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Connect Google BigQuery to Experience Platform using the Flow Service API

Read this guide to learn how to connect your Google BigQuery database to ÃÛ¶¹ÊÓƵ Experience Platform using the .

Get started

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

Using Experience Platform APIs

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

Gather required credentials

Read the Google BigQuery authentication guide for detailed steps on retrieving your Google BigQuery credentials.

Connect Google BigQuery to Experience Platform on Azure azure

Read the steps below for information on how to connect your Google BigQuery source to Experience Platform on Azure.

Create a base connection for Google BigQuery on Experience Platform on Azure azure-base

A base connection retains information between your source and Experience Platform, including your source’s authentication credentials, the current state of the connection, and your unique base connection ID. The base connection ID allows you to explore and navigate files from within your source and identify the specific items that you want to ingest, including information regarding their data types and formats.

To create a base connection ID, make a POST request to the /connections endpoint while providing your Google BigQuery authentication credentials as part of the request parameters.

API format

POST /connections

curl -X POST \
    'https://platform.adobe.io/data/foundation/flowservice/connections' \
    -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": "Google BigQuery connection with basic authentication",
        "description": "Google BigQuery connection with basic authentication",
        "auth": {
            "specName": "Basic Authentication",
            "type": "OAuth2.0",
            "params": {
                    "project": "{PROJECT}",
                    "clientId": "{CLIENT_ID},
                    "clientSecret": "{CLIENT_SECRET}",
                    "refreshToken": "{REFRESH_TOKEN}"
                }
        },
        "connectionSpec": {
            "id": "3c9b37f8-13a6-43d8-bad3-b863b941fedd",
            "version": "1.0"
        }
    }'

{
    "id": "6990abad-977d-41b9-a85d-17ea8cf1c0e4",
    "etag": "\"ca00acbf-0000-0200-0000-60149e1e0000\""
}

curl -X POST \
  'https://platform.adobe.io/data/foundation/flowservice/connections' \
  -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": "Google BigQuery base connection with service account",
      "description": "Google BigQuery connection with service account",
      "auth": {
          "specName": "Service Authentication",
          "params": {
                  "projectId": "{PROJECT_ID}",
                  "keyFileContent": "{KEY_FILE_CONTENT},
                  "largeResultsDataSetId": "{LARGE_RESULTS_DATASET_ID}"
              }
      },
      "connectionSpec": {
          "id": "3c9b37f8-13a6-43d8-bad3-b863b941fedd",
          "version": "1.0"
      }
  }'

{
    "id": "6990abad-977d-41b9-a85d-17ea8cf1c0e4",
    "etag": "\"ca00acbf-0000-0200-0000-60149e1e0000\""
}

Connect Google BigQuery to Experience Platform on Amazon Web Services (AWS) aws

Read the steps below for information on how to connect your Google BigQuery database to Experience Platform on AWS.

Create a base connection for Google BigQuery on Experience Platform on AWS

API format

POST /connections

Request

The following request creates a base connection to connect Google BigQuery to Experience Platform on AWS.

curl -X POST \
  'https://platform.adobe.io/data/foundation/flowservice/connections' \
  -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": "Google BigQuery base connection on AWS",
      "description": "Google BigQuery base connection on AWS",
      "auth": {
          "specName": "Service Authentication",
          "params": {
                  "projectId": "{PROJECT_ID}",
                  "keyFileContent": "{KEY_FILE_CONTENT},
                  "datasetId": "{DATASET_ID}"
      },
      "connectionSpec": {
          "id": "3c9b37f8-13a6-43d8-bad3-b863b941fedd",
          "version": "1.0"
      }
  }'

Response

A successful response returns details of the newly created connection, including its unique identifier (id). This ID is required to explore your storage in the next tutorial.

{
    "id": "6990abad-977d-41b9-a85d-17ea8cf1c0e4",
    "etag": "\"ca00acbf-0000-0200-0000-60149e1e0000\""
}

Next steps

By following this tutorial, you have created a Google BigQuery base connection using the Flow Service API. You can use this base connection ID in the following tutorials: