Crie um fluxo de trabalho de migração

Cria um fluxo de trabalho de migração na API BigQuery Migration. Um fluxo de trabalho de migração contém uma lista de subtarefas que são executadas para migrar um armazém de dados para o BigQuery.

Exemplo de código

Node.js

Antes de experimentar este exemplo, siga as Node.jsinstruções de configuração no início rápido do BigQuery com bibliotecas cliente. Para mais informações, consulte a API Node.js BigQuery documentação de referência.

Para se autenticar no BigQuery, configure as Credenciais padrão da aplicação. Para mais informações, consulte o artigo Configure a autenticação para bibliotecas de 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 experimentar este exemplo, siga as Pythoninstruções de configuração no início rápido do BigQuery com bibliotecas cliente. Para mais informações, consulte a API Python BigQuery documentação de referência.

Para se autenticar no BigQuery, configure as Credenciais padrão da aplicação. Para mais informações, consulte o artigo Configure a autenticação para bibliotecas de 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}")

O que se segue?

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