Crea un flujo de trabajo de migración

Crea un flujo de trabajo de migración en la API de BigQuery Migration. Un flujo de trabajo de migración contiene una lista de tareas secundarias que se ejecutan para migrar un almacén de datos a BigQuery.

Muestra de código

Java

Antes de probar este ejemplo, sigue las instrucciones de configuración para Java incluidas en la guía de inicio rápido de BigQuery sobre cómo usar bibliotecas cliente. Para obtener más información, consulta la documentación de referencia de la API de BigQuery para Java.

Para autenticarte en BigQuery, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para bibliotecas cliente.

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

Antes de probar este ejemplo, sigue las instrucciones de configuración para Node.js incluidas en la guía de inicio rápido de BigQuery sobre cómo usar bibliotecas cliente. Para obtener más información, consulta la documentación de referencia de la API de BigQuery para Node.js.

Para autenticarte en BigQuery, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para bibliotecas cliente.

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

Antes de probar este ejemplo, sigue las instrucciones de configuración para Python incluidas en la guía de inicio rápido de BigQuery sobre cómo usar bibliotecas cliente. Para obtener más información, consulta la documentación de referencia de la API de BigQuery para Python.

Para autenticarte en BigQuery, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para bibliotecas cliente.

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}")

¿Qué sigue?

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