Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Resource BatchPredictionJob memungkinkan Anda menjalankan permintaan prediksi
asinkron. Minta prediksi batch langsung dari resource
model. Anda tidak perlu men-deploy model ke endpoint. Untuk jenis data
yang mendukung prediksi batch dan online, Anda dapat menggunakan prediksi batch.
Ini berguna jika Anda tidak memerlukan respons langsung dan ingin memproses
data yang terakumulasi menggunakan satu permintaan.
Untuk membuat prediksi batch, tentukan sumber input dan lokasi output
agar Vertex AI dapat menyimpan hasil prediksi. Input dan output
bergantung pada jenis model yang Anda gunakan. Misalnya, prediksi batch untuk jenis model gambar AutoML memerlukan file JSON Lines input dan nama bucket Cloud Storage untuk menyimpan output.
Untuk informasi lebih lanjut tentang prediksi batch,
lihat Mendapatkan prediksi batch.
Anda dapat menggunakan komponen ModelBatchPredictOp untuk mengakses resource ini melalui Vertex AI Pipelines.
[[["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 2025-08-19 UTC."],[],[],null,["# Batch prediction components\n\n| To learn more,\n| run the \"Learn how to use prebuilt Pipeline Components to train a custom model\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/custom_model_training_and_batch_prediction.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fpipelines%2Fcustom_model_training_and_batch_prediction.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fpipelines%2Fcustom_model_training_and_batch_prediction.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/custom_model_training_and_batch_prediction.ipynb)\n\nThe `BatchPredictionJob` resource lets you run an asynchronous\nprediction request. Request batch predictions directly from the `model`\nresource. You don't need to deploy the model to an `endpoint`. For data types\nthat support both batch and online predictions you can use batch predictions.\nThis is useful when you don't require an immediate response and want to process\naccumulated data by using a single request.\n\nTo make a batch prediction, specify an input source and an output location\nfor Vertex AI to store predictions results. The inputs and outputs\ndepend on the `model` type that you're working with. For example, batch\npredictions for the AutoML image model type require an input\n[JSON Lines](https://jsonlines.org/)\nfile and the name of a Cloud Storage bucket to store the output.\nFor more information about batch prediction, see\n[Get batch predictions](/vertex-ai/docs/predictions/batch-predictions).\n\nYou can use the [`ModelBatchPredictOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/batch_predict_job.html#v1.batch_predict_job.ModelBatchPredictOp) component to access this resource through Vertex AI Pipelines.\n\nAPI reference\n-------------\n\n- For component reference, see the [Google Cloud SDK reference for Batch prediction components](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/batch_predict_job.html).\n- For Vertex AI API reference, see the [`BatchPredictionJob` resource](/vertex-ai/docs/reference/rest/v1/projects.locations.batchPredictionJobs) page.\n\nTutorials\n---------\n\n- [Custom training with prebuilt Google Cloud Pipeline Components](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/custom_model_training_and_batch_prediction.ipynb)\n\n### Version history and release notes\n\nTo learn more about the version history and changes to the Google Cloud Pipeline Components SDK, see the [Google Cloud Pipeline Components SDK Release Notes](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/release.html).\n\n### Technical support contacts\n\nIf you have any questions, reach out to\n[kubeflow-pipelines-components@google.com](mailto: kubeflow-pipelines-components@google.com)."]]
