Autorisierte Ansicht erstellen

Autorisierte Ansicht mit öffentlichen GitHub-Daten erstellen

Weitere Informationen

Eine ausführliche Dokumentation, die dieses Codebeispiel enthält, finden Sie hier:

Codebeispiel

Java

Bevor Sie dieses Beispiel anwenden, folgen Sie den Schritten zur Einrichtung von Java in der BigQuery-Kurzanleitung zur Verwendung von Clientbibliotheken. Weitere Angaben finden Sie in der Referenzdokumentation zur BigQuery Java API.

Richten Sie zur Authentifizierung bei BigQuery die Standardanmeldedaten für Anwendungen ein. Weitere Informationen finden Sie unter Authentifizierung für Clientbibliotheken einrichten. 

// 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();

Python

Bevor Sie dieses Beispiel ausprobieren, folgen Sie der Python-Einrichtungsanleitung in der BigQuery-Kurzanleitung zur Verwendung von Clientbibliotheken. Weitere Angaben finden Sie in der Referenzdokumentation zur BigQuery Python API.

Richten Sie zur Authentifizierung bei BigQuery die Standardanmeldedaten für Anwendungen ein. Weitere Informationen finden Sie unter Authentifizierung für Clientbibliotheken einrichten. 

# 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

Informationen zum Anwenden oder Entfernen einer Terraform-Konfiguration finden Sie unter Grundlegende Terraform-Befehle. Weitere Informationen finden Sie in der Anbieterreferenzdokumentation zu Terraform. 

# 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
}

Nächste Schritte

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