Exportar elementos a BigQuery

Exporta un inventario de elementos a BigQuery

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Para obtener documentación en la que se incluye esta muestra de código, consulta lo siguiente:

Bibliotecas cliente de Cloud Asset Inventory

Muestra de código

Go

Para autenticarte en Cloud Asset Inventory, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para un entorno de desarrollo local.


// Sample asset-quickstart exports assets to given bigquery table.
package main

import (
	"context"
	"fmt"
	"log"
	"os"
	"strings"

	asset "cloud.google.com/go/asset/apiv1"
	"cloud.google.com/go/asset/apiv1/assetpb"
)

func main() {
	ctx := context.Background()
	projectID := os.Getenv("GOOGLE_CLOUD_PROJECT")
	client, err := asset.NewClient(ctx)
	if err != nil {
		log.Fatalf("asset.NewClient: %v", err)
	}
	defer client.Close()
	datasetID := strings.Replace(fmt.Sprintf("%s-for-assets", projectID), "-", "_", -1)
	dataset := fmt.Sprintf("projects/%s/datasets/%s", projectID, datasetID)
	req := &assetpb.ExportAssetsRequest{
		Parent: fmt.Sprintf("projects/%s", projectID),
		OutputConfig: &assetpb.OutputConfig{
			Destination: &assetpb.OutputConfig_BigqueryDestination{
				BigqueryDestination: &assetpb.BigQueryDestination{
					Dataset: dataset,
					Table:   "test",
					Force:   true,
				},
			},
		},
	}
	op, err := client.ExportAssets(ctx, req)
	if err != nil {
		log.Fatalf("ExportAssets: %v", err)
	}
	resp, err := op.Wait(ctx)
	if err != nil {
		log.Fatalf("Wait: %v", err)
	}
	fmt.Print(resp)
}

Java

// Imports the Google Cloud client library

import com.google.cloud.ServiceOptions;
import com.google.cloud.asset.v1.AssetServiceClient;
import com.google.cloud.asset.v1.BigQueryDestination;
import com.google.cloud.asset.v1.ContentType;
import com.google.cloud.asset.v1.ExportAssetsRequest;
import com.google.cloud.asset.v1.ExportAssetsRequest.Builder;
import com.google.cloud.asset.v1.ExportAssetsResponse;
import com.google.cloud.asset.v1.OutputConfig;
import com.google.cloud.asset.v1.PartitionSpec;
import com.google.cloud.asset.v1.ProjectName;
import java.io.IOException;
import java.util.Arrays;
import java.util.concurrent.ExecutionException;

public class ExportAssetsBigqueryExample {

  // Use the default project Id.
  private static final String projectId = ServiceOptions.getDefaultProjectId();

  /**
   * Export assets to BigQuery for a project.

   * @param bigqueryDataset which dataset the results will be exported to
   * @param bigqueryTable which table the results will be exported to
   * @param contentType determines the schema for the table
   * @param assetTypes a list of asset types to export. if empty, export all.
   * @param isPerType separate BigQuery tables for each resource type
   */
  public static void exportBigQuery(String bigqueryDataset, String bigqueryTable,
      ContentType contentType, String[] assetTypes, boolean isPerType)
      throws IOException, IllegalArgumentException, InterruptedException, ExecutionException {
    try (AssetServiceClient client = AssetServiceClient.create()) {
      ProjectName parent = ProjectName.of(projectId);
      OutputConfig outputConfig;
      // Outputs to per-type BigQuery table.
      if (isPerType) {
        outputConfig =
            OutputConfig.newBuilder()
                .setBigqueryDestination(
                    BigQueryDestination.newBuilder()
                        .setDataset(bigqueryDataset)
                        .setTable(bigqueryTable)
                        .setForce(true)
                        .setSeparateTablesPerAssetType(true)
                        .setPartitionSpec(
                            PartitionSpec.newBuilder()
                                .setPartitionKey(PartitionSpec.PartitionKey.READ_TIME)
                                .build())
                        .build())
                .build();
      } else {
        outputConfig =
            OutputConfig.newBuilder()
                .setBigqueryDestination(
                    BigQueryDestination.newBuilder()
                        .setDataset(bigqueryDataset)
                        .setTable(bigqueryTable)
                        .setForce(true)
                        .build())
                .build();
      }
      Builder exportAssetsRequestBuilder = ExportAssetsRequest.newBuilder()
          .setParent(parent.toString()).setContentType(contentType).setOutputConfig(outputConfig);
      if (assetTypes.length > 0) {
        exportAssetsRequestBuilder.addAllAssetTypes(Arrays.asList(assetTypes));
      }
      ExportAssetsRequest request = exportAssetsRequestBuilder.build();
      ExportAssetsResponse response = client.exportAssetsAsync(request).get();
      System.out.println(response);
    }
  }
}

Node.js

/**
 * TODO(developer): Uncomment these variables before running the sample.
 */
// const dataSet = 'projects/project_id/datasets/dataset_id';
// const table = 'mytable';

const {AssetServiceClient} = require('@google-cloud/asset');
const client = new AssetServiceClient();

async function exportAssetsBigquery() {
  const projectId = await client.getProjectId();
  const projectResource = client.projectPath(projectId);
  const dataset = dataSet;

  const request = {
    parent: projectResource,
    outputConfig: {
      bigqueryDestination: {
        dataset: `projects/${projectId}/${dataset}`,
        table: table,
        force: true,
      },
    },
  };

  // Handle the operation using the promise pattern.
  const [operation] = await client.exportAssets(request);

  // Operation#promise starts polling for the completion of the operation.
  const [result] = await operation.promise();

  // Do things with with the response.
  console.log(result);
}

exportAssetsBigquery();

Python

from google.cloud import asset_v1

# TODO project_id = 'Your Google Cloud Project ID'
# TODO dataset = 'Your BigQuery dataset path'
# TODO table = 'Your BigQuery table name'
# TODO content_type ="Content type to export"

client = asset_v1.AssetServiceClient()
parent = f"projects/{project_id}"
output_config = asset_v1.OutputConfig()
output_config.bigquery_destination.dataset = dataset
output_config.bigquery_destination.table = table
output_config.bigquery_destination.force = True
response = client.export_assets(
    request={
        "parent": parent,
        "content_type": content_type,
        "output_config": output_config,
    }
)
print(response.result())

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