Utiliser les clés de chiffrement gérées par le client

Cet exemple montre comment utiliser des clés de chiffrement gérées par le client, avec un pipeline Dataflow.

Exemple de code

Java

Pour vous authentifier auprès de Dataflow, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.

// Query from the NASA wildfires public dataset:
// https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=nasa_wildfire&t=past_week&page=table
String query =
    "SELECT latitude,longitude,acq_date,acq_time,bright_ti4,confidence "
    + "FROM `bigquery-public-data.nasa_wildfire.past_week` "
    + "LIMIT 10";

// Schema for the output BigQuery table.
final TableSchema outputSchema = new TableSchema().setFields(Arrays.asList(
    new TableFieldSchema().setName("latitude").setType("FLOAT"),
    new TableFieldSchema().setName("longitude").setType("FLOAT"),
    new TableFieldSchema().setName("acq_date").setType("DATE"),
    new TableFieldSchema().setName("acq_time").setType("TIME"),
    new TableFieldSchema().setName("bright_ti4").setType("FLOAT"),
    new TableFieldSchema().setName("confidence").setType("STRING")));

// Create the BigQuery options from the command line arguments.
BigQueryKmsKeyOptions options = PipelineOptionsFactory.fromArgs(args)
    .withValidation().as(BigQueryKmsKeyOptions.class);

// String outputBigQueryTable = "<project>:<dataset>.<table>";
String outputBigQueryTable = options.getOutputBigQueryTable();

// String kmsKey =
//    "projects/<project>/locations/<kms-location>/keyRings/<kms-keyring>/cryptoKeys/<kms-key>";
String kmsKey = options.getKmsKey();

// Create and run an Apache Beam pipeline.
Pipeline pipeline = Pipeline.create(options);
pipeline
    .apply("Read from BigQuery with KMS key",
        BigQueryIO.readTableRows()
            .fromQuery(query)
            .usingStandardSql()
            .withKmsKey(kmsKey))
    .apply("Write to BigQuery with KMS key",
        BigQueryIO.writeTableRows()
            .to(outputBigQueryTable)
            .withSchema(outputSchema)
            .withWriteDisposition(WriteDisposition.WRITE_TRUNCATE)
            .withKmsKey(kmsKey));
pipeline.run().waitUntilFinish();

Python

Pour vous authentifier auprès de Dataflow, configurez le service Identifiants par défaut de l'application. Pour en savoir plus, consultez Configurer l'authentification pour un environnement de développement local.

import apache_beam as beam

# output_bigquery_table = '<project>:<dataset>.<table>'
# kms_key = 'projects/<project>/locations/<kms-location>/keyRings/<kms-keyring>/cryptoKeys/<kms-key>' # noqa
# beam_args = [
#     '--project', 'your-project-id',
#     '--runner', 'DataflowRunner',
#     '--temp_location', 'gs://your-bucket/samples/dataflow/kms/tmp',
#     '--region', 'us-central1',
# ]

# Query from the NASA wildfires public dataset:
# https://console.cloud.google.com/bigquery?p=bigquery-public-data&d=nasa_wildfire&t=past_week&page=table
query = """
    SELECT latitude,longitude,acq_date,acq_time,bright_ti4,confidence
    FROM `bigquery-public-data.nasa_wildfire.past_week`
    LIMIT 10
"""

# Schema for the output BigQuery table.
schema = {
    "fields": [
        {"name": "latitude", "type": "FLOAT"},
        {"name": "longitude", "type": "FLOAT"},
        {"name": "acq_date", "type": "DATE"},
        {"name": "acq_time", "type": "TIME"},
        {"name": "bright_ti4", "type": "FLOAT"},
        {"name": "confidence", "type": "STRING"},
    ],
}

options = beam.options.pipeline_options.PipelineOptions(beam_args)
with beam.Pipeline(options=options) as pipeline:
    (
        pipeline
        | "Read from BigQuery with KMS key"
        >> beam.io.Read(
            beam.io.BigQuerySource(
                query=query,
                use_standard_sql=True,
                kms_key=kms_key,
            )
        )
        | "Write to BigQuery with KMS key"
        >> beam.io.WriteToBigQuery(
            output_bigquery_table,
            schema=schema,
            write_disposition=beam.io.BigQueryDisposition.WRITE_TRUNCATE,
            kms_key=kms_key,
        )
    )

Étape suivante

Pour rechercher et filtrer des exemples de code pour d'autres Google Cloud produits, consultez l'explorateur d'exemplesGoogle Cloud .