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Créer un workflow de migration

Crée un workflow de migration dans l'API BigQuery Migration. Un workflow de migration contient une liste de tâches secondaires qui sont exécutées pour migrer un entrepôt de données vers BigQuery.

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.

import com.google.api.gax.rpc.AlreadyExistsException;
import com.google.api.gax.rpc.ApiException;
import com.google.api.gax.rpc.InvalidArgumentException;
import com.google.cloud.bigquery.migration.v2.BigQueryDialect;
import com.google.cloud.bigquery.migration.v2.CreateMigrationWorkflowRequest;
import com.google.cloud.bigquery.migration.v2.Dialect;
import com.google.cloud.bigquery.migration.v2.LocationName;
import com.google.cloud.bigquery.migration.v2.MigrationServiceClient;
import com.google.cloud.bigquery.migration.v2.MigrationTask;
import com.google.cloud.bigquery.migration.v2.MigrationWorkflow;
import com.google.cloud.bigquery.migration.v2.TeradataDialect;
import com.google.cloud.bigquery.migration.v2.TranslationConfigDetails;
import java.io.IOException;
import java.util.Map;

public class CreateMigrationWorkflow {

  /**
   * Creates a Teradata SQL translation migration workflow to batch translate Teradata SQL scripts
   * and DDL into BigQuery-compatible SQL. The translation task reads input files from a Cloud
   * Storage source path and writes the converted output to a Cloud Storage target path.
   *
   * @param projectId The Google Cloud project ID (for example, "example-project-id").
   * @param location The geographic location of the migration workflow (for example, "us").
   * @param gcsSourcePath The Cloud Storage path for a directory of files to translate in a batch
   *     (for example, "gs://example-bucket/example-input-folder/").
   * @param gcsTargetPath The Cloud Storage path to write back the translated output files to (for
   *     example, "gs://example-bucket/example-output-folder/").
   */
  public static void createMigrationWorkflow(
      String projectId, String location, String gcsSourcePath, String gcsTargetPath) {
    LocationName parent = LocationName.of(projectId, location);

    Dialect sourceDialect =
        Dialect.newBuilder()
            .setTeradataDialect(
                TeradataDialect.newBuilder().setMode(TeradataDialect.Mode.SQL).build())
            .build();

    Dialect targetDialect =
        Dialect.newBuilder().setBigqueryDialect(BigQueryDialect.getDefaultInstance()).build();

    TranslationConfigDetails translationConfigDetails =
        TranslationConfigDetails.newBuilder()
            .setGcsSourcePath(gcsSourcePath)
            .setGcsTargetPath(gcsTargetPath)
            .setSourceDialect(sourceDialect)
            .setTargetDialect(targetDialect)
            .build();

    MigrationTask task =
        MigrationTask.newBuilder()
            .setType("Translation_Teradata2BQ")
            .setTranslationConfigDetails(translationConfigDetails)
            .build();

    MigrationWorkflow migrationWorkflow =
        MigrationWorkflow.newBuilder()
            .setDisplayName("Example Teradata to BigQuery Migration Workflow")
            .putTasks("translation-task", task)
            .build();

    CreateMigrationWorkflowRequest request =
        CreateMigrationWorkflowRequest.newBuilder()
            .setParent(parent.toString())
            .setMigrationWorkflow(migrationWorkflow)
            .build();

    try (MigrationServiceClient client = MigrationServiceClient.create()) {
      MigrationWorkflow response = client.createMigrationWorkflow(request);
      System.out.printf("Created migration workflow: %s%n", response.getName());
      System.out.printf("  Display Name: %s%n", response.getDisplayName());
      System.out.printf("  State: %s%n", response.getState());
      System.out.println("  Tasks:");
      for (Map.Entry<String, MigrationTask> entry : response.getTasksMap().entrySet()) {
        MigrationTask createdTask = entry.getValue();
        System.out.printf("    - %s:%n", entry.getKey());
        System.out.printf("        Type: %s%n", createdTask.getType());
        System.out.printf("        State: %s%n", createdTask.getState());
      }
    } catch (AlreadyExistsException err) {
      System.err.printf(
          "error: migration workflow already exists in location '%s' for project '%s': %s%n",
          location, projectId, err.getMessage());
    } catch (InvalidArgumentException err) {
      System.err.printf(
          "error: invalid argument creating migration workflow in location '%s' for project '%s': %s%n",
          location, projectId, err.getMessage());
    } catch (ApiException | IOException err) {
      System.err.printf(
          "error: failed to create migration workflow in location '%s' for project '%s': %s%n",
          location, projectId, err.getMessage());
    }
  }

Node.js

Avant d'essayer cet exemple, suivez les instructions de configuration pour Node.js 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 Node.js.

const {MigrationServiceClient} = require('@google-cloud/bigquery-migration').v2;
const {status} = require('@grpc/grpc-js');

const client = new MigrationServiceClient();

/**
 * Creates a migration workflow.
 *
 * Batch translate Teradata SQL scripts and DDL into BigQuery-compatible SQL.
 * It configures a translation task that reads input files from a
 * Google Cloud Storage source bucket and writes the converted output to a target bucket.
 *
 * @param {string} projectId The Google Cloud project ID (for example, 'example-project-id').
 * @param {string} location The Google Cloud location (for example, 'us').
 * @param {string} gcsSourcePath The Cloud Storage path for the source data (for example, 'gs://example-bucket/example-input-folder').
 * @param {string} gcsTargetPath The Cloud Storage path for the translated results (for example, 'gs://example-bucket/example-output-folder').
 */
async function createMigrationWorkflow(
  projectId,
  location,
  gcsSourcePath,
  gcsTargetPath,
) {
  const parent = client.locationPath(projectId, location);
  const migrationWorkflow = {
    displayName: 'Example BTEQ Migration Workflow',
    tasks: {
      'translation-task': {
        type: 'Translation_Teradata2BQ',
        translationConfigDetails: {
          gcsSourcePath,
          gcsTargetPath,
          sourceDialect: {
            teradataDialect: {
              mode: 'SQL',
            },
          },
          targetDialect: {
            bigqueryDialect: {},
          },
        },
      },
    },
  };

  const request = {
    parent,
    migrationWorkflow,
  };

  try {
    const [workflow] = await client.createMigrationWorkflow(request);
    console.log(`Created migration workflow: ${workflow.name}`);
    console.log(`  Display Name: ${workflow.displayName}`);
    console.log(`  State: ${workflow.state}`);
    console.log('  Tasks:');
    for (const taskName in workflow.tasks) {
      const task = workflow.tasks[taskName];
      console.log(`    - ${taskName}:`);
      console.log(`        Type: ${task.type}`);
      console.log(`        State: ${task.state}`);
    }
  } catch (err) {
    if (err.code === status.INVALID_ARGUMENT) {
      console.error(
        `Error: Invalid argument provided for creating Migration '${migrationWorkflow.displayName}'. ` +
          `Details: ${err.message}. Please check the request parameters and ensure they are valid.`,
      );
    } else {
      console.error('Error creating migration workflow:', err);
    }
  }
}

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.

from google.api_core import exceptions
from google.cloud import bigquery_migration_v2
from google.cloud.bigquery_migration_v2.types import (
    migration_entities,
    translation_config,
)


def create_migration_workflow(
    project_id: str, location: str, gcs_source_path: str, gcs_target_path: str
) -> None:
    """Creates a Teradata SQL translation workflow

    Creates a migration workflow to batch translate Teradata SQL scripts
    and DDL into BigQuery-compatible SQL. It configures a translation task
    that reads input files from a Google Cloud Storage source bucket and
    writes the converted output to a target bucket.

    Args:
        project_id: The Google Cloud project ID.
        location: The geographic location of the migration workflow (for example, us).
        gcs_source_path: The Cloud Storage path for a directory of files to
            translate in a batch (for example, gs://example-bucket/example-input-folder/).
        gcs_target_path: The Cloud Storage path to write back the corresponding
            input files to (for example, gs://example-bucket/example-output-folder/).
    """
    client = bigquery_migration_v2.MigrationServiceClient()

    parent = f"projects/{project_id}/locations/{location}"

    source_dialect = bigquery_migration_v2.Dialect()
    source_dialect.teradata_dialect = bigquery_migration_v2.TeradataDialect(
        mode=bigquery_migration_v2.TeradataDialect.Mode.SQL
    )
    target_dialect = bigquery_migration_v2.Dialect()
    target_dialect.bigquery_dialect = bigquery_migration_v2.BigQueryDialect()

    translation_config_details = bigquery_migration_v2.TranslationConfigDetails(
        gcs_source_path=gcs_source_path,
        gcs_target_path=gcs_target_path,
        source_dialect=source_dialect,
        target_dialect=target_dialect,
    )

    task = migration_entities.MigrationTask(
        type="Translation_Teradata2BQ",
        translation_config_details=translation_config_details,
    )

    workflow = migration_entities.MigrationWorkflow(
        display_name="Example Teradata to BigQuery Migration Workflow",
        tasks={"translation-task": task},
    )

    try:
        response = client.create_migration_workflow(
            parent=parent,
            migration_workflow=workflow,
        )
        print(f"Created migration workflow: {response.name}")
        print(f"Display name: {response.display_name}")
        print(f"State: {response.state.name}")
    except exceptions.AlreadyExists as e:
        print(f"Migration workflow already exists: {e}")

Étapes suivantes

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

Créer un workflow de migration Restez organisé à l'aide des collections Enregistrez et classez les contenus selon vos préférences.