Query a linked dataset in BigQuery

This document describes how to create a linked dataset for a log bucket, and how to query and view logs in that dataset. For example, you might create a linked dataset so that you can run queries on Log Analytics by using your reserved BigQuery slots. Similarly, you might want a linked dataset so that you can write queries in BigQuery or in Looker Studio that join your log data with other business datata.

If you aren't familiar with Log Analytics, then see Log Analytics overview.

When you need a linked dataset

You don't need a linked BigQuery dataset to issue queries to a log view on the Log Analytics page. You can save and share these queries, and you can save the results to a custom dashboard.

You do need a linked BigQuery dataset when you want to do any of the following:

• Join log entry data with other BigQuery datasets.
• Query log data from another service like the BigQuery Studio page or Looker Studio.
• Improve the performance of the queries that you run from the Log Analytics by running them on your BigQuery reserved slots

A linked BigQuery dataset for a log bucket lets BigQuery read access to the underlying data.

If you run your queries on reserved BigQuery slots, then your queries are subject to capacity compute pricing. Also, if you query your data by using a service other than Log Analytics, then your queries might be subject to other charges based on that service. See the pricing page for the service that you are using.

Before you begin

Before you use Log Analytics, do the following:

• To get the permissions that you need to use Log Analytics, ask your administrator to grant you the following IAM roles on your project:

  • To query the _Required and _Default log buckets: Logs Viewer (roles/logging.viewer)
  • To query all log views in a project: Logs View Accessor (roles/logging.viewAccessor)

  You can restrict a principal to a specific log view either by adding an IAM condition to the Logs View Accessor role grant made at the project level, or by adding an IAM binding to the policy file of the log view. For more information, see Control access to a log view.

  These are the same permissions that you need to view log entries on the Logs Explorer page. For information about additional roles that you need to query views on user-defined buckets or to query the _AllLogs view of the _Default log bucket, see Cloud Logging roles.

• To get the permissions that you need to create and query linked datasets, ask your administrator to grant you the following IAM roles on the project that stores the log bucket:

  • To create and view linked datasets: Logs Configuration Writer (roles/logging.configWriter)
  • To run queries on linked datasets using reserved BigQuery slots:
    • BigQuery User (roles/bigquery.user)
    • BigQuery Job User (roles/bigquery.jobUser)
  • To view linked datasets in BigQuery Studio, grant all roles mentioned in this step, and the following role. You can grant this role to a dataset or to your project: BigQuery Data Viewer (roles/bigquery.dataViewer)

• Ensure that your log buckets have been upgraded to use Log Analytics:

  1. In the Google Cloud console, go to the Logs Storage page:

     Go to Logs Storage

     If you use the search bar to find this page, then select the result whose subheading is Logging.

  2. For each log bucket that has a log view that you want to query, ensure that the Log Analytics available column displays Open. If Upgrade is shown, then click Upgrade and complete the dialog.
• If you want to query your log data from the Log Analytics page by using reserved BigQuery slots and if you are using projects with Virtual Private Cloud (VPC) Service Controls, then ensure you are using the Enterprise Edition of BigQuery. For more information, see Understand BigQuery editions.

Create a linked BigQuery dataset

When you want to use the capabilities of BigQuery to analyze your log data, upgrade a log bucket to use Log Analytics, and then create a linked dataset. With this configuration, Logging stores your log data but BigQuery can read the log data.

gcloud logging links create LINK_ID --bucket=BUCKET_ID --location=LOCATION

gcloud logging links create mylink --bucket=my-bucket --location=global

Run queries from BigQuery

When you have a log bucket that uses Log Analytics and linked datasets, you can view and query your linked datasets by using the BigQuery Studio page. With this configuration, you can analyze your datasets using commands, workflows, and datasets available only in BigQuery Studio.

To open BigQuery from the Log Analytics and then query linked dataset, do the following:

1. Ensure that a linked dataset exists for the log bucket which hosts the log view that you want to query:

   1. In the Google Cloud console, go to the Logs Storage page:

      Go to Logs Storage

      If you use the search bar to find this page, then select the result whose subheading is Logging.

   2. Locate the log bucket and verify that the BigQuery linked dataset column displays a URL. If the entry is empty, then you must create a linked dataset. For information on these steps, see Create a linked BigQuery dataset

2. In the Google Cloud console, go to the Log Analytics page:

   Go to Log Analytics

   If you use the search bar to find this page, then select the result whose subheading is Logging.

3. In the Log views list, find the log view, and then select Query. The Query pane is populated with a default query. You can also enter a query in the Query pane, or edit a displayed query.

4. In the toolbar, expand the button labeled Run query or Run on BigQuery, and select Open in BigQuery.

   The BigQuery Studio page opens. The FROM statement of the query is modified to specify the path to the log view on the linked dataset by using the BigQuery Table path syntax.

   You can also edit the displayed query.

5. On the BigQuery Studio page, click Run query.

Run Log Analytics queries on your reserved BigQuery slots

When you want to minimize the execution time of your Log Analytics, run them on your reserved BigQuery slots. The Log Analytics page is preconfigured to use the default Log Analytics service, which means that your queries must compete for limited slot space with other queries. When there aren't available slots, your the execution of your query is delayed. You can eliminate these delays by running your queries on reserved BigQuery slots.

To issue a SQL query to a log view, do the following:

1. Ensure that a linked dataset exists for the log bucket which hosts the log view that you want to query:

   1. In the Google Cloud console, go to the Logs Storage page:

      Go to Logs Storage

      If you use the search bar to find this page, then select the result whose subheading is Logging.

   2. Locate the log bucket and verify that the BigQuery linked dataset column displays a URL. If the entry is empty, then you must create a linked dataset. For information on these steps, see Create a linked BigQuery dataset

2. Ensure that you have configured your reserved BigQuery slots:

   1. Create a reservation with dedicated slots
   2. Create reservation assignments

3. Configure Log Analytics to run your queries on your reserved BigQuery slots:

   1. In the Google Cloud console, go to the Log Analytics page:

      Go to Log Analytics

      If you use the search bar to find this page, then select the result whose subheading is Logging.

   2. In the Log views list, find the view, and then select Query or enter a query.

      If the query pane displays an error message that references the FROM statement, then the table can't be resolved to a specific log view. For information about how to resolve this failure, see Error FROM clause must contain exactly one log view.

   3. Go to the toolbar and ensure that a button labeled Run on BigQuery is displayed.

      If the toolbar displays Run Query, then click settings Settings and select BigQuery.

      If the Run on BigQuery button is disabled, then you need to create a linked dataset.

   4. Run your query.

      You can use the toolbar options to format your query, clear the query, and open the BigQuery SQL reference documentation.

What's next

• Save and share a SQL query
• Sample SQL queries
• Chart SQL query results