Google BigQuery

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La monitorización Advanced BigQuery está en Vista previa. Utiliza este formulario para registrarte y empezar a obtener información sobre el rendimiento de sus consultas.

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Información general

BigQuery de Google es el almacén de datos empresariales de bajo coste, totalmente gestionado y a escala de petabyte para realizar análisis.

Obtén métricas de Google BigQuery para:

  • Visualizar el rendimiento de tus consultas BigQuery.
  • Correlacionar el rendimiento de tus consultas BigQuery con tus aplicaciones.

Configuración

Instalación

Si aún no lo has hecho, configura la integración Google Cloud Platform. No es necesario realizar ningún otro paso de instalación.

Recopilación de logs

Los logs de Google BigQuery se recopilan con Google Cloud Logging y se envían a una tarea de Dataflow a través de un tema Cloud Pub/Sub. Si aún no lo has hecho, configura la generación de logs con la plantilla Dataflow de Datadog.

Una vez hecho esto, exporta tus logs de Google BigQuery desde Google Cloud Logging al tema Pub/Sub:

  1. Ve a la página de Google Cloud Logging y filtra logs de Google BigQuery.
  2. Haz clic en Create Export (Crear exportación) y asigna un nombre al sumidero.
  3. Elige “Cloud Pub/Sub” como destino y selecciona el tema Pub/Sub creado para tal fin. Nota: El tema Pub/Sub puede estar ubicado en un proyecto diferente.
  4. Haz clic en Create (Crear) y espera a que aparezca el mensaje de confirmación.

Datos recopilados

Métricas

gcp.bigquery.job.num_in_flight
(gauge)
Number of in flight jobs.
Shown as job
gcp.bigquery.query.biengine_fallback_count
(count)
The reasons that queries failed BI Engine execution.
Shown as query
gcp.bigquery.query.column_metadata_index_staleness.avg
(gauge)
The average distribution of staleness in milliseconds of the column metadata index for queries that successfully used the column metadata index in the last sampling interval.
Shown as millisecond
gcp.bigquery.query.column_metadata_index_staleness.samplecount
(gauge)
The sample count for distribution of staleness in milliseconds of the column metadata index for queries that successfully used the column metadata index in the last sampling interval.
Shown as millisecond
gcp.bigquery.query.column_metadata_index_staleness.sumsqdev
(gauge)
The sum of squared deviation for distribution of staleness in milliseconds of the column metadata index for queries that successfully used the column metadata index in the last sampling interval.
Shown as millisecond
gcp.bigquery.query.count
(gauge)
Queries in flight.
Shown as query
gcp.bigquery.query.execution_count
(count)
Number of queries executed.
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 six-hour delay.
Shown as byte
gcp.bigquery.query.scanned_bytes_billed
(rate)
Number of scanned bytes billed. Note: this metric is available with a six-hour delay.
Shown as byte
gcp.bigquery.query.statement_scanned_bytes
(count)
Scanned bytes broken down by statement type. Note: this metric is available with a six-hour delay.
Shown as byte
gcp.bigquery.query.statement_scanned_bytes_billed
(count)
Scanned bytes billed broken down by statement type. Note: this metric is available with a six-hour 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.assigned
(gauge)
The number of slots assigned to the given project or organization.
gcp.bigquery.slots.capacity_committed
(gauge)
The total slot capacity commitments purchased through this administrator project or organization.
gcp.bigquery.slots.max_assigned
(gauge)
The maximum number of slots assigned to the given project or organization.
gcp.bigquery.slots.total_allocated_for_reservation
(gauge)
Number of BigQuery slots currently allocated across all projects in the reservation.
gcp.bigquery.storage.insertall_inserted_bytes
(count)
The number of bytes uploaded by the project using the InsertAll streaming API.
Shown as byte
gcp.bigquery.storage.insertall_inserted_rows
(count)
The number of rows uploaded by the project using the InsertAll streaming API.
Shown as row
gcp.bigquery.storage.stored_bytes
(gauge)
Number of bytes stored. Note: this metric is available with a three-hour delay.
Shown as byte
gcp.bigquery.storage.table_count
(gauge)
Number of tables. Note: this metric is available with a three-hour delay.
Shown as table
gcp.bigquery.storage.uploaded_bytes
(count)
Number of uploaded bytes. Note: this metric is available with a six-hour delay.
Shown as byte
gcp.bigquery.storage.uploaded_bytes_billed
(count)
Number of uploaded bytes billed. Note: this metric is available with a six-hour delay.
Shown as byte
gcp.bigquery.storage.uploaded_row_count
(count)
Number of uploaded rows. Note: this metric is available with a six-hour delay.
Shown as row

Eventos

La integración Google BigQuery no incluye eventos.

Checks de servicio

La integración Google BigQuery no incluye checks de servicios.

Solucionar problemas

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