PUT
/
tables
/
{tableID}

Overwrite an existing Big Table by clearing all rows and adding new data. You can also update the table schema.

When using a CSV or TSV request body, you cannot pass a schema. The current schema will be used. If you need to update the schema, use the onSchemaError=updateSchema query parameter, or stash the CSV/TSV data and pass a JSON request body.

This is a destructive operation that cannot be undone.

Examples

Authorizations

Authorization
string
headerrequired

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

tableID
string
required

ID of the table, e.g., 2a1bad8b-cf7c-44437-b8c1-e3782df6

Query Parameters

onSchemaError
enum<string>

The action to take when the passed data does not match the table schema:

  • abort: Abort the entire operation and return an error.
  • dropColumns: Ignore the data that caused the error, and do not import those columns in the affected rows.
  • updateSchema: Update the schema as needed to add any missing columns or widen the data types of existing columns, and then import the data from them.
Available options:
abort,
dropColumns,
updateSchema

Body

rows
required

A collection of row objects conforming to the schema of the table where keys are the column IDs and values are the column values:

[
	{
		"fullName": "Alex Bard",
		"invoiceDate": "2024-07-29T14:04:15.561Z",
		"totalAmount": 34.50,
		"amountPaid": 0
	},
	{
		"fullName": "Alicia Hines",
		"invoiceDate": "2023-06-15T10:30:00.000Z",
		"totalAmount": 50.75,
		"amountPaid": 20
	}
]
schema
object

The schema of the table as a collection of column definitions.

Response

200 - application/json
data
object
required