> For the complete documentation index, see [llms.txt](https://docs.jentis.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.jentis.com/data-activation/connectors/google-big-query.md).

# Google Big Query

Related to SD-5810

To enable an external application to submit data to your BigQuery dataset using the `tabledata.insertAll` method, you need to follow these steps for authentication, authorization, and API implementation.

{% hint style="info" %}
Please note: While the `tabledata.insertAll` method is marked as deprecated it still is the only option to submit data via HTTP POST requests as a RESTFUL API. Other options are recommended by Google BigQuery but require a different streaming approach and framework.
{% endhint %}

#### 1. Set Up Authentication

Since your application is external to Google Cloud, you should use a **Service Account** to authenticate.

1. **Create a Service Account:** Go to the IAM & Admin console in Google Cloud and create a service account specifically for this application.
2. **Generate a Key:** Create and download a JSON key file for this service account. Your external application will use this file to authenticate.
3. **Environment Variable:** Set the environment variable `GOOGLE_APPLICATION_CREDENTIALS` to the path of your JSON key file on the server where your application runs.

#### 2. Grant Permissions (IAM Roles)

The service account needs specific permissions to write data to your dataset. You should grant one of the following roles to the service account at the **dataset** or **project** level:

* **`roles/bigquery.dataEditor`**: Allows streaming inserts and modifying data.
* **`roles/bigquery.dataOwner`**: Full control over the dataset.

Specifically, the `tabledata.insertAll` method requires:

* `bigquery.tables.updateData`
* `bigquery.tables.get`
* `bigquery.datasets.get`

#### 3. API Implementation (JSON Payload)

The `tabledata.insertAll` method (Legacy Streaming API) expects a POST request to the following endpoint:\
`POST https://bigquery.googleapis.com/bigquery/v2/projects/{projectId}/datasets/MSDAC_JENTIS_CONNECTOR/tables/{tableId}/insertAll`

**Example JSON Payload:**\
The rows must be wrapped in a `json` object within a `rows` array.

```
{
  "kind": "bigquery#tableDataInsertAllRequest",
  "rows": [
    {
      "insertId": "unique_id_1", 
      "json": {
        "column_name_1": "value1",
        "column_name_2": 123
      }
    }
  ]
}

```

* **`insertId`**: (Optional but recommended) Used for best-effort deduplication if the same request is sent twice.

#### 4. Implementation Example (Python)

If you are using the BigQuery Client Library, the implementation is simplified:

```
from google.cloud import bigquery

client = bigquery.Client()
table_id = "msdac-generic-projects.MSDAC_JENTIS_CONNECTOR.your_table"

rows_to_insert = [
    {"column_name_1": "value1", "column_name_2": 123},
]

errors = client.insert_rows_json(table_id, rows_to_insert)

if errors == []:
    print("New rows have been added.")
else:
    print(f"Encountered errors: {errors}")

```

#### Recommendation

For new integrations, Google recommends using the **BigQuery Storage Write API** instead of `tabledata.insertAll`. It offers lower costs, better performance, and stronger reliability (exactly-once delivery). However, `tabledata.insertAll` remains fully supported.


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