[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-09-04 (世界標準時間)。"],[[["\u003cp\u003eBigtable Studio allows users to manage and explore Bigtable data directly within the Google Cloud console, using its integrated Explorer pane.\u003c/p\u003e\n"],["\u003cp\u003eThe Explorer pane in Bigtable Studio enables users to perform various actions on tables, including creation, deletion, editing, and monitoring, as well as managing column families and their garbage collection policies.\u003c/p\u003e\n"],["\u003cp\u003eUsers can query their Bigtable data through either an interactive Query builder, which requires no code, or the Query editor, which utilizes SQL statements.\u003c/p\u003e\n"],["\u003cp\u003eTo query a table, users need the Bigtable reader IAM role on the instance that contains the table, which can be granted by an administrator.\u003c/p\u003e\n"],["\u003cp\u003eThe Query editor supports SQL SELECT statements, allowing for complex queries, and offers features like formatting, running selected portions of code, and viewing detailed row data, including historical data.\u003c/p\u003e\n"]]],[],null,["Manage your data using Bigtable Studio\n\nThis page explains how to explore and manage your Bigtable data\nusing Bigtable Studio in the Google Cloud console.\n\nBigtable Studio includes an **Explorer** pane that\nintegrates with the following:\n\n- Query builder, an interactive form that lets you build and run a query without writing code\n- Query editor, where you can create and execute SQL commands\n- SQL query results table\n\nIf you're new to Bigtable, learn how to\n[create an instance and write data with the\n`cbt` CLI](/bigtable/docs/create-instance-write-data-cbt-cli).\n\nRequired roles\n\n\nTo get the permissions that\nyou need to query a table,\n\nask your administrator to grant you the\nfollowing IAM roles on the instance that contains the table:\n\n- All: [Bigtable reader](/iam/docs/roles-permissions/bigtable#bigtable.reader) (`roles/bigtable.reader`)\n\n\nFor more information about granting roles, see [Manage access to projects, folders, and organizations](/iam/docs/granting-changing-revoking-access).\n\n\nYou might also be able to get\nthe required permissions through [custom\nroles](/iam/docs/creating-custom-roles) or other [predefined\nroles](/iam/docs/roles-overview#predefined).\n\nExplore your data\n\nYou can use the explorer to perform the following actions on your\nBigtable resources:\n\n| Bigtable resource | Explorer actions |\n|------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Table | - Create a new table - Create a backup - Prevent deletion - Edit - Delete - View a sample query - View backups - Monitor by viewing system insights - Export to Cloud Storage |\n| Column families | - Add a column family to a table |\n| Specific column family | - Edit a garbage collection policy |\n| Authorized view | - Open in the query builder - Grant access - Delete |\n| View | - View definition in the query editor |\n| Materialized view | - View definition in the query editor - Enable or disable deletion protection |\n\nTo access the **Explorer**, follow these steps:\n\n1. In the Google Cloud console, open the **Bigtable instances** page.\n\n [Go to instances list](https://console.cloud.google.com/bigtable)\n2. Select an instance from the list.\n\n3. In the navigation menu, click **Bigtable Studio** . The\n **Explorer** pane displays a list of tables and authorized views in the\n instance.\n\nQuery your data in the query builder\n\nThe query builder is an interactive form that lets you send read requests to the\nBigtable Data API from the Google Cloud console without needing to write\ncode or SQL statements. For more information, see [Build queries in the\nconsole](/bigtable/docs/query-builder).\n\nQuery your data with SQL in the query editor\n\nUsing the query editor, you can run any combination of SQL `SELECT` statements.\nStatements must be separated by a semicolon.\n\nStatements are executed based on the order in which you enter them in the query\neditor.\n| **Note:** You can't use a [Data Boost](/bigtable/docs/data-boost-overview) app profile with the query editor.\n\nTo query your data, follow these steps:\n\n1. In the Google Cloud console, open the **Bigtable instances** page.\n\n [Go to instances list](https://console.cloud.google.com/bigtable)\n2. Select an instance from the list.\n\n3. In the navigation menu, click **Bigtable Studio**.\n\n4. Compose a query:\n\n 1. Open a new tab by clicking add and then choosing **Editor**.\n 2. When the query editor appears, write your query. If the query is valid SQL, a **Valid** message is displayed.\n 3. Optional: To return all cells in the queried columns instead of only the most recent cell, append the table ID with `(with_history =\u003e TRUE)`.\n5. Optional: To format your statement in SQL style, click **Format**.\n\n6. Click **Run** . The results of your query appear in the **Results** table.\n\n7. To view a formatted display of a row's data, click the row in the results\n table. The **Row details** pane opens. Each column qualifier and its value\n are displayed on a new line. If you run the query using `(with_history =\u003e\n TRUE)`, each cell in a column is presented as a struct that includes the\n value and timestamp for the cell.\n\n8. Optional: To run only a selected portion of the text in the editor,\n highlight it, and then click **Run selected** . The results of the\n highlighted query appear in the **Results** table.\n\nTo remove all text from the query editor, click **Clear**.\n\nFor more information, including examples, about crafting SQL statements to query\nyour Bigtable data, see the [GoogleSQL for\nBigtable overview](/bigtable/docs/googlesql-overview).\n| **Note:** You can use an app profile configured for multi-cluster routing to run queries in the query editor, but if the request fails, it doesn't fail over to another cluster and you must run it again.\n\nExport query results\n\nYou can export the results of your query in one of the following ways:\n\n- Download a local file in a CSV or JSON format.\n- Export to Google Sheets.\n- Copy to clipboard in a CSV, TSV, or JSON file format.\n\nTo export query results from the query editor or the query\nbuilder, follow these steps:\n\n1. In the Google Cloud console, open the **Bigtable instances** page.\n\n [Go to instances list](https://console.cloud.google.com/bigtable)\n2. Select an instance from the list.\n\n3. In the navigation menu, click **Bigtable Studio**.\n\n The **Explorer** pane displays a list of tables and authorized views in the\n instance.\n4. Run your query from either the **Builder** or the **Editor** tab.\n\n The results appear in the **Results** table.\n5. On the **Results** toolbar, click **Export**.\n\n6. From the menu, select one of the export options.\n\n If you selected **Export to Google Sheets** , a dialog appears. Click **Open**\n to view your results in Google Sheets.\n\nCreate logical views\n\nBigtable Studio lets you create and save logical views of your\nBigtable tables. Logical view operations require permissions\nbeyond those granted in `roles/bigtable.reader`. For details, see the\ndocumentation for each view type.\n\nAuthorized views\n\nYou can use the query builder to create and save [authorized\nviews](/bigtable/docs/authorized-views), which are table subsets that you grant\naccess to separately from access to the table. You can also grant access and\ndelete authorized views in Bigtable Studio, using the **Action**\nmenu in the explorer.\n\nFor more information, see [Create and manage authorized\nviews](/bigtable/docs/authorized-views-create-manage).\n\nContinuous materialized views\n| **Preview**\n|\n|\n| This product or feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA products and features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nYou can use the query editor to create a continuous materialized view, a\nprecomputed result of a continuously running SQL query that synchronizes with\nits source table with incremental updates. Continuous materialized views often\ncontain aggregated data based on values in their source tables.\n\nFor more information, see the following documentation:\n\n- [Continuous materialized views](/bigtable/docs/continuous-materialized-views)\n- [Create and manage continuous materialized views](/bigtable/docs/manage-continuous-materialized-views)\n- [Continuous materialized view queries](/bigtable/docs/continuous-materialized-view-queries)\n\nLogical views\n\nYou can also use the query editor to create a logical view, a saved query that\ncan be queried like a table. For more information, see [Create and manage\nviews](/bigtable/docs/create-manage-views).\n\nWhat's next\n\n- [Learn additional ways to use SQL with Bigtable.](/bigtable/docs/introduction-sql)\n- [Work through a quickstart using the\n `cbt` CLI\n .](/bigtable/docs/create-instance-write-data-cbt-cli)"]]
