Mengelola set data

Beta

Produk ini tunduk pada "Persyaratan Penawaran Pra-GA" di bagian Persyaratan Layanan Umum di Persyaratan Khusus Layanan. Produk pra-GA tersedia "sebagaimana adanya" dan mungkin memiliki dukungan terbatas. Untuk mengetahui informasi selengkapnya, lihat deskripsi tahap peluncuran.

Halaman ini menjelaskan cara menghapus dan mendapatkan informasi tentang {i>dataset<i} Anda.

Untuk mengetahui informasi tentang cara membuat set data dan mengimpor data ke dalamnya, lihat Membuat set data dan mengimpor data.

Sebelum memulai

Sebelum dapat menggunakan AutoML Tables, Anda harus menyiapkan project seperti yang dijelaskan dalam Sebelum memulai.

Membuat daftar set data

Project dapat mencakup banyak set data. Bagian ini menjelaskan cara mengambil daftar set data yang tersedia untuk sebuah project.

Konsol

Untuk melihat daftar set data yang tersedia menggunakan AutoML Tables UI, klik link Datasets di bagian atas menu navigasi sebelah kiri dan pilih Region.

REST

Untuk membuat daftar set data, gunakan metode datasets.list.

Sebelum menggunakan salah satu data permintaan, lakukan penggantian berikut:

• endpoint: automl.googleapis.com untuk lokasi global, dan eu-automl.googleapis.com untuk region Uni Eropa.
• project-id: Project ID Google Cloud Anda.
• location: lokasi untuk resource: us-central1 untuk Global atau eu untuk Uni Eropa.

Metode HTTP dan URL:

GET https://endpoint/v1beta1/projects/project-id/locations/location/datasets

Untuk mengirim permintaan Anda, pilih salah satu opsi berikut:

curl

Jalankan perintah berikut:

curl -X GET \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    -H "x-goog-user-project: project-id" \
    "https://endpoint/v1beta1/projects/project-id/locations/location/datasets"

PowerShell

Jalankan perintah berikut:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "project-id" }

Invoke-WebRequest `
    -Method GET `
    -Headers $headers `
    -Uri "https://endpoint/v1beta1/projects/project-id/locations/location/datasets" | Select-Object -Expand Content

Anda akan melihat respons JSON seperti berikut:

{
      "name": "projects/29434381/locations/us-central1/datasets/TBL75559",
      "displayName": "test_dataset",
      "createTime": "2019-03-21T00:50:20.660378Z",
      "updateTime": "2019-08-23T19:32:52.025469Z",
      "etag": "AB3BwFoV4USmhM3pT8c6Y5AIA6n51dAmSuObc=",
      "exampleCount": 94356,
      "tablesDatasetMetadata": {
        "primaryTableSpecId": "16930321664",
        "targetColumnSpecId": "46579780096",
        "areStatsFresh": true,
        "targetColumnCorrelations": {
          "6788648672679690240": {
            "cramersV": 0.16511808788616378
          },
          "87292427152392192": {
            "cramersV": 0.20327159375043746
          },
          "2393135436366086144": {
            "cramersV": 0.15513206308654948
          },
          "9094491681893384192": {
            "cramersV": 0.021499396246101456
          },
          "7004821454793474048": {
            "cramersV": 0.030097587339321379
          }
        },
        "statsUpdateTime": "2019-08-16T01:43:38.583Z",
        "tablesDatasetType": "BASIC"
      }
    },
...

Java

Jika resource Anda berada di region Uni Eropa, Anda harus menetapkan endpoint secara eksplisit. Pelajari lebih lanjut.

import com.google.cloud.automl.v1beta1.AutoMlClient;
import com.google.cloud.automl.v1beta1.Dataset;
import com.google.cloud.automl.v1beta1.ListDatasetsRequest;
import com.google.cloud.automl.v1beta1.LocationName;
import java.io.IOException;

class ListDatasets {

  static void listDatasets() throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "YOUR_PROJECT_ID";
    listDatasets(projectId);
  }

  // List the datasets
  static void listDatasets(String projectId) throws IOException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
      // A resource that represents Google Cloud Platform location.
      LocationName projectLocation = LocationName.of(projectId, "us-central1");
      ListDatasetsRequest request =
          ListDatasetsRequest.newBuilder().setParent(projectLocation.toString()).build();

      // List all the datasets available in the region by applying filter.
      System.out.println("List of datasets:");
      for (Dataset dataset : client.listDatasets(request).iterateAll()) {
        // Display the dataset information
        System.out.format("%nDataset name: %s%n", dataset.getName());
        // To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
        // required for other methods.
        // Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
        String[] names = dataset.getName().split("/");
        String retrievedDatasetId = names[names.length - 1];
        System.out.format("Dataset id: %s%n", retrievedDatasetId);
        System.out.format("Dataset display name: %s%n", dataset.getDisplayName());
        System.out.println("Dataset create time:");
        System.out.format("\tseconds: %s%n", dataset.getCreateTime().getSeconds());
        System.out.format("\tnanos: %s%n", dataset.getCreateTime().getNanos());

        System.out.format("Tables dataset metadata: %s%n", dataset.getTablesDatasetMetadata());

      }
    }
  }
}

Node.js

Jika resource Anda berada di region Uni Eropa, Anda harus menetapkan endpoint secara eksplisit. Pelajari lebih lanjut.

const automl = require('@google-cloud/automl');
const util = require('util');
const client = new automl.v1beta1.AutoMlClient();

/**
 * Demonstrates using the AutoML client to list all datasets.
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = '[PROJECT_ID]' e.g., "my-gcloud-project";
// const computeRegion = '[REGION_NAME]' e.g., "us-central1";
// const filter = '[FILTER_EXPRESSIONS]' e.g., "tablesDatasetMetadata:*";

// A resource that represents Google Cloud Platform location.
const projectLocation = client.locationPath(projectId, computeRegion);

// List all the datasets available in the region by applying filter.
client
  .listDatasets({parent: projectLocation, filter: filter})
  .then(responses => {
    const dataset = responses[0];

    // Display the dataset information.
    console.log('List of datasets:');
    for (let i = 0; i < dataset.length; i++) {
      const tablesDatasetMetadata = dataset[i].tablesDatasetMetadata;

      console.log(`Dataset name: ${dataset[i].name}`);
      console.log(`Dataset Id: ${dataset[i].name.split('/').pop(-1)}`);
      console.log(`Dataset display name: ${dataset[i].displayName}`);
      console.log(`Dataset example count: ${dataset[i].exampleCount}`);
      console.log('Tables dataset metadata:');
      console.log(
        `\tTarget column correlations: ${util.inspect(
          tablesDatasetMetadata.targetColumnCorrelations,
          false,
          null
        )}`
      );
      console.log(
        `\tPrimary table spec Id: ${tablesDatasetMetadata.primaryTableSpecId}`
      );
      console.log(
        `\tTarget column spec Id: ${tablesDatasetMetadata.targetColumnSpecId}`
      );
      console.log(
        `\tWeight column spec Id: ${tablesDatasetMetadata.weightColumnSpecId}`
      );
      console.log(
        `\tMl use column spec Id: ${tablesDatasetMetadata.mlUseColumnSpecId}`
      );
    }
  })
  .catch(err => {
    console.error(err);
  });

Python

Library klien untuk AutoML Tables menyertakan metode Python tambahan yang menyederhanakan penggunaan AutoML Tables API. Metode ini merujuk pada set data dan model berdasarkan nama, bukan ID. Nama set data dan model Anda harus unik. Untuk mengetahui informasi selengkapnya, lihat Referensi klien.

Jika resource Anda berada di region Uni Eropa, Anda harus menetapkan endpoint secara eksplisit. Pelajari lebih lanjut.

# TODO(developer): Uncomment and set the following variables
# project_id = 'PROJECT_ID_HERE'
# compute_region = 'COMPUTE_REGION_HERE'
# filter = 'filter expression here'

from google.cloud import automl_v1beta1 as automl

client = automl.TablesClient(project=project_id, region=compute_region)

# List all the datasets available in the region by applying filter.
response = client.list_datasets(filter=filter)

print("List of datasets:")
for dataset in response:
    # Display the dataset information.
    print(f"Dataset name: {dataset.name}")
    print("Dataset id: {}".format(dataset.name.split("/")[-1]))
    print(f"Dataset display name: {dataset.display_name}")
    metadata = dataset.tables_dataset_metadata
    print(
        "Dataset primary table spec id: {}".format(metadata.primary_table_spec_id)
    )
    print(
        "Dataset target column spec id: {}".format(metadata.target_column_spec_id)
    )
    print(
        "Dataset target column spec id: {}".format(metadata.target_column_spec_id)
    )
    print(
        "Dataset weight column spec id: {}".format(metadata.weight_column_spec_id)
    )
    print(
        "Dataset ml use column spec id: {}".format(metadata.ml_use_column_spec_id)
    )
    print(f"Dataset example count: {dataset.example_count}")
    print(f"Dataset create time: {dataset.create_time}")
    print("\n")

Menghapus set data

Menghapus set data akan menghapus set data secara permanen dari project Anda. Operasi ini tidak menghapus model apa pun yang dibuat dari set data tersebut. Jika ingin menghapus model, Anda harus menghapusnya secara eksplisit.

Konsol

1. Di AutoML Tables UI, klik link Datasets di bagian atas menu navigasi sebelah kiri dan pilih Region untuk menampilkan daftar set data yang tersedia.

2. Klik menu tindakan lainnya di ujung kanan baris yang ingin Anda hapus, lalu pilih Delete set data.

   

3. Klik Konfirmasi di kotak dialog konfirmasi.

REST

Untuk menghapus set data, gunakan metode datasets.delete.

Sebelum menggunakan salah satu data permintaan, lakukan penggantian berikut:

• endpoint: automl.googleapis.com untuk lokasi global, dan eu-automl.googleapis.com untuk region Uni Eropa.
• project-id: Project ID Google Cloud Anda.
• location: lokasi untuk resource: us-central1 untuk Global atau eu untuk Uni Eropa.
• dataset-id: ID set data yang ingin Anda hapus. Misalnya, TBL6543.

Metode HTTP dan URL:

DELETE https://endpoint/v1beta1/projects/project-id/locations/location/datasets/dataset-id

Untuk mengirim permintaan Anda, pilih salah satu opsi berikut:

curl

Jalankan perintah berikut:

curl -X DELETE \
    -H "Authorization: Bearer $(gcloud auth print-access-token)" \
    -H "x-goog-user-project: project-id" \
    "https://endpoint/v1beta1/projects/project-id/locations/location/datasets/dataset-id"

PowerShell

Jalankan perintah berikut:

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred"; "x-goog-user-project" = "project-id" }

Invoke-WebRequest `
    -Method DELETE `
    -Headers $headers `
    -Uri "https://endpoint/v1beta1/projects/project-id/locations/location/datasets/dataset-id" | Select-Object -Expand Content

Anda akan melihat respons JSON seperti berikut:

{
  "name": "projects/29452381/locations/us-central1/operations/TBL6543",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.automl.v1beta1.OperationMetadata",
    "createTime": "2019-12-26T17:19:50.684850Z",
    "updateTime": "2019-12-26T17:19:50.684850Z",
    "deleteDetails": {},
    "worksOn": [
      "projects/29452381/locations/us-central1/datasets/TBL6543"
    ],
    "state": "DONE"
  },
  "done": true,
  "response": {
    "@type": "type.googleapis.com/google.protobuf.Empty"
  }
}

Menghapus set data adalah operasi yang berjalan lama. Anda dapat memeriksa status operasi atau menunggu operasi ditampilkan. Pelajari lebih lanjut.

Java

Jika resource Anda berada di region Uni Eropa, Anda harus menetapkan endpoint secara eksplisit. Pelajari lebih lanjut.

import com.google.cloud.automl.v1beta1.AutoMlClient;
import com.google.cloud.automl.v1beta1.DatasetName;
import com.google.protobuf.Empty;
import java.io.IOException;
import java.util.concurrent.ExecutionException;

class DeleteDataset {

  static void deleteDataset() throws IOException, ExecutionException, InterruptedException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "YOUR_PROJECT_ID";
    String datasetId = "YOUR_DATASET_ID";
    deleteDataset(projectId, datasetId);
  }

  // Delete a dataset
  static void deleteDataset(String projectId, String datasetId)
      throws IOException, ExecutionException, InterruptedException {
    // Initialize client that will be used to send requests. This client only needs to be created
    // once, and can be reused for multiple requests. After completing all of your requests, call
    // the "close" method on the client to safely clean up any remaining background resources.
    try (AutoMlClient client = AutoMlClient.create()) {
      // Get the full path of the dataset.
      DatasetName datasetFullId = DatasetName.of(projectId, "us-central1", datasetId);
      Empty response = client.deleteDatasetAsync(datasetFullId).get();
      System.out.format("Dataset deleted. %s%n", response);
    }
  }
}

Node.js

Jika resource Anda berada di region Uni Eropa, Anda harus menetapkan endpoint secara eksplisit. Pelajari lebih lanjut.

const automl = require('@google-cloud/automl');
const client = new automl.v1beta1.AutoMlClient();

/**
 * Demonstrates using the AutoML client to delete a dataset.
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = '[PROJECT_ID]' e.g., "my-gcloud-project";
// const computeRegion = '[REGION_NAME]' e.g., "us-central1";
// const datasetId = '[DATASET_ID]' e.g., "TBL2246891593778855936";

// Get the full path of the dataset.
const datasetFullId = client.datasetPath(projectId, computeRegion, datasetId);

// Delete a dataset.
client
  .deleteDataset({name: datasetFullId})
  .then(responses => {
    const operation = responses[0];
    return operation.promise();
  })
  .then(responses => {
    // The final result of the operation.
    const operationDetails = responses[2];

    // Get the dataset delete details.
    console.log('Dataset delete details:');
    console.log('\tOperation details:');
    console.log(`\t\tName: ${operationDetails.name}`);
    console.log(`\t\tDone: ${operationDetails.done}`);
  })
  .catch(err => {
    console.error(err);
  });

Python

Library klien untuk AutoML Tables menyertakan metode Python tambahan yang menyederhanakan penggunaan AutoML Tables API. Metode ini merujuk pada set data dan model berdasarkan nama, bukan ID. Nama set data dan model Anda harus unik. Untuk mengetahui informasi selengkapnya, lihat Referensi klien.

Jika resource Anda berada di region Uni Eropa, Anda harus menetapkan endpoint secara eksplisit. Pelajari lebih lanjut.

# TODO(developer): Uncomment and set the following variables
# project_id = 'PROJECT_ID_HERE'
# compute_region = 'COMPUTE_REGION_HERE'
# dataset_display_name = 'DATASET_DISPLAY_NAME_HERE

from google.cloud import automl_v1beta1 as automl

client = automl.TablesClient(project=project_id, region=compute_region)

# Delete a dataset.
response = client.delete_dataset(dataset_display_name=dataset_display_name)

# synchronous check of operation status.
print(f"Dataset deleted. {response.result()}")

Langkah selanjutnya

• Buat model Anda.
• Pelajari jenis data lebih lanjut.