BigQuery: Set up limits and custom quotas through API

guillaume blaquiere
Jan 6 · 4 min read

BigQuery is the petabytes scale data warehouse on Google Cloud Platform. You can load a lot of data freely and easily, the storage cost is very affordable with an automatic switch to cold storage after 90 days.

When you use the on-demand pricing, the cost is based on the volume of data that the query scans (about $5 per TB for the cheaper location) in your queries. And when you have terabytes or petabytes, it can become expensive!

Cost optimizations

For optimizing the data organisation and reduce the volume of data that you scan, you can clusterize and/or partition your data on any fields. You can also require the partition filter in the where clause of the queries. The objective is to force the requester to ask himself about the data scanned for optimizing the queries.

However, nothing forces the requester to use the partitioned field smartly or to prevent a badly use of it. Thereby, requiring the partition field in each request can be useless and the whole data can still be scanned.

Custom quotas on volume of data scanned

To prevent the scanning of large volumes of data due to the lacks of partitioning or bad usages of partitions, Google allows to set custom quotas on volume of data scanned per user or per project. The quotas are reset to 0 every days at midnight, pacific time.

It’s easy to set a quota

  • Go to quotas page
  • Select only BigQuery service
  • Look for Query usage per day per user or Query usage per day and select it
  • Click on Edit Quotas
  • Set the limit on the right side, validate and Submit
Set a custom quota with console

Perfect per console, but how to do it at scale?

Automate the quota limits

My company is global (50+ countries), thousands of GCP projects (3k+) and BigQuery tables (100k+), hundreds of subsidiaries, and lot of different internal and external IT teams and data scientists. With my colleagues at headquarters, we do a lot for training, helping and assisting users for preventing mistakes and unexpected cost. But it’s not enough.

BigQuery cost in 2019

Thereby, we decided to set a limit on all DEV and TEST projects, for production, it’s only when requested by the teams in charge of the project. For this, we wanted to use the service management API and we tried all the documented endpoints… It’s impossible to update quotas via API!!

How to update thousands of project? and how to apply this automatically on new ones?

Undocumented API usage

Stuck in a dead end, I tried to understand how the API worked in the console thanks to the developer mode of Chrome and I found a workaround.

The API principle

To invoke this API, use this URL.

The API is secured, you have to present an HTTP Bearer access token with your request. The call uses the HTTP verb PATCH and you have to present application/json content-type body.

The limit is in MB. Here the body sets the limit to 150Tb per day on the project.


Put it all together

For experimenting this API, make a call with curl. Create a file with data as name and the previous body as content. Then, run this command (for example on Cloud Shell).

curl -d @data \
-H "content-type: application/json" \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \

The answer is the ID of the operation

"name": "operations/tmo-quf.9d6e6e04-28fd-4147-8fee-dea59764b5d0"

Check the console

Great, that works!

Use with caution

Now, you can script this quotas API and include this in all your automated project creations, and performing an update of your existing projects.

However, keep in mind that is an hack and the viability of this solution is not guaranteed.

Google Cloud - Community

A collection of technical articles published or curated by Google Cloud Developer Advocates. The views expressed are those of the authors and don't necessarily reflect those of Google.

guillaume blaquiere

Written by

GDE Google Cloud Platform, scrum master, speaker, writer and polyglot developer, Google Cloud platform 3x certified, serverless addict and Go fan.

Google Cloud - Community

A collection of technical articles published or curated by Google Cloud Developer Advocates. The views expressed are those of the authors and don't necessarily reflect those of Google.

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