Create a streaming dataflow for raw data using the Flow Service API

This tutorial covers the steps for retrieving raw data from a streaming source connector and bringing them to Experience Platform using the Flow Service API.

Getting started

This tutorial requires you to have a working understanding of the following components of Adobe Experience Platform:

Using Platform APIs

For information on how to successfully make calls to Platform APIs, see the guide on getting started with Platform APIs.

Create a source connection source

This tutorial also requires you to have a valid source connection ID for a streaming connector. If you do not have this information, see the following tutorials on create a streaming source connection before attempting this tutorial:

Create a target XDM schema target-schema

In order for the source data to be used in Platform, a target schema must be created to structure the source data according to your needs. The target schema is then used to create a Platform dataset in which the source data is contained. This target XDM schema also extends the XDM Individual Profile class.

To create a target XDM schema, make a POST request to the /schemas endpoint of the Schema Registry API.

API format

POST /tenant/schemas

Request

The following example request creates an XDM schema that extends the XDM Individual Profile class.

curl -X POST \
    'https://platform.adobe.io/data/foundation/schemaregistry/tenant/schemas' \
    -H 'Authorization: Bearer {ACCESS_TOKEN}' \
    -H 'x-api-key: {API_KEY}' \
    -H 'x-gw-ims-org-id: {ORG_ID}' \
    -H 'x-sandbox-name: {SANDBOX_NAME}' \
    -H 'Content-Type: application/json' \
    -d '{
        "type": "object",
        "title": "Sample schema for a streaming connector",
        "description": "Sample schema for a streaming connector",
        "allOf": [
            {
                "$ref": "https://ns.adobe.com/xdm/context/profile"
            },
            {
                "$ref": "https://ns.adobe.com/xdm/context/profile-person-details"
            },
            {
                "$ref": "https://ns.adobe.com/xdm/context/profile-personal-details"
            }
        ],
        "meta:containerId": "tenant",
        "meta:resourceType": "schemas",
        "meta:xdmType": "object",
        "meta:class": "https://ns.adobe.com/xdm/context/profile"
    }'

Response

A successful response returns details of the newly created schema including its unique identifier ($id). This ID is required in later steps to create a target dataset, mapping, and dataflow.

{
    "$id": "https://ns.adobe.com/{TENANT_ID}/schemas/e45dd983026ce0daec5185cfddd48cbc0509015d880d6186",
    "meta:altId": "_{TENANT_ID}.schemas.e45dd983026ce0daec5185cfddd48cbc0509015d880d6186",
    "meta:resourceType": "schemas",
    "version": "1.0",
    "title": "Sample schema for a streaming connector",
    "type": "object",
    "description": "Sample schema for a streaming connector",
    "allOf": [
        {
            "$ref": "https://ns.adobe.com/xdm/context/profile",
            "type": "object",
            "meta:xdmType": "object"
        },
        {
            "$ref": "https://ns.adobe.com/xdm/context/profile-person-details",
            "type": "object",
            "meta:xdmType": "object"
        },
        {
            "$ref": "https://ns.adobe.com/xdm/context/profile-personal-details",
            "type": "object",
            "meta:xdmType": "object"
        }
    ],
    "refs": [
        "https://ns.adobe.com/xdm/context/profile-person-details",
        "https://ns.adobe.com/xdm/context/profile-personal-details",
        "https://ns.adobe.com/xdm/context/profile"
    ],
    "imsOrg": "{ORG_ID}",
    "meta:extensible": false,
    "meta:abstract": false,
    "meta:extends": [
        "https://ns.adobe.com/xdm/context/profile-person-details",
        "https://ns.adobe.com/xdm/context/profile-personal-details",
        "https://ns.adobe.com/xdm/common/auditable",
        "https://ns.adobe.com/xdm/data/record",
        "https://ns.adobe.com/xdm/context/profile"
    ],
    "meta:xdmType": "object",
    "meta:registryMetadata": {
        "repo:createdDate": 1604960074752,
        "repo:lastModifiedDate": 1604960074752,
        "xdm:createdClientId": "{CREATED_CLIENT_ID}",
        "xdm:lastModifiedClientId": "{MODIFIED_CLIENT_ID}",
        "xdm:createdUserId": "{CREATED_USER_ID}",
        "xdm:lastModifiedUserId": "{MODIFIED_USER_ID}",
        "eTag": "8522a151effd974429518ed90c3eaf6efc9bf6ffb6644087a85c6d4455dcd045",
        "meta:globalLibVersion": "1.16.1"
    },
    "meta:class": "https://ns.adobe.com/xdm/context/profile",
    "meta:containerId": "tenant",
    "meta:sandboxId": "{SANDBOX_ID}",
    "meta:sandboxType": "production",
    "meta:tenantNamespace": "_{TENANT_ID}"
}

Create a target dataset

With a target XDM schema created and its unique $id you can now create a target dataset to contain your source data. To create a target dataset, make a POST request to the dataSets endpoint of the Catalog Service API, while providing the ID of the target schema within the payload.

API format

POST /catalog/dataSets

Request

curl -X POST \
    'https://platform.adobe.io/data/foundation/catalog/dataSets?requestDataSource=true' \
    -H 'Authorization: Bearer {ACCESS_TOKEN}' \
    -H 'x-api-key: {API_KEY}' \
    -H 'x-gw-ims-org-id: {ORG_ID}' \
    -H 'x-sandbox-name: {SANDBOX_NAME}' \
    -H 'Content-Type: application/json' \
    -d '{
        "name": "Test streaming dataset",
        "schemaRef": {
            "id": "https://ns.adobe.com/{TENANT_ID}/schemas/e45dd983026ce0daec5185cfddd48cbc0509015d880d6186",
            "contentType": "application/vnd.adobe.xed-full-notext+json; version=1"
        },
        "tags": {
            "identity": [
            "enabled:true"
            ],
            "profile": [
            "enabled:true"
            ]
        }
    }'

Response

A successful response returns an array containing the ID of the newly created dataset in the format "@/datasets/{DATASET_ID}". The dataset ID is a read-only, system-generated string that is used to reference the dataset in API calls. The target dataset ID is required in later steps to create a target connection and a dataflow.

[
    "@/dataSets/5f7187bac6d00f194fb937c0"
]

Create a target connection target-connection

Target connections create and manage a destination connection to Platform or any location where the transferred data will land. Target connections contain information regarding data destination, data format, and the target connection ID required to create a dataflow. Target connection instances are specific to a tenant and organization.

To create a target connection, make a POST request to the /targetConnections endpoint of the Flow Service API. As part of the request, you must provide the data format, the dataSetId retrieved in the previous step, and the fixed connection specification ID tied to Data Lake. This ID is c604ff05-7f1a-43c0-8e18-33bf874cb11c.

API format

POST /targetConnections

Request

curl -X POST \
    'https://platform.adobe.io/data/foundation/flowservice/targetConnections' \
    -H 'Authorization: Bearer {ACCESS_TOKEN}' \
    -H 'x-api-key: {API_KEY}' \
    -H 'x-gw-ims-org-id: {ORG_ID}' \
    -H 'x-sandbox-name: {SANDBOX_NAME}' \
    -H 'Content-Type: application/json' \
    -d '{
        "name": "Streaming target connection",
        "description": "Streaming target connection",
        "connectionSpec": {
            "id": "c604ff05-7f1a-43c0-8e18-33bf874cb11c",
            "version": "1.0"
        },
        "data": {
            "format": "parquet_xdm",
            "schema": {
                "id": "https://ns.adobe.com/{TENANT_ID}/schemas/e45dd983026ce0daec5185cfddd48cbc0509015d880d6186",
                "version": "application/vnd.adobe.xed-full+json;version=1"
            }
        },
        "params": {
            "dataSetId": "5f7187bac6d00f194fb937c0"
        }
    }'

Response

A successful response returns the new target connection’s unique identifier (id). This ID is required in later steps.

{
    "id": "d9300194-6a82-4163-b001-946a821163b8",
    "etag": "\"4006d3e4-0000-0200-0000-5f7189220000\""
}

Create a mapping mapping

In order for the source data to be ingested into a target dataset, it must first be mapped to the target schema that the target dataset adheres to.

To create a mapping set, make a POST request to the mappingSets endpoint of the Data Prep API while providing your target XDM schema $id and the details of the mapping sets you want to create.

API format

POST /mappingSets

Request

curl -X POST \
    'https://platform.adobe.io/data/foundation/mappingSets' \
    -H 'Authorization: Bearer {ACCESS_TOKEN}' \
    -H 'x-api-key: {API_KEY}' \
    -H 'x-gw-ims-org-id: {ORG_ID}' \
    -H 'x-sandbox-name: {SANDBOX_NAME}' \
    -H 'Content-Type: application/json' \
    -d '{
        "version": 0,
        "xdmSchema": "_{TENANT_ID}.schemas.e45dd983026ce0daec5185cfddd48cbc0509015d880d6186",
        "xdmVersion": "1.0",
        "mappings": [
            {
                "destinationXdmPath": "person.name.firstName",
                "sourceAttribute": "firstName",
                "identity": false,
                "version": 0
            },
            {
                "destinationXdmPath": "person.name.lastName",
                "sourceAttribute": "lastName",
                "identity": false,
                "version": 0
            }
        ]
    }'

Response

A successful response returns details of the newly created mapping including its unique identifier (id). This ID is required in a later step to create a dataflow.

{
    "id": "380b032b445a46008e77585e046efe5e",
    "version": 0,
    "createdDate": 1604960750613,
    "modifiedDate": 1604960750613,
    "createdBy": "{CREATED_BY}",
    "modifiedBy": "{MODIFIED_BY}"
}

Retrieve a list of dataflow specifications specs

A dataflow is responsible for collecting data from sources and bringing them into Platform. In order to create a dataflow, you must first obtain the dataflow specifications by performing a GET request to the Flow Service API.

API format

GET /flowSpecs

Request

curl -X GET \
    'https://platform.adobe.io/data/foundation/flowservice/flowSpecs' \
    -H 'x-api-key: {API_KEY}' \
    -H 'x-gw-ims-org-id: {ORG_ID}' \
    -H 'x-sandbox-name: {SANDBOX_NAME}'

Response

A successful response returns a list of dataflow specifications. The dataflow specification ID that you need to retrieve to create a dataflow using any of Amazon Kinesis, Azure Event Hubs, or Google PubSub, is d69717ba-71b4-4313-b654-49f9cf126d7a.

{
    "items": [
        {
            "id": "d69717ba-71b4-4313-b654-49f9cf126d7a",
            "name": "Stream data with optional transformation",
            "providerId": "521eee4d-8cbe-4906-bb48-fb6bd4450033",
            "version": "1.0",
            "sourceConnectionSpecIds": [
                "bc7b00d6-623a-4dfc-9fdb-f1240aeadaeb",
                "bf9f5905-92b7-48bf-bf20-455bc6b60a4e",
                "86043421-563b-46ec-8e6c-e23184711bf6",
                "70116022-a743-464a-bbfe-e226a7f8210c"
            ],
            "targetConnectionSpecIds": [
                "bf9f5905-92b7-48bf-bf20-455bc6b60a4e",
                "c604ff05-7f1a-43c0-8e18-33bf874cb11c",
                "db4fe783-ef79-4a12-bda9-32b2b1bc3b2c"
            ],
            "transformationSpecs": [
                {
                    "name": "Mapping",
                    "spec": {
                        "$schema": "http://json-schema.org/draft-07/schema#",
                        "type": "object",
                        "description": "defines various params required for different mapping from source to target",
                        "properties": {
                            "mappingId": {
                                "type": "string"
                            }
                        }
                    }
                }
            ],
            "attributes": {
                "uiAttributes": {
                    "apiFeatures": {
                        "flowRunsSupported": false
                    }
                }
            },
            "permissionsInfo": {
                "view": [
                    {
                        "@type": "lowLevel",
                        "name": "StreamingSource",
                        "permissions": [
                            "read"
                        ]
                    }
                ],
                "manage": [
                    {
                        "@type": "lowLevel",
                        "name": "StreamingSource",
                        "permissions": [
                            "write"
                        ]
                    }
                ]
            }
        },
    ]
}

Create a dataflow

The last step towards collecting streaming data is to create a dataflow. By now, you have the following required values prepared:

A dataflow is responsible for scheduling and collecting data from a source. You can create a dataflow by performing a POST request while providing the previously mentioned values within the payload.

API format

POST /flows

Request

curl -X POST \
    'https://platform.adobe.io/data/foundation/flowservice/flows' \
    -H 'x-api-key: {API_KEY}' \
    -H 'x-gw-ims-org-id: {ORG_ID}' \
    -H 'x-sandbox-name: {SANDBOX_NAME}' \
    -H 'Content-Type: application/json' \
    -d '{
        "name": "Streaming dataflow",
        "description": "Streaming dataflow",
        "flowSpec": {
            "id": "d69717ba-71b4-4313-b654-49f9cf126d7a",
            "version": "1.0"
        },
        "sourceConnectionIds": [
            "e96d6135-4b50-446e-922c-6dd66672b6b2"
        ],
        "targetConnectionIds": [
            "723222e2-6ab9-4b0b-b222-e26ab9bb0bc2"
        ],
        "transformations": [
            {
                "name": "Mapping",
                "params": {
                    "mappingId": "380b032b445a46008e77585e046efe5e",
                    "mappingVersion": 0
                }
            }
        ]
    }'

Response

A successful response returns the ID (id) of the newly created dataflow.

{
    "id": "1f086c23-2ea8-4d06-886c-232ea8bd061d",
    "etag": "\"8e000533-0000-0200-0000-5f3c40fd0000\""
}

Post data for ingestion

View the sample payload below for examples of raw or XDM-compliant json that you can send for ingestion.

The following examples apply to all of:

'{
      "name": "Johnson Smith",
      "location": {
          "city": "Seattle",
          "country": "United State of America",
          "address": "3692 Main Street"
      },
      "gender": "Male",
      "birthday": {
          "year": 1984,
          "month": 6,
          "day": 9
      }
  }'

{
  "header": {
    "schemaRef": {
      "id": "https://ns.adobe.com/aepstreamingservicesint/schemas/73cae7e6db06ebca535cd973e3ece85e66253962f504e7d8",
      "contentType": "application/vnd.adobe.xed-full-notext+json; version=1.0"
    }
  },
  "body": {
    "xdmMeta": {
      "schemaRef": {
        "id": "https://ns.adobe.com/aepstreamingservicesint/schemas/73cae7e6db06ebca535cd973e3ece85e66253962f504e7d8",
        "contentType": "application/vnd.adobe.xed-full-notext+json; version=1.0"
      }
    },
    "xdmEntity": {
      "_id": "acme",
      "workEmail": {
        "address": "mike@acme.com",
        "primary": true,
        "type": "work",
        "status": "active"
      },
      "person": {
        "gender": "male",
        "name": {
          "firstName": "Mike",
          "lastName": "Wazowski"
        },
        "birthDate": "1985-01-01"
      },
      "identityMap": {
        "ecid": [
          {
            "id": "01262118050522051420082102000000000000"
          }
        ]
      }
    }
  }
}

Next steps

By following this tutorial, you have created a dataflow to collect streaming data from your streaming connector. Incoming data can now be used by downstream Platform services such as Real-Time Customer Profile and Data Science Workspace. See the following documents for more details: