JOBS_TIMELINE_BY_USER view
The INFORMATION_SCHEMA.JOBS_TIMELINE_BY_USER
view contains near real-time
BigQuery metadata by timeslice of the jobs submitted by the
current user in the current project. This view contains currently running and
completed jobs.
Required permissions
To query the INFORMATION_SCHEMA.JOBS_TIMELINE_BY_USER
view, you need the
bigquery.jobs.list
Identity and Access Management (IAM) permission for the project.
Each of the following predefined IAM roles includes the required
permission:
- Project Viewer
- BigQuery User
For more information about BigQuery permissions, see Access control with IAM.
Schema
When you query the INFORMATION_SCHEMA.JOBS_TIMELINE_BY_*
views, the query
results contain one row for every second of execution of every
BigQuery job. Each period starts on a whole-second interval and
lasts exactly one second.
The INFORMATION_SCHEMA.JOBS_TIMELINE_BY_*
view has the following schema:
Column name | Data type | Value |
---|---|---|
period_start |
TIMESTAMP |
Start time of this period. |
period_slot_ms |
INTEGER |
Slot milliseconds consumed in this period. |
period_shuffle_ram_usage_ratio |
FLOAT |
Shuffle usage ratio in the selected time period. |
project_id |
STRING |
(Clustering column) ID of the project. |
project_number |
INTEGER |
Number of the project. |
user_email |
STRING |
(Clustering column) Email address or service account of the user who ran the job. |
job_id |
STRING |
ID of the job. For example, bquxjob_1234 . |
job_type |
STRING |
The type of the job. Can be QUERY , LOAD ,
EXTRACT , COPY , or null . Job
type null indicates an internal job, such as script job
statement evaluation or materialized view refresh. |
statement_type |
STRING |
The type of query statement, if valid. For example,
SELECT , INSERT , UPDATE , or
DELETE . |
job_creation_time |
TIMESTAMP |
(Partitioning column) Creation time of this job. Partitioning is based on the UTC time of this timestamp. |
job_start_time |
TIMESTAMP |
Start time of this job. |
job_end_time |
TIMESTAMP |
End time of this job. |
state |
STRING |
Running state of the job at the end of this period. Valid states
include PENDING , RUNNING , and
DONE . |
reservation_id |
STRING |
Name of the primary reservation assigned to this job at the end of this period, if applicable. |
edition |
STRING |
The edition associated with the reservation assigned to this job. For more information about editions, see Introduction to BigQuery editions. |
total_bytes_processed |
INTEGER |
Total bytes processed by the job. |
error_result |
RECORD |
Details of error (if any) as an
ErrorProto.
|
cache_hit |
BOOLEAN |
Whether the query results of this job were from a cache. |
period_estimated_runnable_units |
INTEGER |
Units of work that can be scheduled immediately in this period. Additional slots for these units of work accelerate your query, provided no other query in the reservation needs additional slots. |
Data retention
This view contains currently running jobs and the job history of the past 180 days.
Scope and syntax
Queries against this view must include a region qualifier. If you do not specify a regional qualifier, metadata is retrieved from all regions. The following table explains the region and resource scope for this view:
View name | Resource scope | Region scope |
---|---|---|
[PROJECT_ID.]`region-REGION`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_USER |
Jobs submitted by the current user in the specified project. | 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
The following query displays the total slot milliseconds consumed per second by jobs submitted by the current user in the designated project:
SELECT period_start, SUM(period_slot_ms) AS total_period_slot_ms FROM `region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_USER GROUP BY period_start ORDER BY period_start DESC;
The result is similar to the following:
+---------------------------+---------------------------------+ | period_start | total_period_slot_ms | +---------------------------+---------------------------------+ | 2019-10-10 00:00:04 UTC | 118639 | | 2019-10-10 00:00:03 UTC | 251353 | | 2019-10-10 00:00:02 UTC | 1074064 | | 2019-10-10 00:00:01 UTC | 1124868 | | 2019-10-10 00:00:00 UTC | 1113961 | +---------------------------+---------------------------------+