使用 BigQuery 分析記錄檔
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BigQuery 是功能強大的分析工具。您可以使用這項服務儲存長期記錄,並對資料執行類似 SQL 的查詢。如要使用 BigQuery 進行分析,您必須明確將記錄檔傳送至 BigQuery,如下一節所述。
將記錄檔傳送至 BigQuery
- 在記錄檔探索工具中,建立可隔離 Fleet Engine 記錄的篩選器:
Fleetengine.googleapis.com/Fleet
。
- 在「查詢結果」窗格中,按一下「動作」或「更多動作」選單,然後選擇「建立接收器」。
- 指定接收器名稱 (例如 FleetEngineLogsSink)。點選「下一步」。
- 在「接收器目的地」中,選取「BigQuery 資料集」。
- 在「選取 BigQuery 資料集」中,選取「建立新的 BigQuery 資料集」。
- 在「建立資料集」對話方塊中,輸入「資料集 ID」。
- 其餘設定均保留預設狀態,然後點選「建立資料集」。
- 勾選「使用分區資料表」。點選「下一步」。
- 保留「選擇要納入接收器的記錄檔」和「選擇要從接收器排除的記錄檔」。
- 按一下「建立接收器」。
記錄現在應該會開始填入 BigQuery 資料集,這可能需要一段時間。另請參閱「將記錄檔傳送至支援的目的地」。
將記錄資料傳送至 BigQuery 後,系統會自動在 FleetEngineLogs 資料集下填入多個資料表,每個記錄類型各有一個資料表:
- CreateVehicle
- GetVehicle
- ListVehicles
- SearchVehicles
- UpdateVehicle
- CreateTrip
- GetTrip
- UpdateTrip
- ListTrips
資料表名稱採用下列模式:
project_id.data_set.log_name
舉例來說,如果專案名稱為 test-project,資料集名稱為 FleetEngineLogs,則 CreateTrip
資料表的名稱如下:
test-project.FleetEngineLogs.fleetengine_googleapis_com_create_trip
BigQuery 查詢範例
下列範例查詢說明如何在 BigQuery 中搜尋不同記錄項目。
以小時為單位分組的 CreateTrips 記錄數
SELECT TIMESTAMP_TRUNC(timestamp, HOUR) as hour,
count(*) as num_trips_created
FROM
`ProjectId.FleetEngineLogs.fleetengine_googleapis_com_create_trip`
GROUP BY hour
ORDER by hour
每輛車每小時的停靠次數
SELECT
jsonpayload_v1_updatevehiclelog.request.vehicleid AS vehicle,
TIMESTAMP_TRUNC(timestamp, HOUR) AS hour,
COUNT(*) AS num_stops
FROM
`ProjectId.FleetEngineLogs.fleetengine_googleapis_com_update__vehicle`
WHERE
ARRAY_LENGTH(jsonpayload_v1_updatevehiclelog.request.vehicle.remainingvehiclejourneysegments) > 0
AND jsonpayload_v1_updatevehiclelog.request.vehicle.remainingvehiclejourneysegments[
OFFSET
(0)].stop.state = 'VEHICLE_STOP_STATE_LOG_ARRIVED'
GROUP BY
1,
2
ORDER BY
2
舉例來說,這項查詢可能會告訴您過去一小時內:
- 車輛 A 在第 12 個小時完成 10 個停靠站,在第 13 個小時完成 8 個停靠站。
- 車輛 B 在第 11 小時完成 5 個停靠點,在第 12 小時完成 7 個停靠點。
- 車輛 C 在第 13 小時完成 12 個停靠站,在第 14 小時完成 9 個停靠站。
另請參閱「查看已路由至 BigQuery 的記錄」。
將 BigQuery 與 Looker Studio 整合
BigQuery 可與商業智慧工具整合,建立商業分析資訊主頁。請參閱 Looker Studio。
以下範例說明如何建構 Looker Studio 資訊主頁,在地圖上顯示行程和車輛移動情形。
- 啟動新的 Looker Studio 資訊主頁,然後選取 BigQuery 做為資料連線。
- 選取「自訂查詢」,然後手動輸入或選取應計費的 Cloud 專案。
- 在查詢方塊中輸入下列任一查詢。
隨選行程查詢範例
SELECT
timestamp,
labels.vehicle_id,
jsonpayload_v1_updatevehiclelog.response.lastlocation.location.latitude AS lat,
jsonpayload_v1_updatevehiclelog.response.lastlocation.location.longitude AS lng
FROM
`ProjectId.TableName.fleetengine_googleapis_com_update_vehicle`
排定的工作範例查詢
SELECT
labels.delivery_vehicle_id,
jsonpayload_v1_updatedeliveryvehiclelog.response.lastlocation.rawlocation.longitude as lat, jsonpayload_v1_updatedeliveryvehiclelog.response.lastlocation.rawlocation.latitude as lng
FROM `ProjectID.TableName.fleetengine_googleapis_com_update_delivery_vehicle`
- 選取「泡泡地圖」做為「圖表類型」,然後選取「位置」欄位。
- 選取「新增欄位」。
- 為欄位命名,然後新增下列公式:
CONCAT(lat, ",", lng)
。
- 將類型設為「地理位置」->「緯度、經度」。
- 您可以在資訊主頁中新增控制項來篩選資料。例如,選取「日期範圍」篩選器。
- 編輯日期範圍方塊,選取預設日期範圍。
- 您可以為
vehicle_id
新增其他下拉式清單控制項。透過這些控制項,您可以查看車輛的移動情形,或行程中的移動情形。
Looker Studio 輸出範例:

後續步驟
如要遵守資料保留政策,請參閱「限制記錄保留時間」。
除非另有註明,否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權,程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
上次更新時間:2025-08-31 (世界標準時間)。
[null,null,["上次更新時間:2025-08-31 (世界標準時間)。"],[[["\u003cp\u003eBigQuery enables analysis of Fleet Engine logs via SQL-like queries after routing logs to a BigQuery dataset.\u003c/p\u003e\n"],["\u003cp\u003eRouting logs to BigQuery involves creating a sink in the Logs Explorer and selecting a BigQuery dataset as the destination.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery automatically populates tables for each Fleet Engine log type under the specified dataset.\u003c/p\u003e\n"],["\u003cp\u003eExample queries demonstrate how to analyze trip creation, vehicle stops, and other data points within BigQuery.\u003c/p\u003e\n"],["\u003cp\u003eBigQuery integrates with Looker Studio for creating dashboards and visualizing data, such as vehicle movement on a map.\u003c/p\u003e\n"]]],[],null,["BigQuery is a powerful tool for performing analytics. You can use it to store\nlonger-term logs and to perform SQL-like queries against the data. To use\nBigQuery for analysis, you must explicitly route your logs to BigQuery, as\ndescribed in the next section.\n\nRoute logs to BigQuery\n\n1. In the [Logs Explorer](https://cloud.google.com/logging/docs/view/logs-explorer-interface), create a filter that isolates the Fleet Engine logs: `Fleetengine.googleapis.com/Fleet`.\n2. In the **Query Results pane** , click the **Actions** or **More Actions** menu and choose **Create Sink**.\n3. Specify a sink name (for example, *FleetEngineLogsSink* ). Click **Next**.\n4. In the **Sink Destination** , select **BigQuery dataset**.\n5. In **Select BigQuery dataset** , select **Create new BigQuery dataset**.\n6. In the **Create dataset** dialog, enter a **Dataset ID**.\n7. Leave everything else as is and click **Create dataset**.\n8. Check **Use partitioned tables** . Click **Next**.\n9. Leave **Choose logs to include in sink** and **Choose logs to filter out of\n sink** as they are.\n10. Click **Create Sink**.\n\nYour logs should now begin to populate the BigQuery dataset, which can take a\nshort while. See also [Route logs to supported destinations](https://cloud.google.com/logging/docs/export/configure_export_v2).\n\nOnce you are routing log data to BigQuery, several tables under the\n*FleetEngineLogs* dataset are automatically populated, one for each log type:\n\n- CreateVehicle\n- GetVehicle\n- ListVehicles\n- SearchVehicles\n- UpdateVehicle\n- CreateTrip\n- GetTrip\n- UpdateTrip\n- ListTrips\n\nThe table names use the following pattern: \n\n project_id.data_set.log_name\n\nFor example, if the project is called *test-project* and the dataset name is\n*FleetEngineLogs* , the `CreateTrip` table has the following name: \n\n test-project.FleetEngineLogs.fleetengine_googleapis_com_create_trip\n\nExample queries for BigQuery\n\nThe following example queries show how you can search for different log entries\nin BigQuery.\n\nNumber of CreateTrips logs grouped by hour \n\n SELECT TIMESTAMP_TRUNC(timestamp, HOUR) as hour,\n count(*) as num_trips_created\n FROM\n `ProjectId.FleetEngineLogs.fleetengine_googleapis_com_create_trip`\n GROUP BY hour\n ORDER by hour\n\nNumber of stops per vehicle per hour \n\n SELECT\n jsonpayload_v1_updatevehiclelog.request.vehicleid AS vehicle,\n TIMESTAMP_TRUNC(timestamp, HOUR) AS hour,\n COUNT(*) AS num_stops\n FROM\n `ProjectId.FleetEngineLogs.fleetengine_googleapis_com_update__vehicle`\n WHERE\n ARRAY_LENGTH(jsonpayload_v1_updatevehiclelog.request.vehicle.remainingvehiclejourneysegments) \u003e 0\n AND jsonpayload_v1_updatevehiclelog.request.vehicle.remainingvehiclejourneysegments[\n OFFSET\n (0)].stop.state = 'VEHICLE_STOP_STATE_LOG_ARRIVED'\n GROUP BY\n 1,\n 2\n ORDER BY\n 2\n\nFor example, this query could tell you that in the last hour:\n\n- Vehicle A completed 10 stops in hour 12 and 8 stops in hour 13.\n- Vehicle B completed 5 stops in hour 11 and 7 stops in hour 12.\n- Vehicle C completed 12 stops in hour 13 and 9 stops in hour 14.\n\nSee also [View logs routed to BigQuery](https://cloud.google.com/logging/docs/export/bigquery).\n\nIntegrate BigQuery with Looker Studio\n\nBigQuery can be integrated with business intelligence tools to create dashboards\nfor business analytics. See [Looker Studio](https://lookerstudio.google.com).\n\nThe following example shows how to build a Looker Studio dashboard for\nvisualizing trips and vehicle movements on a map.\n\n1. Launch a new [Looker Studio](https://lookerstudio.google.com) dashboard and select **BigQuery** as the data connection.\n2. Select **Custom Query** and manually enter or select the Cloud Project to which it should be billed.\n3. Enter one of the following queries into the query box.\n\nOn-demand trips example query \n\n SELECT\n timestamp,\n labels.vehicle_id,\n jsonpayload_v1_updatevehiclelog.response.lastlocation.location.latitude AS lat,\n jsonpayload_v1_updatevehiclelog.response.lastlocation.location.longitude AS lng\n FROM\n `ProjectId.TableName.fleetengine_googleapis_com_update_vehicle`\n\nScheduled Tasks example query \n\n SELECT\n labels.delivery_vehicle_id,\n jsonpayload_v1_updatedeliveryvehiclelog.response.lastlocation.rawlocation.longitude as lat, jsonpayload_v1_updatedeliveryvehiclelog.response.lastlocation.rawlocation.latitude as lng\n FROM `ProjectID.TableName.fleetengine_googleapis_com_update_delivery_vehicle`\n\n1. Select **Chart Type as Bubble Map** , and then select the **location** field.\n2. Select **Add a Field**.\n3. Name the field and add the following formula: `CONCAT(lat, \",\", lng)`.\n4. Set the type to **Geo-\\\u003eLatitude, Longitude**.\n5. You can add controls to the dashboard to filter data. For example, select the **Date-range** filter.\n6. Edit the date range box to select a default date range.\n7. You can add additional *drop-down list* controls for `vehicle_id`. With these controls, you can visualize the movement of the vehicle or the movement within a trip.\n\nLooker Studio example output:\n\nWhat's next\n\nTo comply with data retention policies, see [Restrict log\nretention](/maps/documentation/mobility/operations/cloud-logging/reduce-cost)."]]