INFORMATION_SCHEMA.RECOMMENDATIONS view
To request feedback or support for this feature, send email to bq-recommendations+feedback@google.com.
The INFORMATION_SCHEMA.RECOMMENDATIONS
view contains data about all BigQuery
recommendations in the current project. BigQuery retrieves
recommendations for all BigQuery recommenders from the Recommendation Hub
and present it in this view.
The INFORMATION_SCHEMA.RECOMMENDATIONS
view supports the following
recommendations:
- Partition & cluster recommendations
- Materialized view recommendations
- Role recommendations for BigQuery datasets
The INFORMATION_SCHEMA.RECOMMENDATIONS
view shows only BigQuery-related recommendations.
You can view Google Cloud recommendations in the Recommendation Hub.
Required permission
To view recommendations with the INFORMATION_SCHEMA.RECOMMENDATIONS
view, you
must have the required permissions for the corresponding recommender. The
INFORMATION_SCHEMA.RECOMMENDATIONS
view only returns recommendations that you
have permission to view.
Ask your administrator to grant access to view the recommendations. To see the required permissions for each recommender, see the following:
- Partition & cluster recommender permissions
- Materialized view recommendations permissions
- Role recommendations for datasets permissions
Schema
The INFORMATION_SCHEMA.RECOMMENDATIONS
view has the following schema:
Column name | Data type | Value |
---|---|---|
recommendation_id |
STRING |
Base64 encoded ID that contains the RecommendationID and recommender. |
recommender |
STRING |
The type of recommendation. For example, google.bigquery.table.PartitionClusterRecommender for partitioning and clustering recommendations. |
subtype |
STRING |
The subtype of the recommendation. |
project_id |
STRING |
The ID of the project. |
project_number |
STRING |
The number of the project. |
description |
STRING |
The description about the recommendation. |
last_updated_time |
TIMESTAMP |
This field represents the time when the recommendation was last created. |
target_resources |
STRING |
Fully qualified resource names this recommendation is targeting. |
state |
STRING |
The state of the recommendation. For a list of possible values, see State. |
primary_impact |
RECORD |
The impact this recommendation can have when trying to optimize the primary category. Contains the following fields:
|
priority |
STRING |
The priority of the recommendation. For a list of possible values, see Priority. |
associated_insight_ids |
STRING |
Full Insight names associated with the recommendation.Insight name is the Base64 encoded representation of Insight type name & the Insight ID. This can be used to query Insights view. |
additional_details |
RECORD |
Additional Details about the recommendation.
|
Scope and syntax
Queries against this view must include a region qualifier. A project ID is optional. If no project ID is specified, the project that the query runs in is used.
View name | Resource scope | Region scope |
---|---|---|
[PROJECT_ID.]`region-REGION`.INFORMATION_SCHEMA.RECOMMENDATIONS[_BY_PROJECT] |
Project level | REGION |
Optional: PROJECT_ID
: the ID of your
Google Cloud project. If not specified, the default project is used.
REGION
: any dataset region name.
For example, `region-us`
.
Example
To run the query against a project other than your default project, add the project ID in the following format:
`PROJECT_ID`.`region-REGION_NAME`.INFORMATION_SCHEMA.RECOMMENDATIONS
PROJECT_ID
: the ID of the project.REGION_NAME
: the region for your project.
For example, `myproject`.`region-us`.INFORMATION_SCHEMA.RECOMMENDATIONS
.
View top cost saving recommendations
The following example returns top 3 COST
category recommendations on the basis
of the projected slot_hours_saved_monthly
:
SELECT
recommender,
target_resources,
LAX_INT64(additional_details.overview.bytesSavedMonthly) / POW(1024, 3) as est_gb_saved_monthly,
LAX_INT64(additional_details.overview.slotMsSavedMonthly) / (1000 * 3600) as slot_hours_saved_monthly,
last_updated_time
FROM
`region-us`.
INFORMATION_SCHEMA.RECOMMENDATIONS_BY_PROJECT
WHERE
primary_impact.category = 'COST'
AND
state = 'ACTIVE'
ORDER by
slot_hours_saved_monthly DESC
LIMIT 3;
The result is similar to the following:
+---------------------------------------------------+--------------------------------------------------------------------------------------------------+ | recommender | target_resources | est_gb_saved_monthly | slot_hours_saved_monthly | last_updated_time +---------------------------------------------------+--------------------------------------------------------------------------------------------------+ | google.bigquery.materializedview.Recommender | ["project_resource"] | 140805.38289248943 | 9613.139166666666 | 2024-07-01 13:00:00 | google.bigquery.table.PartitionClusterRecommender | ["table_resource_1"] | 4393.7416711859405 | 56.61476777777777 | 2024-07-01 13:00:00 | google.bigquery.table.PartitionClusterRecommender | ["table_resource_2"] | 3934.07264107652 | 10.499466666666667 | 2024-07-01 13:00:00 +---------------------------------------------------+--------------------------------------------------------------------------------------------------+