Monitor BI Engine

BigQuery BI Engine accelerates BigQuery for BI scenarios using memory cache and faster execution. Acceleration details can be monitored using INFORMATION_SCHEMA and Cloud Monitoring metrics.

Cloud Monitoring

You can monitor and configure alerts for BigQuery BI Engine with Cloud Monitoring. To learn how to create dashboard for BI Engine metrics, see Creating charts.

The following metrics are provided for BigQuery BI Engine:

Resource Metric Details
BigQuery Project Reservation Total Bytes Total capacity allocated to one Google Cloud project
BigQuery Project Reservation Used Bytes Total capacity used in one Google Cloud project
BigQuery Project BI Engine Top Tables Cached Bytes Cache usage per table. This metric displays the top N tables per region report usage.

Query statistics for BI Engine

This section explains how to find query statistics to help monitor, diagnose, and troubleshoot BI Engine use.

BI Engine acceleration modes

With BI Engine acceleration enabled, your query can run in any one of these four modes:

BI_ENGINE_DISABLED
 		BI Engine disabled the acceleration. biEngineReasons specifies a more detailed reason. The query was run using the BigQuery execution engine. 
PARTIAL_INPUT
 Part of the query input was accelerated using BI Engine. As described in Query optimization and acceleration, a query plan is generally broken down into multiple input stages. BI Engine supports the common types of subquery patterns that are typically used in dashboarding. If the query consists of multiple input stages, only a few of which fall under the supported use cases, then BI Engine runs the unsupported stages using the normal BigQuery engine without acceleration. In this situation, BI Engine returns a PARTIAL acceleration code, and uses biEngineReasons to populate the reason for not accelerating other input stages. 
 FULL_INPUT
All input stages of the query were accelerated using BI Engine. Cached data is reused across queries, and the computation that follows immediately after reading the data is accelerated. 
 FULL_QUERY
The entire query was accelerated using BI Engine.

View BigQuery API job statistics

Detailed statistics on BI Engine are available through the BigQuery API.

To fetch the statistics associated with BI Engine accelerated queries, run the following bq command-line tool command:

bq show --format=prettyjson -j job_id

If the project is enabled for BI Engine acceleration, then the output produces a new field, biEngineStatistics. Here is a sample job report:

 "statistics": { "creationTime": "1602175128902", "endTime": "1602175130700", "query": { "biEngineStatistics": { "biEngineMode": "DISABLED", "biEngineReasons": [ { "code": "UNSUPPORTED_SQL_TEXT", "message": "Detected unsupported join type" } ] },

For more information about the BiEngineStatistics field, see the Job reference.

BigQuery information schema statistics

BI Engine acceleration statistics are included in the BigQuery INFORMATION_SCHEMA views as part of the INFORMATION_SCHEMA.JOBS_BY_* views in the bi_engine_statistics column. For example, this query returns the bi_engine_statistics for all of the current projects' jobs for the last 24 hours:

SELECT creation_time, job_id, bi_engine_statistics FROM `region-us`.INFORMATION_SCHEMA.JOBS_BY_PROJECT WHERE creation_time > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 1 DAY) AND job_type = "QUERY"

Use the following format to specify regionality for the project-id, region, and views in the INFORMATION_SCHEMA view: 

`PROJECT_ID`.`region-REGION_NAME`.INFORMATION_SCHEMA.VIEW

View Looker Studio information schema details

You can track which Looker Studio reports and data sources are used by BigQuery by viewing the INFORMATION_SCHEMA.JOBS view. Every Looker Studio query in BigQuery creates an entry with report_id and datasource_id labels. Those IDs appear at the end of Looker Studio URL when opening a report or data source page. For example, a report with URL https://lookerstudio.google.com/navigation/reporting/my-report-id-123 has a report ID of "my-report-id-123".

The following examples show how to view reports and data sources:

Find report and data source URL for each Looker Studio BigQuery job

-- Standard labels used by Looker Studio. DECLARE requestor_key STRING DEFAULT 'requestor'; DECLARE requestor_value STRING DEFAULT 'looker_studio'; CREATE TEMP FUNCTION GetLabel(labels ANY TYPE, label_key STRING) AS (  (SELECT l.value FROM UNNEST(labels) l WHERE l.key = label_key) ); CREATE TEMP FUNCTION GetDatasourceUrl(labels ANY TYPE) AS (  CONCAT("https://lookerstudio.google.com/datasources/", GetLabel(labels, 'looker_studio_datasource_id')) ); CREATE TEMP FUNCTION GetReportUrl(labels ANY TYPE) AS (  CONCAT("https://lookerstudio.google.com/reporting/", GetLabel(labels, 'looker_studio_report_id')) ); SELECT  job_id,  GetDatasourceUrl(labels) AS datasource_url,  GetReportUrl(labels) AS report_url, FROM  `region-us`.INFORMATION_SCHEMA.JOBS jobs WHERE  creation_time > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)  AND GetLabel(labels, requestor_key) = requestor_value LIMIT  100;

View jobs produced by using a report and data source

-- Specify report and data source id, which can be found at the end of Looker Studio URLs. DECLARE user_report_id STRING DEFAULT '*report id here*'; DECLARE user_datasource_id STRING DEFAULT '*datasource id here*'; -- Looker Studio labels for BigQuery. DECLARE requestor_key STRING DEFAULT 'requestor'; DECLARE requestor_value STRING DEFAULT 'looker_studio'; DECLARE datasource_key STRING DEFAULT 'looker_studio_datasource_id'; DECLARE report_key STRING DEFAULT 'looker_studio_report_id'; CREATE TEMP FUNCTION GetLabel(labels ANY TYPE, label_key STRING) AS (  (SELECT l.value FROM UNNEST(labels) l WHERE l.key = label_key) ); SELECT  creation_time,  job_id, FROM  `region-us`.INFORMATION_SCHEMA.JOBS jobs WHERE  creation_time > TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)  AND GetLabel(labels, requestor_key) = requestor_value  AND GetLabel(labels, datasource_key) = user_datasource_id  AND GetLabel(labels, report_key) = user_report_id ORDER BY 1 LIMIT 100;

Cloud Logging

BI Engine acceleration is part of BigQuery job processing. To inspect BigQuery jobs for a specific project, see the Cloud Logging page with a payload of protoPayload.serviceName="bigquery.googleapis.com".

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