no operations defined for identity.
curl -X POST 'https://dcs.adobedc.net/collection/9aba816d350a69c4abbd283eb5818ec3583275ffce4880ffc482be5a9d810c4b' \
  -H 'Content-Type: application/json' \
  -H 'x-adobe-flow-id: d5262d48-0f47-4949-be6d-795f06933527' \
  -d '{
    "header": {
        "flowId" : "d5262d48-0f47-4949-be6d-795f06933527",
        "imsOrgId": "{ORG_ID}",
        "datasetId": "62259f817f62d71947929a7b",
        "operations": {
         "data": "create"
     }
    },
    {
        "body": {
        "homeAddress": {
            "country": "US",
            "state": "GA",
            "region": "va7"
        },
        "homePhone": {
            "number": "123.456.799"
        },
        "identityMap": {
            "Email": [{
                "id": "sampleEmail@gmail.com",
                "primary": true
            }]
        },
      "personalEmail": {
            "address": "sampleEmail@gmail.com",
            "primary": true
       },
      "personID": "346576345",
      "_id": "346576345",
      "timestamp": "2021-05-05T17:51:45.1880+02",
      "workEmail": "sampleWorkEmail@gmail.com"
  }
}'

Designate one of the identity fields as the primary identity through the identity map field group in the XDM schema

In this example, the header contains the operations attribute with the identity and identityDatasetId properties. This allows data to be merged with Real-Time Customer Profile and also for identities to be passed to Identity Service.

curl -X POST 'https://dcs.adobedc.net/collection/9aba816d350a69c4abbd283eb5818ec3583275ffce4880ffc482be5a9d810c4b' \
  -H 'Content-Type: application/json' \
  -H 'x-adobe-flow-id: d5262d48-0f47-4949-be6d-795f06933527' \
  -d '{
    "header": {
        "flowId" : "d5262d48-0f47-4949-be6d-795f06933527",
        "imsOrgId": "{ORG_ID}",
        "datasetId": "62259f817f62d71947929a7b",
        "operations": {
            "data": "merge",
            "identity": "create",
            "identityDatasetId": "6254a93b851ecd194b64af9e"
      }
    },
    {
       "body": {
        "homeAddress": {
            "country": "US",
            "state": "GA",
            "region": "va7"
        },
        "homePhone": {
            "number": "123.456.799"
        },
        "identityMap": {
            "Email": [{
                "id": "sampleEmail@gmail.com",
                "primary": true
            }]
        },
      "personalEmail": {
            "address": "sampleEmail@gmail.com",
            "primary": true
       },
      "personID": "346576345",
      "_id": "346576345",
      "timestamp": "2021-05-05T17:51:45.1880+02",
      "workEmail": "sampleWorkEmail@gmail.com"
  }
 }'

Known limitations and key considerations

The following outlines a list of known limitations to consider when streaming upserts with Data Prep:

  • The streaming upserts method should only be used when sending partial row updates to Real-Time Customer Profile. Partial row updates are not consumed by data lake.
  • The streaming upserts method does not support updating, replacing, and removing identities. New identities are created if they do not exist. Hence the identity operation must always be set to create. If an identity already exists, the operation is a no-op.
  • The streaming upserts method currently does not support Adobe Experience Platform Web SDK and Adobe Experience Platform Mobile SDK.

Next steps

By reading this document, you should now understand how to stream upserts in Data Prep to send partial row updates to your Real-Time Customer Profile data, while also creating and linking identities with a single API request. For more information on other Data Prep features, please read the Data Prep overview. To learn how to use mapping sets within the Data Prep API, please read the Data Prep developer guide.

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