Google BigQuery

Overview

BigQuery is Google’s fully managed, petabyte scale, low cost enterprise data warehouse for analytics.

Get metrics from Google BigQuery to:

Visualize the performance of your BigQuery queries.
Correlate the performance of your BigQuery queries with your applications.

Setup

Installation

If you haven’t already, set up the Google Cloud Platform integration first. There are no other installation steps that need to be performed.

Log collection

Google BigQuery logs are collected with Google Cloud Logging and sent to a Cloud pub/sub with an HTTP push forwarder. If you haven’t already, set up a Cloud pub/sub with an HTTP push forwarder.

Once this is done, export your Google BigQuery logs from Google Cloud Logging to the pub/sub:

Go to the Google Cloud Logging page and filter the Google BigQuery logs.
Click Create Export and name the sink.
Choose “Cloud Pub/Sub” as the destination and select the pub/sub that was created for that purpose. Note: The pub/sub can be located in a different project.
Click Create and wait for the confirmation message to show up.

Data Collected

Metrics

gcp.bigquery.job.num_in_flight (gauge)	Number of in flight jobs Shown as job
gcp.bigquery.query.count (gauge)	Queries in flight Shown as query
gcp.bigquery.query.execution_times.avg (gauge)	Average of query execution times Shown as second
gcp.bigquery.query.execution_times.samplecount (count)	Sample Count of query execution times Shown as second
gcp.bigquery.query.execution_times.sumsqdev (gauge)	Sum of Squared Deviation for query execution times Shown as second
gcp.bigquery.query.scanned_bytes (rate)	Number of scanned bytes. Note: this metric is available with a 6h delay Shown as byte
gcp.bigquery.query.scanned_bytes_billed (rate)	Number of scanned bytes billed. Note: this metric is available with a 6h delay Shown as byte
gcp.bigquery.query.statement_scanned_bytes (rate)	Scanned bytes broken down by statement type. Note: this metric is available with a 6h delay Shown as byte
gcp.bigquery.query.statement_scanned_bytes_billed (rate)	Scanned bytes billed broken down by statement type. Note: this metric is available with a 6h delay Shown as byte
gcp.bigquery.slots.allocated (gauge)	Number of BigQuery slots currently allocated for project, slot allocation can be broken down based on reservation and job type
gcp.bigquery.slots.allocated_for_project (gauge)	Number of BigQuery slots currently allocated for the project
gcp.bigquery.slots.allocated_for_project_and_job_type (gauge)	Number of BigQuery slots currently allocated for the project and job type
gcp.bigquery.slots.allocated_for_reservation (gauge)	Number of BigQuery slots currently allocated for project in the reservation
gcp.bigquery.slots.total_allocated_for_reservation (gauge)	Number of BigQuery slots currently allocated across all projects in the reservation
gcp.bigquery.storage.stored_bytes (gauge)	Number of bytes stored. Note: this metric is available with a 3h delay Shown as byte
gcp.bigquery.storage.table_count (gauge)	Number of tables. Note: this metric is available with a 3h delay Shown as table
gcp.bigquery.storage.uploaded_bytes (rate)	Number of uploaded bytes. Note: this metric is available with a 6h delay Shown as byte
gcp.bigquery.storage.uploaded_bytes_billed (rate)	Number of uploaded bytes billed. Note: this metric is available with a 6h delay Shown as byte
gcp.bigquery.storage.uploaded_row_count (rate)	Number of uploaded rows. Note: this metric is available with a 6h delay Shown as row

Events

The Google BigQuery integration does not include any events.

Service Checks

The Google BigQuery integration does not include any service checks.

Troubleshooting

Need help? Contact Datadog support.