INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION ビューをクエリするには、組織の bigquery.jobs.listAll Identity and Access Management（IAM）権限が必要です。次に示す各 IAM の事前定義ロールには、必要な権限が含まれています。
組織レベルの BigQuery リソース管理者
組織オーナー
組織管理者
JOBS_BY_ORGANIZATION スキーマ テーブルは、Trusted Cloud by S3NS 組織が定義されているユーザーのみが使用できます。
SELECTres.period_start,SUM(jobs.period_slot_ms)/1000/60ASperiod_slot_minutes,ANY_VALUE(res.slots_assigned)ASrough_slots_assigned,ANY_VALUE(res.slots_max_assigned)ASrough_slots_max_assignedFROM`region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATIONjobsJOIN`region-us`.INFORMATION_SCHEMA.RESERVATIONS_TIMELINEresONTIMESTAMP_TRUNC(jobs.period_start,MINUTE)=res.period_startANDjobs.reservation_id=res.reservation_idWHEREjobs.job_creation_timeBETWEENTIMESTAMP_SUB(CURRENT_TIMESTAMP(),INTERVAL1DAY)ANDCURRENT_TIMESTAMP()ANDres.reservation_id='YOUR_RESERVATION_ID'AND(jobs.statement_type!="SCRIPT"ORjobs.statement_typeISNULL)-- Avoid duplicate byte counting in parent and children jobs.GROUPBYperiod_startORDERBYperiod_startDESC;
SELECTres.period_start,res.reservation_id,SUM(jobs.period_slot_ms)/1000/60ASperiod_slot_minutes,ANY_VALUE(res.slots_assigned)ASrough_slots_assigned,ANY_VALUE(res.slots_max_assigned)ASrough_slots_max_assigned,FROM`region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATIONjobsJOIN`region-us`.INFORMATION_SCHEMA.RESERVATIONS_TIMELINEresONTIMESTAMP_TRUNC(jobs.period_start,MINUTE)=res.period_startANDjobs.reservation_id=res.reservation_idWHEREjobs.job_creation_timeBETWEENTIMESTAMP_SUB(CURRENT_TIMESTAMP(),INTERVAL1DAY)ANDCURRENT_TIMESTAMP()AND(jobs.statement_type!="SCRIPT"ORjobs.statement_typeISNULL)-- Avoid duplicate byte counting in parent and children jobs.GROUPBYperiod_start,reservation_idORDERBYperiod_startDESC,reservation_id;
[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["必要な情報がない","missingTheInformationINeed","thumb-down"],["複雑すぎる / 手順が多すぎる","tooComplicatedTooManySteps","thumb-down"],["最新ではない","outOfDate","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["サンプル / コードに問題がある","samplesCodeIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2025-08-19 UTC。"],[[["\u003cp\u003eThe \u003ccode\u003eINFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION\u003c/code\u003e view provides near real-time BigQuery metadata, detailing every second of execution for all jobs within an organization.\u003c/p\u003e\n"],["\u003cp\u003eAccess to this view requires the \u003ccode\u003ebigquery.jobs.listAll\u003c/code\u003e IAM permission at the organization level, which is included in predefined roles like BigQuery Resource Admin, Organization Owner, and Organization Admin.\u003c/p\u003e\n"],["\u003cp\u003eEach row in the query results of this view corresponds to a one-second interval of a BigQuery job's execution, capturing details such as slot milliseconds consumed, project ID, user email, job type, and state.\u003c/p\u003e\n"],["\u003cp\u003eThe view's data includes currently running jobs and job history from the past 180 days, and it is partitioned by \u003ccode\u003ejob_creation_time\u003c/code\u003e and clustered by \u003ccode\u003eproject_id\u003c/code\u003e and \u003ccode\u003euser_email\u003c/code\u003e.\u003c/p\u003e\n"],["\u003cp\u003eQueries against this view require a region qualifier to specify the region from which to retrieve metadata and the query execution location must match the region of the \u003ccode\u003eINFORMATION_SCHEMA\u003c/code\u003e view.\u003c/p\u003e\n"]]],[],null,["# JOBS_TIMELINE_BY_ORGANIZATION view\n==================================\n\nThe `INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION` view contains near\nreal-time\nBigQuery metadata by timeslice for all jobs submitted in the\norganization associated with the current project.\nThis view contains currently running and completed jobs.\n\nRequired permissions\n--------------------\n\nTo query the `INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION` view, you need\nthe `bigquery.jobs.listAll` Identity and Access Management (IAM) permission for the organization.\nEach of the following predefined IAM roles includes the required\npermission:\n\n- BigQuery Resource Admin at the organization level\n- Organization Owner\n- Organization Admin\n\nThe `JOBS_BY_ORGANIZATION` schema table is only available to users with defined\nGoogle Cloud organizations.\n\nFor more information about BigQuery permissions, see\n[Access control with IAM](/bigquery/docs/access-control).\n\nSchema\n------\n\nWhen you query the `INFORMATION_SCHEMA.JOBS_TIMELINE_BY_*` views, the query\nresults contain one row for every second of execution of every\nBigQuery job. Each period starts on a whole-second interval and\nlasts exactly one second.\n\nThe `INFORMATION_SCHEMA.JOBS_TIMELINE_BY_*` view has the following schema:\n| **Note:** The underlying data is partitioned by the `job_creation_time` column and clustered by `project_id` and `user_email`.\n\nData retention\n--------------\n\nThis view contains currently running jobs and the job history of the past 180\ndays.\n\nScope and syntax\n----------------\n\nQueries against this view must include a [region qualifier](/bigquery/docs/information-schema-intro#syntax).\nIf you do not specify a regional qualifier, metadata is retrieved from all\nregions. The following table explains the region scope for this view:\n\nReplace the following:\n\n- Optional: \u003cvar translate=\"no\"\u003ePROJECT_ID\u003c/var\u003e: the ID of your Google Cloud project. If not specified, the default project is used.\n- \u003cvar translate=\"no\"\u003eREGION\u003c/var\u003e: any [dataset region name](/bigquery/docs/locations). For example, ```region-us```.\n\n \u003cbr /\u003e\n\n \u003cbr /\u003e\n\n | **Note:** You must use [a region qualifier](/bigquery/docs/information-schema-intro#region_qualifier) to query `INFORMATION_SCHEMA` views. The location of the query execution must match the region of the `INFORMATION_SCHEMA` view.\n\n\u003cbr /\u003e\n\nExamples\n--------\n\n#### Example: See total slot usage per minute\n\nTo run the query against a project other than your default project, add the\nproject ID in the following format: \n\n```bash\n`PROJECT_ID`.`region-REGION_NAME`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION\n```\n. For example, ```myproject`.`region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION``.\n\n\u003cbr /\u003e\n\n| **Caution:** To compare slot usage to slot capacity, you can combine the reservation information with the jobs timeline by using the reservation timeline view. However, the results from using this method can be inaccurate. The `INFORMATION_SCHEMA.RESERVATIONS_TIMELINE` view displays reservation metadata with minute-level granularity. If the reservation changes more than once within a minute, the view only displays the largest value for that minute. For example, if your [autoscaling](/bigquery/docs/slots-autoscaling-intro) reservation scales first from 0 to 100 slots, and then from 100 to 200 slots within the same minute, the value of `autoscale.current_slots` is 200 for that minute. Using this method, the value of `slot_capacity` might be considerably larger than the true value. For information about more granular monitoring of slots, see [Monitoring autoscaling with information\n| schema](/bigquery/docs/slots-autoscaling-intro#monitor_autoscaling_with_information_schema).\n\nThe following example shows per-minute slot usage from projects assigned to\n\u003cvar translate=\"no\"\u003eYOUR_RESERVATION_ID\u003c/var\u003e across all jobs: \n\n```googlesql\nSELECT\n res.period_start,\n SUM(jobs.period_slot_ms) / 1000 / 60 AS period_slot_minutes,\n ANY_VALUE(res.slots_assigned) AS rough_slots_assigned,\n ANY_VALUE(res.slots_max_assigned) AS rough_slots_max_assigned\nFROM\n `region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION jobs\nJOIN\n `region-us`.INFORMATION_SCHEMA.RESERVATIONS_TIMELINE res\n ON\n TIMESTAMP_TRUNC(jobs.period_start, MINUTE) = res.period_start\n AND jobs.reservation_id = res.reservation_id\nWHERE\n jobs.job_creation_time\n BETWEEN TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 1 DAY)\n AND CURRENT_TIMESTAMP()\n AND res.reservation_id = '\u003cvar translate=\"no\"\u003eYOUR_RESERVATION_ID\u003c/var\u003e'\n AND (jobs.statement_type != \"SCRIPT\" OR jobs.statement_type IS NULL) -- Avoid duplicate byte counting in parent and children jobs.\nGROUP BY\n period_start\nORDER BY\n period_start DESC;\n```\n\nThe result is similar to the following: \n\n```\n+-----------------------+---------------------+---------------------+-------------------------+\n| period_start | period_slot_minutes | rough_slots_assigned| rough_slots_max_assigned|\n+-----------------------+---------------------+---------------------+-------------------------+\n|2021-06-08 21:33:00 UTC| 100.000 | 100 | 100 |\n|2021-06-08 21:32:00 UTC| 96.753 | 100 | 100 |\n|2021-06-08 21:31:00 UTC| 41.668 | 100 | 100 |\n+-----------------------+---------------------+---------------------+-------------------------+\n```\n\n#### Example: Slot usage by reservation\n\nThe following example shows per-minute slot usage for each reservation in the\nlast day:\n| **Caution:** To compare slot usage to slot capacity, you can combine the reservation information with the jobs timeline by using the reservation timeline view. However, the results from using this method can be inaccurate. The `INFORMATION_SCHEMA.RESERVATIONS_TIMELINE` view displays reservation metadata with minute-level granularity. If the reservation changes more than once within a minute, the view only displays the largest value for that minute. For example, if your [autoscaling](/bigquery/docs/slots-autoscaling-intro) reservation scales first from 0 to 100 slots, and then from 100 to 200 slots within the same minute, the value of `autoscale.current_slots` is 200 for that minute. Using this method, the value of `slot_capacity` might be considerably larger than the true value. For information about more granular monitoring of slots, see [Monitoring autoscaling with information\nschema](/bigquery/docs/slots-autoscaling-intro#monitor_autoscaling_with_information_schema). \n\n```googlesql\nSELECT\n res.period_start,\n res.reservation_id,\n SUM(jobs.period_slot_ms) / 1000 / 60 AS period_slot_minutes,\n ANY_VALUE(res.slots_assigned) AS rough_slots_assigned,\n ANY_VALUE(res.slots_max_assigned) AS rough_slots_max_assigned,\nFROM\n `region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_ORGANIZATION jobs\nJOIN\n `region-us`.INFORMATION_SCHEMA.RESERVATIONS_TIMELINE res\n ON TIMESTAMP_TRUNC(jobs.period_start, MINUTE) = res.period_start\n AND jobs.reservation_id = res.reservation_id\nWHERE\n jobs.job_creation_time\n BETWEEN TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 1 DAY)\n AND CURRENT_TIMESTAMP()\n AND (jobs.statement_type != \"SCRIPT\" OR jobs.statement_type IS NULL) -- Avoid duplicate byte counting in parent and children jobs.\nGROUP BY\n period_start,\n reservation_id\nORDER BY\n period_start DESC,\n reservation_id;\n```\n\nThe result is similar to the following: \n\n```\n+-----------------------+----------------+---------------------+----------------------+--------------------------+\n| period_start | reservation_id | period_slot_minutes | rough_slots_assigned | rough_slots_max_assigned |\n+-----------------------+----------------+---------------------+----------------------+--------------------------+\n|2021-06-08 21:33:00 UTC| prod01 | 100.000 | 100 | 100 |\n|2021-06-08 21:33:00 UTC| prod02 | 177.201 | 200 | 500 |\n|2021-06-08 21:32:00 UTC| prod01 | 96.753 | 100 | 100 |\n|2021-06-08 21:32:00 UTC| prod02 | 182.329 | 200 | 500 |\n+-----------------------+----------------+---------------------+----------------------+--------------------------+\n```"]]
