Exporting a schema in BigQuery outputs the table or dataset structure to a JSON file for version control, migration, or documentation.
Exporting lets you track schema changes, replicate tables across projects, and document data contracts. It’s faster than recreating tables manually.
The bq CLI, Cloud Console, and INFORMATION_SCHEMA views all support schema export. The CLI is script-friendly and preferred for CI/CD pipelines.
Run bq show --schema --format=prettyjson project:dataset.table > file.json
. The command writes a JSON array of field definitions.
bq show --schema --format=prettyjson galaxy:ecommerce.Customers > customers_schema.json
Loop through table names returned by bq ls
or INFORMATION_SCHEMA and call bq show --schema
for each. Store each JSON in version control.
Yes. Query INFORMATION_SCHEMA.COLUMNS
and save the results. The output isn’t identical to the CLI JSON but contains column names, types, and positions.
Keep exports in the same repo as code, automate nightly runs, and diff schemas in pull requests to spot breaking changes early.
Use bq mk --table --schema=path/to/schema.json project:dataset.table
. The JSON must match BigQuery’s field format.
No native flag exists. You must iterate over tables and concatenate individual JSON files or aggregate INFORMATION_SCHEMA results.
No. The command is metadata-only and has no impact on performance or locks.
Yes. The CLI JSON includes timePartitioning
and clustering
objects when they exist.