관점 유형 나열

기존 측정기준 유형을 나열합니다.

코드 샘플

Java

이 샘플을 사용해 보기 전에 클라이언트 라이브러리 사용한 Dataplex 빠른 시작의 Java 설정 안내를 따르세요. 자세한 내용은 Dataplex Java API 참조 문서를 참고하세요.

Dataplex에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.

import com.google.cloud.dataplex.v1.AspectType;
import com.google.cloud.dataplex.v1.CatalogServiceClient;
import com.google.cloud.dataplex.v1.LocationName;
import com.google.common.collect.ImmutableList;
import java.io.IOException;
import java.util.List;

public class ListAspectTypes {

  public static void main(String[] args) throws IOException {
    // TODO(developer): Replace these variables before running the sample.
    String projectId = "MY_PROJECT_ID";
    // Available locations: https://cloud.google.com/dataplex/docs/locations
    String location = "MY_LOCATION";

    List<AspectType> aspectTypes = listAspectTypes(projectId, location);
    aspectTypes.forEach(
        aspectType -> System.out.println("Aspect type name: " + aspectType.getName()));
  }

  // Method to list Aspect Types located in projectId and location
  public static List<AspectType> listAspectTypes(String projectId, String location)
      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.
    try (CatalogServiceClient client = CatalogServiceClient.create()) {
      LocationName locationName = LocationName.of(projectId, location);
      CatalogServiceClient.ListAspectTypesPagedResponse listAspectTypesResponse =
          client.listAspectTypes(locationName);
      // Paging is implicitly handled by .iterateAll(), all results will be returned
      return ImmutableList.copyOf(listAspectTypesResponse.iterateAll());
    }
  }
}

Python

이 샘플을 사용해 보기 전에 클라이언트 라이브러리 사용한 Dataplex 빠른 시작의 Python 설정 안내를 따르세요. 자세한 내용은 Dataplex Python API 참조 문서를 참고하세요.

Dataplex에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 로컬 개발 환경의 인증 설정을 참조하세요.

from typing import List

from google.cloud import dataplex_v1


def list_aspect_types(project_id: str, location: str) -> List[dataplex_v1.AspectType]:
    """Method to list Aspect Types located in project_id and location"""

    # Initialize client that will be used to send requests across threads. This
    # client only needs to be created once, and can be reused for multiple requests.
    # After completing all of your requests, call the "__exit__()" method to safely
    # clean up any remaining background resources. Alternatively, use the client as
    # a context manager.
    with dataplex_v1.CatalogServiceClient() as client:
        # The resource name of the Aspect Type location
        parent = f"projects/{project_id}/locations/{location}"
        results = client.list_aspect_types(parent=parent)
        return list(results)


if __name__ == "__main__":
    # TODO(developer): Replace these variables before running the sample.
    project_id = "MY_PROJECT_ID"
    # Available locations: https://cloud.google.com/dataplex/docs/locations
    location = "MY_LOCATION"

    aspect_types = list_aspect_types(project_id, location)
    for aspect_type in aspect_types:
        print(f"Aspect type name: {aspect_type.name}")

다음 단계

다른 Google Cloud 제품의 코드 샘플을 검색하고 필터링하려면 Google Cloud 샘플 브라우저를 참조하세요.