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  • Getting Started
    • What is Count?
    • Count FAQ
    • Intro to your workspace
    • Example canvases
    • Getting started guides
      • Set up your workspace and projects
        • 1. Review workspace settings
        • 2. Create and organise your projects
      • Canvas orientation
      • Your first ad hoc analysis
        • 1. Examples and templates
        • 2. Build your first queries
        • 3. Create visuals
        • 4. Caching, local cells and scheduling
        • 5. Collaborating with a stakeholder
      • Your first report
        • 1. Examples and templates
        • 2. Filters and control cells
        • 3. Sharing your report
        • 4. Alerts
  • Connect your data
    • Database connection overview
      • Athena
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      • BigQuery
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  • THE CANVAS
    • Navigating the canvas
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    • Cells overview
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    • Troubleshooting
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    • Every Visual Under the Sun
  • Presenting and Reporting
    • Reports and Slides
  • Count Metrics
    • Intro to Count Metrics
    • Build and edit a catalog
    • Views
      • Creating views
      • Customizing views
    • Datasets
      • Creating datasets
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    • Caching in Count Metrics
    • Using the catalog
      • Explore from cell
  • Sharing and Permissions
    • Real-time collaboration
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Powered by GitBook
On this page
  • Enter your connection details
  • Dataset access
  • BigQuery Storage API
  • Processed data estimations
  • Troubleshooting
  1. Connect your data
  2. Database connection overview

BigQuery

How to connect BigQuery to Count.

Enter your connection details

You'll need:

  • The Project ID of the BigQuery instance

  • A service account key in JSON format for a service account with the following permissions

bigquery.datasets.get
bigquery.jobs.create
bigquery.routines.get
bigquery.routines.list
bigquery.tables.get
bigquery.tables.getData
bigquery.tables.list

The quickest way to grant these permissions is to assign the service account the roles BigQuery Data Viewer and BigQuery Job User.

Dataset access

By default, you are able to query any dataset in the BigQuery project (limited by the supplied credentials). You are also able to query datasets in other BigQuery projects (as long as the credentials have access to those projects), but datasets in other BigQuery projects will not appear in the Count UI.

If table access is restricted within a Count project, then canvases in that project will be unable to query tables outside of this BigQuery project.

BigQuery Storage API

bigquery.readsessions.create
bigquery.readsessions.getData

Use of the BigQuery Storage API may result in a small increase in your BigQuery costs.

If your workspace has been granted an increase in the default query response size limit, you'll need to enable the BigQuery Storage API for this increase to take effect.

Processed data estimations

Troubleshooting

The most common issue when connecting to BigQuery data is getting the service account permissions correct. Double-check the service account permissions with the list above.

Out of Memory Errors:

If you are connecting to a BigQuery project with many tables, you may see an out-of-memory error when you try to connect. To resolve this, you can limit the datasets you want to connect to using the following steps:

  1. Create a new service account with the BigQuery Job User permission

3. Add the service account email to the dataset with the BigQuery Data Viewer permission:

4. Repeat this for any other datasets you want this service account to have access to.

5. Add the service account key to Count and you'll only access the tables for the datasets you've specifically chosen.

PreviousAzure SynapseNextDatabricks

Last updated 2 months ago

When running queries with the default , it may take a long time to extract large result sets from BigQuery. In this case you may want to enable the BigQuery Storage API, which uses an alternative method to extract results more quickly for these queries. To use this API, you'll need to grant your service account the additional permissions:

If automatic execution for a BigQuery cell has been , then an estimate of the data that will be processed by the query is shown in the cell body:

Additionally, if your BigQuery datasets contain tables that reference , please check that the service account has viewer access to the files/buckets/drives where the datasources reside.

2. In the BigQuery console, go the dataset you want to assign permission to, and click Share Dataset (instructions ).

If you are having trouble connecting, to us to schedule a support session

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