Buka VS Code, lalu di panel aktivitas, klik Extensions.
Dengan menggunakan kotak penelusuran, temukan ekstensi Jupyter, lalu klik
Install. Fitur BigQuery di VS Code memerlukan ekstensi Jupyter dari Microsoft sebagai dependensi.
Menginstal Google Cloud ekstensi
Buka VS Code, lalu di panel aktivitas, klik Extensions.
Menggunakan kotak penelusuran, temukan ekstensi Google Cloud Code, lalu
klik Install.
Jika diminta, mulai ulang VS Code.
Ikon Google Cloud Code kini terlihat di panel aktivitas.
Mengonfigurasi ekstensi
Buka VS Code, lalu di panel aktivitas, klik Google Cloud Code.
Buka bagian BigQuery Notebooks.
Klik Login ke Google Cloud. Anda akan dialihkan untuk login dengan kredensial Anda.
Gunakan panel tugas aplikasi tingkat teratas untuk membuka
Code > Settings > Settings > Extensions.
Temukan Google Cloud Code, lalu klik ikon Kelola untuk membuka menu.
Pilih Setelan.
Untuk setelan Cloud Code: Project, masukkan nama
Google Cloud project yang ingin Anda gunakan untuk menjalankan notebook dan
menampilkan set data BigQuery.
Untuk setelan Cloud Code > Beta: BigQuery Region, masukkan
lokasi BigQuery.
Ekstensi menampilkan set data dari lokasi ini.
Mengembangkan notebook BigQuery
Buka VS Code, lalu di panel aktivitas, klik Google Cloud Code.
Buka bagian BigQuery Notebooks, lalu klik BigQuery Notebook. File .ipynb baru yang berisi kode contoh akan dibuat dan dibuka di editor.
Di notebook baru, klik Select Kernel, lalu pilih kernel Python.
Notebook BigQuery memerlukan kernel Python lokal untuk
eksekusi. Anda dapat membuat lingkungan virtual baru atau menggunakan salah satu lingkungan virtual yang sudah ada.
Jika belum diinstal di lingkungan virtual Anda, instal pustaka klien
bigframes:
Buka jendela Terminal.
Jalankan perintah pip install bigframes.
Sekarang Anda dapat menulis dan menjalankan kode di notebook BigQuery.
Menjelajahi dan melihat pratinjau set data BigQuery
Buka VS Code, lalu di panel aktivitas, klik Google Cloud Code.
Untuk melihat set data dan tabel dari project dan region yang Anda tentukan, buka bagian
Set Data BigQuery. Set data publik BigQuery juga terlihat.
Untuk membuka tab baru di editor, klik nama tabel. Tab ini berisi
detail tabel, skema, dan pratinjau.
Harga
Ekstensi Visual Studio Code tidak dikenai biaya, tetapi Anda akan ditagih untuk setiap
Google Cloud layanan (BigQuery, Dataproc, Cloud Storage) yang Anda gunakan.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-08-17 UTC."],[[["\u003cp\u003eThe Google Cloud extension for Visual Studio Code allows users to develop and execute BigQuery notebooks, as well as browse, inspect, and preview BigQuery datasets directly within VS Code.\u003c/p\u003e\n"],["\u003cp\u003eBefore using the extension, you must ensure Python 3.11 or later is installed, install the Google Cloud CLI, initialize the gcloud CLI, configure a default project, set up Application Default Credentials, download VS Code, and install the Jupyter extension.\u003c/p\u003e\n"],["\u003cp\u003eInstalling the Google Cloud Code extension in VS Code is necessary to access its features, including the BigQuery Notebooks and BigQuery Datasets sections.\u003c/p\u003e\n"],["\u003cp\u003eTo develop BigQuery notebooks, users must select a Python kernel, and the \u003ccode\u003ebigframes\u003c/code\u003e client library should be installed in their virtual environment.\u003c/p\u003e\n"],["\u003cp\u003eThe Visual Studio Code extension itself is free, however, usage of Google Cloud services like BigQuery will incur charges.\u003c/p\u003e\n"]]],[],null,["# Use the Google Cloud for Visual Studio Code extension\n=====================================================\n\n|\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| **Note:** To provide feedback or ask questions that are related to this Preview feature, contact [bigquery-ide-plugin@google.com](mailto:bigquery-ide-plugin@google.com).\n\nThe Google Cloud [Visual Studio Code (VS Code)](https://code.visualstudio.com/)\nextension lets you do the following in VS Code:\n\n- Develop and execute BigQuery notebooks.\n- Browse, inspect, and preview BigQuery datasets.\n\nBefore you begin\n----------------\n\n1. In your local terminal, check to make sure you have\n [Python 3.11](https://www.python.org/downloads/) or later installed on your\n system:\n\n ```bash\n python3 --version\n ```\n2. [Install the Google Cloud CLI](/sdk/docs/install).\n\n3. In your local terminal,\n [initialize the gcloud CLI](/sdk/docs/initializing):\n\n ```bash\n gcloud init\n ```\n4. Configure a default project:\n\n ```bash\n gcloud config set project PROJECT_ID\n ```\n\n Replace \u003cvar translate=\"no\"\u003e\u003ccode translate=\"no\" dir=\"ltr\"\u003ePROJECT_ID\u003c/code\u003e\u003c/var\u003e with your default project.\n5. Set up [Application Default Credentials](/bigquery/docs/authentication):\n\n ```bash\n gcloud auth application-default login\n ```\n6. [Download and install VS Code](https://code.visualstudio.com/download).\n\n7. Open VS Code, and then in the activity bar, click **Extensions**.\n\n8. Using the search bar, find the **Jupyter** extension, and then click\n **Install**. The BigQuery features in VS Code require the\n Jupyter extension by Microsoft as a dependency.\n\nInstall the Google Cloud extension\n----------------------------------\n\n1. Open VS Code, and then in the activity bar, click **Extensions**.\n2. Using the search bar, find the **Google Cloud Code** extension, and then\n click **Install**.\n\n3. If prompted, restart VS Code.\n\nThe **Google Cloud Code** icon is now visible in the activity bar.\n\nConfigure the extension\n-----------------------\n\n1. Open VS Code, and then in the activity bar, click **Google Cloud Code**.\n2. Open the **BigQuery Notebooks** section.\n3. Click **Login to Google Cloud**. You are redirected to sign in with your credentials.\n4. Use the top-level application taskbar to navigate to **Code \\\u003e Settings \\\u003e Settings \\\u003e Extensions**.\n5. Find **Google Cloud Code** , and click the **Manage** icon to open the menu.\n6. Select **Settings**.\n7. For the **Cloud Code: Project** setting, enter the name of the Google Cloud project that you want to use to execute notebooks and display BigQuery datasets.\n8. For the **Cloud Code \\\u003e Beta: BigQuery Region** setting, enter a [BigQuery location](/bigquery/docs/locations#supported_locations). The extension displays datasets from this location.\n\nDevelop BigQuery notebooks\n--------------------------\n\n1. Open VS Code, and then in the activity bar, click **Google Cloud Code**.\n2. Open the **BigQuery Notebooks** section, and click **BigQuery Notebook** . A new `.ipynb` file containing sample code is created and opened in the editor.\n3. In the new notebook, click **Select Kernel**, and select a Python kernel.\n BigQuery notebooks require a local Python kernel for\n execution. You can create a new virtual environment or use one of the\n existing ones.\n\n4. If it hasn't already been installed in your virtual environment, install the\n `bigframes` client library:\n\n 1. Open the **Terminal** window.\n 2. Run the `pip install bigframes` command.\n\nYou can now write and execute code in your BigQuery notebook.\n\nExplore and preview BigQuery datasets\n-------------------------------------\n\n1. Open VS Code, and then in the activity bar, click **Google Cloud Code**.\n2. To see datasets and tables from your specified project and region, open the **BigQuery Datasets** section. BigQuery public datasets are also visible.\n3. To open a new tab in the editor, click any table name. This tab contains the table details, schema, and preview.\n\nPricing\n-------\n\nThe Visual Studio Code extension is free, but you are charged for any\nGoogle Cloud services (BigQuery, Dataproc,\nCloud Storage) that you use.\n\nWhat's next\n-----------\n\n- Learn more about [notebooks in BigQuery](/bigquery/docs/programmatic-analysis).\n- Learn more about [BigQuery DataFrames](/bigquery/docs/bigquery-dataframes-introduction)."]]
