Créer une vue autorisée

Créez une vue autorisée à l'aide des données publiques GitHub.

En savoir plus

Pour obtenir une documentation détaillée incluant cet exemple de code, consultez les articles suivants :

Exemple de code

Java

Avant d'essayer cet exemple, suivez les instructions de configuration pour Java du guide de démarrage rapide de BigQuery : Utiliser les bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API BigQuery pour Java.

Pour vous authentifier auprès de BigQuery, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour les bibliothèques clientes. 

// 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

Avant d'essayer cet exemple, suivez les instructions de configuration pour Python du guide de démarrage rapide de BigQuery : Utiliser les bibliothèques clientes. Pour en savoir plus, consultez la documentation de référence de l'API BigQuery pour Python.

Pour vous authentifier auprès de BigQuery, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez la page Configurer l'authentification pour les bibliothèques clientes. 

# 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

Pour savoir comment appliquer ou supprimer une configuration Terraform, consultez la page Commandes Terraform de base. Pour en savoir plus, consultez la documentation de référence du fournisseur 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
}

Étapes suivantes

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