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코드 샘플

Java

이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 Java 설정 안내를 따르세요. 자세한 내용은 BigQuery Java API 참고 문서를 확인하세요.

BigQuery에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 클라이언트 라이브러리의 인증 설정을 참조하세요. 

// Create a source dataset to store your table.
final Dataset sourceDataset = bigquery.create(DatasetInfo.of(sourceDatasetId));
// Populate a source table
String tableQuery =
    "SELECT commit, author, committer, repo_name"
        + " FROM `bigquery-public-data.github_repos.commits`"
        + " LIMIT 1000";
QueryJobConfiguration queryConfig =
    QueryJobConfiguration.newBuilder(tableQuery)
        .setDestinationTable(TableId.of(sourceDatasetId, sourceTableId))
        .build();
bigquery.query(queryConfig);
// Create a separate dataset to store your view
Dataset sharedDataset = bigquery.create(DatasetInfo.of(sharedDatasetId));
// Create the view in the new dataset
String viewQuery =
    String.format(
        "SELECT commit, author.name as author, "
            + "committer.name as committer, repo_name FROM %s.%s.%s",
        projectId, sourceDatasetId, sourceTableId);
ViewDefinition viewDefinition = ViewDefinition.of(viewQuery);
Table view =
    bigquery.create(TableInfo.of(TableId.of(sharedDatasetId, sharedViewId), viewDefinition));
// Assign access controls to the dataset containing the view
List<Acl> viewAcl = new ArrayList<>(sharedDataset.getAcl());
viewAcl.add(Acl.of(new Acl.Group("example-analyst-group@google.com"), Acl.Role.READER));
sharedDataset.toBuilder().setAcl(viewAcl).build().update();
// Authorize the view to access the source dataset
List<Acl> srcAcl = new ArrayList<>(sourceDataset.getAcl());
srcAcl.add(Acl.of(new Acl.View(view.getTableId())));
sourceDataset.toBuilder().setAcl(srcAcl).build().update();

Node.js

이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 Node.js 설정 안내를 따르세요. 자세한 내용은 BigQuery Node.js API 참고 문서를 확인하세요.

BigQuery에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 클라이언트 라이브러리의 인증 설정을 참조하세요. 

async function authorizedViewTutorial() {
  const {BigQuery} = require('@google-cloud/bigquery');
  const bigquery = new BigQuery();

  /**
   * TODO(developer): Uncomment the following lines before running the sample.
   */
  // const projectId = "my_project_id";
  // const sourceDatasetId = "my_source_dataset";
  // const sourceTableId = "my_source_table";
  // const sharedDatasetId = "shared_views";
  // const sharedViewId = "my_view";

  // Make API request to create dataset
  const [sourceDataset] = await bigquery.createDataset(sourceDatasetId);
  console.log(`Source dataset ${sourceDataset.id} created.`);

  const destinationTable = sourceDataset.table(sourceTableId);

  const query = `SELECT commit, author, committer, repo_name
    FROM \`bigquery-public-data.github_repos.commits\`
    LIMIT 1000`;

  // For all options, see https://cloud.google.com/bigquery/docs/reference/v2/tables#resource
  const options = {
    query: query,
    destination: destinationTable,
  };

  // Make API request to populate a source table
  await bigquery.query(options);
  // Create a separate dataset to store your view

  // Make API request to create a new dataset
  const [sharedDataset] = await bigquery.createDataset(sharedDatasetId);

  console.log(`Dataset ${sharedDataset.id} created.`);
  // Create the view in the new dataset

  const viewQuery = `SELECT
  commit, author.name as author,
  committer.name as committer, repo_name
  FROM
  \`${projectId}.${sourceDatasetId}.${sourceTableId}\``;

  const viewOptions = {
    view: {query: viewQuery, useLegacySql: false},
  };

  // Make API request to create the view
  const [view] = await sharedDataset.createTable(sharedViewId, viewOptions);

  const viewId = view.metadata.id;
  console.log(`View ${viewId} created.`);
  // Assign access controls to the dataset containing the view

  // Note to user: This is a group email for testing purposes. Replace with
  // your own group email address when running this code.
  const analyst_group_email = 'example-analyst-group@google.com';

  const analystAccessEntry = {
    role: 'READER',
    groupByEmail: analyst_group_email,
  };

  // Make API request to retrieve dataset metadata
  const [sharedMetadata] = await sharedDataset.getMetadata();

  const sharedAccessEntries = sharedMetadata.access;
  sharedAccessEntries.push(analystAccessEntry);

  sharedMetadata.access = sharedAccessEntries;

  // Make API request to update dataset metadata
  const [updatedSharedMetadata] =
    await sharedDataset.setMetadata(sharedMetadata);

  console.log(`Dataset ${updatedSharedMetadata.id} updated.`);
  // Authorize the view to access the source dataset

  const viewReference = {
    projectId: projectId,
    datasetId: sharedDatasetId,
    tableId: sharedViewId,
  };

  const datasetAccessEntry = {view: viewReference};

  // Make API request to retrieve source dataset metadata
  const [sourceMetadata] = await sourceDataset.getMetadata();

  const sourceAccessEntries = sourceMetadata.access;
  sourceAccessEntries.push(datasetAccessEntry);

  sourceMetadata.access = sourceAccessEntries;

  // Make API request to update source dataset metadata
  const [updatedSourceMetadata] =
    await sourceDataset.setMetadata(sourceMetadata);

  console.log(`Dataset ${updatedSourceMetadata.id} updated.`);
}

Python

이 샘플을 사용해 보기 전에 BigQuery 빠른 시작: 클라이언트 라이브러리 사용의 Python 설정 안내를 따르세요. 자세한 내용은 BigQuery Python API 참고 문서를 확인하세요.

BigQuery에 인증하려면 애플리케이션 기본 사용자 인증 정보를 설정합니다. 자세한 내용은 클라이언트 라이브러리의 인증 설정을 참조하세요. 

# Create a source dataset
from google.cloud import bigquery
from google.cloud.bigquery.enums import EntityTypes

client = bigquery.Client()
source_dataset_id = "github_source_data"
source_dataset_id_full = "{}.{}".format(client.project, source_dataset_id)


source_dataset = bigquery.Dataset(source_dataset_id_full)
# Specify the geographic location where the dataset should reside.
source_dataset.location = "US"
source_dataset = client.create_dataset(source_dataset)  # API request

# Populate a source table
source_table_id = "github_contributors"
job_config = bigquery.QueryJobConfig()
job_config.destination = source_dataset.table(source_table_id)
sql = """
    SELECT commit, author, committer, repo_name
    FROM `bigquery-public-data.github_repos.commits`
    LIMIT 1000
"""
client.query_and_wait(
    sql,
    # Location must match that of the dataset(s) referenced in the query
    # and of the destination table.
    location="US",
    job_config=job_config,
)  # API request - starts the query and waits for query to finish

# Create a separate dataset to store your view
shared_dataset_id = "shared_views"
shared_dataset_id_full = "{}.{}".format(client.project, shared_dataset_id)


shared_dataset = bigquery.Dataset(shared_dataset_id_full)
shared_dataset.location = "US"
shared_dataset = client.create_dataset(shared_dataset)  # API request

# Create the view in the new dataset
shared_view_id = "github_analyst_view"
view = bigquery.Table(shared_dataset.table(shared_view_id))
sql_template = """
    SELECT
        commit, author.name as author,
        committer.name as committer, repo_name
    FROM
        `{}.{}.{}`
"""
view.view_query = sql_template.format(
    client.project, source_dataset_id, source_table_id
)
view = client.create_table(view)  # API request

# Assign access controls to the dataset containing the view
# analyst_group_email = 'data_analysts@example.com'
access_entries = shared_dataset.access_entries
access_entries.append(
    bigquery.AccessEntry("READER", EntityTypes.GROUP_BY_EMAIL, analyst_group_email)
)
shared_dataset.access_entries = access_entries
shared_dataset = client.update_dataset(
    shared_dataset, ["access_entries"]
)  # API request

# Authorize the view to access the source dataset
access_entries = source_dataset.access_entries
access_entries.append(
    bigquery.AccessEntry(None, EntityTypes.VIEW, view.reference.to_api_repr())
)
source_dataset.access_entries = access_entries
source_dataset = client.update_dataset(
    source_dataset, ["access_entries"]
)  # API request

Terraform

Terraform 구성을 적용하거나 삭제하는 방법은 기본 Terraform 명령어를 참조하세요. 자세한 내용은 Terraform 제공업체 참고 문서를 확인하세요. 

# Creates an authorized view.

# Create a dataset to contain the view.
resource "google_bigquery_dataset" "view_dataset" {
  dataset_id  = "view_dataset"
  description = "Dataset that contains the view"
  location    = "us-west1"
}

# Create the view to authorize.
resource "google_bigquery_table" "movie_view" {
  project     = google_bigquery_dataset.view_dataset.project
  dataset_id  = google_bigquery_dataset.view_dataset.dataset_id
  table_id    = "movie_view"
  description = "View to authorize"

  view {
    query          = "SELECT item_id, avg(rating) FROM `movie_project.movie_dataset.movie_ratings` GROUP BY item_id ORDER BY item_id;"
    use_legacy_sql = false
  }
}


# Authorize the view to access the dataset
# that the query data originates from.
resource "google_bigquery_dataset_access" "view_authorization" {
  project    = "movie_project"
  dataset_id = "movie_dataset"

  view {
    project_id = google_bigquery_table.movie_view.project
    dataset_id = google_bigquery_table.movie_view.dataset_id
    table_id   = google_bigquery_table.movie_view.table_id
  }
}

# Specify the IAM policy for principals that can access
# the authorized view. These users should already
# have the roles/bigqueryUser role at the project level.
data "google_iam_policy" "principals_policy" {
  binding {
    role = "roles/bigquery.dataViewer"
    members = [
      "group:example-group@example.com",
    ]
  }
}

# Set the IAM policy on the authorized  view.
resource "google_bigquery_table_iam_policy" "authorized_view_policy" {
  project     = google_bigquery_table.movie_view.project
  dataset_id  = google_bigquery_table.movie_view.dataset_id
  table_id    = google_bigquery_table.movie_view.table_id
  policy_data = data.google_iam_policy.principals_policy.policy_data
}

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