Overwrite Table
Replaces the schema and/or data of a Big Table
Overwrite an existing Big Table by clearing all rows and adding new data.
Updating the Schema
You can optionally update the table schema at the same time by providing a new schema in the JSON request body. If you do not provide a schema, the existing schema will be used.
When using a CSV or TSV request body, you cannot pass a schema. 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 referencing the stash ID.
Examples
Authorizations
Bearer authentication header of the form Bearer <token>
, where <token>
is your auth token.
Headers
ETag of the current table version. If provided, the request will fail if the table has been updated since this version.
Path Parameters
ID of the table, e.g., 2a1bad8b-cf7c-44437-b8c1-e3782df6
Query Parameters
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.
abort
, dropColumns
, updateSchema
Body
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
}
]
The schema of the table as a collection of column definitions.
Response
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