Batch ingestion overview

The Adobe Experience Platform Data Ingestion API allows you to ingest data into Platform as batch files. Data being ingested can be the profile data from a flat file in a CRM system (such as a Parquet file), or data that conforms to a known schema in the Experience Data Model (XDM) registry.

The Data Ingestion API reference provides additional information on these API calls.

The following diagram outlines the batch ingestion process:

Using the API

The Data Ingestion API allows you to ingest data as batches (a unit of data that consists of one or more files to be ingested as a single unit) into Experience Platform in three basic steps:

1. Create a new batch.
2. Upload files to a specified dataset that matches the XDM schema of the data.
3. Signal the end of the batch.

Data Ingestion prerequisites

• Data to upload must be either in Parquet or JSON formats.
• A dataset created in the Catalog services.
• Contents of the Parquet file must match a subset of the schema of the dataset being uploaded into.
• Have your unique Access Token after authentication.

Batch ingestion best practices

• The recommended batch size is between 256 MB and 100 GB.
• Each batch should contain at most 1500 files.

To upload a file larger than 512MB, the file will need to be divided into smaller chunks. Instructions to upload a large file can be found here.

Reading sample API calls

This guide provides example API calls to demonstrate how to format your requests. These include paths, required headers, and properly formatted request payloads. Sample JSON returned in API responses is also provided. For information on the conventions used in documentation for sample API calls, see the section on how to read example API calls in the Experience Platform troubleshooting guide.

Gather values for required headers

In order to make calls to Platform APIs, you must first complete the authentication tutorial. Completing the authentication tutorial provides the values for each of the required headers in all Experience Platform API calls, as shown below:

• Authorization: Bearer {ACCESS_TOKEN}
• x-api-key: {API_KEY}
• x-gw-ims-org-id: {IMS_ORG}

All resources in Experience Platform are isolated to specific virtual sandboxes. All requests to Platform APIs require a header that specifies the name of the sandbox the operation will take place in:

• x-sandbox-name: {SANDBOX_NAME}

All requests that contain a payload (POST, PUT, PATCH) require an additional header:

• Content-Type: application/json

Create a batch

Before data can be added to a dataset, it must be linked to a batch, which will later be uploaded into a specified dataset.

POST /batches

Request

curl -X POST "https://platform.adobe.io/data/foundation/import/batches" \
  -H "Content-Type: application/json" \
  -H "x-gw-ims-org-id: {IMS_ORG}" \
  -H "x-sandbox-name: {SANDBOX_NAME}" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "x-api-key : {API_KEY}"
  -d '{ 
          "datasetId": "{DATASET_ID}" 
      }'

Reponse

{
    "id": "{BATCH_ID}",
    "imsOrg": "{IMS_ORG}",
    "updated": 0,
    "status": "loading",
    "created": 0,
    "relatedObjects": [
        {
            "type": "dataSet",
            "id": "{DATASET_ID}"
        }
    ],
    "version": "1.0.0",
    "tags": {},
    "createdUser": "{USER_ID}",
    "updatedUser": "{USER_ID}"
}

File upload

After successfully creating a new batch for uploading, files can then be uploaded to a specific dataset.

You can upload files using the Small File Upload API. However, if your files are too large and the gateway limit is exceeded (such as extended timeouts, requests for body size exceeded, and other constrictions), you can switch over to the Large File Upload API. This API uploads the file in chunks, and stitches data together using the Large File Upload Complete API call.

Small file upload

Once a batch is created, data can be uploaded to a preexisting dataset. The file being uploaded must match its referenced XDM schema.

PUT /batches/{BATCH_ID}/datasets/{DATASET_ID}/files/{FILE_NAME}

Request

curl -X PUT "https://platform.adobe.io/data/foundation/import/batches/{BATCH_ID}/datasets/{DATASET_ID}/files/{FILE_NAME}.parquet" \
  -H "content-type: application/octet-stream" \
  -H "x-gw-ims-org-id: {IMS_ORG}" \
  -H "x-sandbox-name: {SANDBOX_NAME}" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "x-api-key : {API_KEY}" \
  --data-binary "@{FILE_PATH_AND_NAME}.parquet"

Reponse

#Status 200 OK, with empty response body

Large file upload - create file

To upload a large file, the file must be split into smaller chunks and uploaded one at a time.

POST /batches/{BATCH_ID}/datasets/{DATASET_ID}/files/{FILE_NAME}?action=initialize

Request

curl -X POST "https://platform.adobe.io/data/foundation/import/batches/{BATCH_ID}/datasets/{DATASET_ID}/files/part1=a/part2=b/{FILE_NAME}.parquet?action=initialize" \
  -H "x-gw-ims-org-id: {IMS_ORG}" \
  -H "x-sandbox-name: {SANDBOX_NAME}" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "x-api-key: {API_KEY}"

Reponse

#Status 201 CREATED, with empty response body

Large file upload - upload subsequent parts

After the file has been created, all subsequent chunks can be uploaded by making repeated PATCH requests, one for each section of the file.

PATCH /batches/{BATCH_ID}/datasets/{DATASET_ID}/files/{FILE_NAME}

Request

curl -X PATCH "https://platform.adobe.io/data/foundation/import/batches/{BATCH_ID}/datasets/{DATASET_ID}/files/part1=a/part2=b/{FILE_NAME}.parquet" \
  -H "content-type: application/octet-stream" \
  -H "x-gw-ims-org-id: {IMS_ORG}" \
  -H "x-sandbox-name: {SANDBOX_NAME}" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "x-api-key: {API_KEY}" \
  -H "Content-Range: bytes {CONTENT_RANGE}" \
  --data-binary "@{FILE_PATH_AND_NAME}.parquet"

Reponse

#Status 200 OK, with empty response

Signal batch completion

After all files have been uploaded to the batch, the batch can be signaled for completion. By doing this, the Catalog DataSetFile entries are created for the completed files and associated with the batch generated above. The Catalog batch is then marked as successful, which triggers downstream flows to ingest the available data.

Request

POST /batches/{BATCH_ID}?action=COMPLETE

curl -X POST "https://platform.adobe.io/data/foundation/import/batches/{BATCH_ID}?action=COMPLETE" \
-H "x-gw-ims-org-id: {IMS_ORG}" \
-H "x-sandbox-name: {SANDBOX_NAME}" \
-H "Authorization: Bearer {ACCESS_TOKEN}" \
-H "x-api-key : {API_KEY}"

Reponse

#Status 200 OK, with empty response

Check batch status

While waiting for the files to uploaded to the batch, the batch’s status can be checked to see its progress.

API format

GET /batch/{BATCH_ID}

Request

curl GET "https://platform.adobe.io/data/foundation/catalog/batch/{BATCH_ID}" \
  -H "Authorization: Bearer {ACCESS_TOKEN}" \
  -H "x-gw-ims-org-id: {IMS_ORG}" \
  -H "x-sandbox-name: {SANDBOX_NAME}" \
  -H "x-api-key: {API_KEY}"

Reponse

{
    "{BATCH_ID}": {
        "imsOrg": "{IMS_ORG}",
        "created": 1494349962314,
        "createdClient": "MCDPCatalogService",
        "createdUser": "{USER_ID}",
        "updatedUser": "{USER_ID}",
        "updated": 1494349963467,
        "externalId": "{EXTERNAL_ID}",
        "status": "success",
        "errors": [
            {
                "code": "err-1494349963436"
            }
        ],
        "version": "1.0.3",
        "availableDates": {
            "startDate": 1337,
            "endDate": 4000
        },
        "relatedObjects": [
            {
                "type": "batch",
                "id": "foo_batch"
            },
            {
                "type": "connection",
                "id": "foo_connection"
            },
            {
                "type": "connector",
                "id": "foo_connector"
            },
            {
                "type": "dataSet",
                "id": "foo_dataSet"
            },
            {
                "type": "dataSetView",
                "id": "foo_dataSetView"
            },
            {
                "type": "dataSetFile",
                "id": "foo_dataSetFile"
            },
            {
                "type": "expressionBlock",
                "id": "foo_expressionBlock"
            },
            {
                "type": "service",
                "id": "foo_service"
            },
            {
                "type": "serviceDefinition",
                "id": "foo_serviceDefinition"
            }
        ],
        "metrics": {
            "foo": 1337
        },
        "tags": {
            "foo_bar": [
                "stuff"
            ],
            "bar_foo": [
                "woo",
                "baz"
            ],
            "foo/bar/foo-bar": [
                "weehaw",
                "wee:haw"
            ]
        },
        "inputFormat": {
            "format": "parquet",
            "delimiter": ".",
            "quote": "`",
            "escape": "\\",
            "nullMarker": "",
            "header": "true",
            "charset": "UTF-8"
        }
    }
}

The "status" field is what shows the current status of the batch requested. The batches can have one of the following states:

Batch ingestion statuses