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Insertar, actualizar y eliminar datos con el lenguaje de manipulación de datos (DML)

En esta página se describe cómo insertar, actualizar y eliminar datos de Spanner mediante instrucciones del lenguaje de manipulación de datos (DML). Puedes ejecutar instrucciones de DML con las bibliotecas de cliente, la consolaGoogle Cloud y la herramienta de línea de comandos gcloud. Puedes ejecutar instrucciones de DML particionado mediante las bibliotecas de cliente y la herramienta de línea de comandos gcloud.

Para consultar la referencia completa de la sintaxis de DML, consulta la sintaxis del lenguaje de manipulación de datos de las bases de datos con dialecto GoogleSQL o el lenguaje de manipulación de datos de PostgreSQL de las bases de datos con dialecto PostgreSQL.

Usar DML

DML admite las instrucciones INSERT, UPDATE y DELETE en la consola, la CLI de Google Cloud y las bibliotecas de cliente.Google Cloud

Bloqueo

Ejecutas instrucciones DML dentro de transacciones de lectura y escritura. Cuando Spanner lee datos, adquiere bloqueos de lectura compartidos en partes limitadas de los intervalos de filas que lees. En concreto, adquiere estos bloqueos solo en las columnas a las que accedes. Los bloqueos pueden incluir datos que no cumplan la condición de filtro de la cláusula WHERE.

Cuando Spanner modifica datos mediante instrucciones DML, adquiere bloqueos exclusivos en los datos específicos que estás modificando. Además, adquiere bloqueos compartidos de la misma forma que cuando lees datos. Si tu solicitud incluye intervalos de filas grandes o una tabla completa, los bloqueos compartidos pueden impedir que otras transacciones avancen en paralelo.

Para modificar los datos de la forma más eficiente posible, utiliza una cláusula WHERE que permita a Spanner leer solo las filas necesarias. Puedes conseguir este objetivo con un filtro en la clave principal o en la clave de un índice secundario. La cláusula WHERE limita el ámbito de los bloqueos compartidos y permite que Spanner procese la actualización de forma más eficiente.

Por ejemplo, supongamos que uno de los músicos de la tabla Singers cambia su nombre y tienes que actualizarlo en tu base de datos. Podrías ejecutar la siguiente instrucción DML, pero obliga a Spanner a analizar toda la tabla y adquiere bloqueos compartidos que cubren toda la tabla. Por lo tanto, Spanner debe leer más datos de los necesarios y las transacciones simultáneas no pueden modificar los datos en paralelo:

-- ANTI-PATTERN: SENDING AN UPDATE WITHOUT THE PRIMARY KEY COLUMN
-- IN THE WHERE CLAUSE

UPDATE Singers SET FirstName = "Marcel"
WHERE FirstName = "Marc" AND LastName = "Richards";

Para que la actualización sea más eficiente, incluya la columna SingerId en la cláusula WHERE. La columna SingerId es la única columna de clave principal de la tabla Singers:

-- ANTI-PATTERN: SENDING AN UPDATE THAT MUST SCAN THE ENTIRE TABLE

UPDATE Singers SET FirstName = "Marcel"
WHERE FirstName = "Marc" AND LastName = "Richards"

Si no hay ningún índice en FirstName o LastName, debes analizar toda la tabla para encontrar a los cantantes objetivo. Si no quieres añadir un índice secundario para que la actualización sea más eficiente, incluye la columna SingerId en la cláusula WHERE.

La columna SingerId es la única columna de clave principal de la tabla Singers. Para encontrarlo, ejecuta SELECT en una transacción de solo lectura independiente antes de la transacción de actualización:


  SELECT SingerId
  FROM Singers
  WHERE FirstName = "Marc" AND LastName = "Richards"

  -- Recommended: Including a seekable filter in the where clause

  UPDATE Singers SET FirstName = "Marcel"
  WHERE SingerId = 1;

Simultaneidad

Spanner ejecuta secuencialmente todas las instrucciones SQL (SELECT, INSERT, UPDATE y DELETE) de una transacción. No se ejecutan simultáneamente. La única excepción es que Spanner puede ejecutar varias instrucciones SELECT simultáneamente, ya que son operaciones de solo lectura.

Límites de transacciones

Una transacción que incluye instrucciones de DML tiene los mismos límites que cualquier otra transacción. Si tienes que hacer cambios a gran escala, te recomendamos que uses DML particionado.

Si las instrucciones de DML de una transacción dan como resultado más de 80.000 mutaciones, la instrucción de DML que supere el límite de la transacción devolverá un error BadUsage con un mensaje sobre el número excesivo de mutaciones.
Si las instrucciones de DML de una transacción dan como resultado una transacción de más de 100 MiB, la instrucción de DML que supere el límite devolverá un error BadUsage con un mensaje sobre la transacción que supera el límite de tamaño.

Las mutaciones realizadas con DML no se devuelven al cliente. Se combinan en la solicitud de confirmación cuando se confirma y se tienen en cuenta para los límites de tamaño máximo. Aunque el tamaño de la solicitud de confirmación que envíes sea pequeño, es posible que la transacción supere el límite de tamaño permitido.

Ejecutar instrucciones en la consola Google Cloud

Sigue estos pasos para ejecutar una instrucción DML en la consolaGoogle Cloud .

Ve a la página Instancias de Spanner.

Ir a la página de instancias
Selecciona tu proyecto en la lista desplegable de la barra de herramientas.
Haga clic en el nombre de la instancia que contiene su base de datos para ir a la página Detalles de la instancia.
En la pestaña Resumen, haga clic en el nombre de su base de datos. Aparecerá la página Detalles de la base de datos.
Haz clic en Spanner Studio.
Introduce una instrucción DML. Por ejemplo, la siguiente instrucción añade una nueva fila a la tabla Singers.
```
INSERT Singers (SingerId, FirstName, LastName)
VALUES (1, 'Marc', 'Richards')
```
Haz clic en Realizar una consulta. La consola Google Cloud muestra el resultado.

Ejecutar instrucciones con Google Cloud CLI

Para ejecutar instrucciones DML, usa el comando gcloud spanner databases execute-sql. En el siguiente ejemplo se añade una fila a la tabla Singers.

gcloud spanner databases execute-sql example-db --instance=test-instance \
    --sql="INSERT Singers (SingerId, FirstName, LastName) VALUES (1, 'Marc', 'Richards')"

Modificar datos con la biblioteca de cliente

Para ejecutar instrucciones DML mediante la biblioteca de cliente, sigue estos pasos:

Crea una transacción de lectura y escritura.
Llama al método de la biblioteca de cliente para ejecutar DML y pasa la instrucción DML.
Usa el valor devuelto del método de ejecución de DML para obtener el número de filas insertadas, actualizadas o eliminadas.

En el siguiente ejemplo de código se inserta una nueva fila en la tabla Singers.

C++

Utiliza la función ExecuteDml() para ejecutar una instrucción DML.

void DmlStandardInsert(google::cloud::spanner::Client client) {
  using ::google::cloud::StatusOr;
  namespace spanner = ::google::cloud::spanner;
  std::int64_t rows_inserted;
  auto commit_result = client.Commit(
      [&client, &rows_inserted](
          spanner::Transaction txn) -> StatusOr<spanner::Mutations> {
        auto insert = client.ExecuteDml(
            std::move(txn),
            spanner::SqlStatement(
                "INSERT INTO Singers (SingerId, FirstName, LastName)"
                "  VALUES (10, 'Virginia', 'Watson')"));
        if (!insert) return std::move(insert).status();
        rows_inserted = insert->RowsModified();
        return spanner::Mutations{};
      });
  if (!commit_result) throw std::move(commit_result).status();
  std::cout << "Rows inserted: " << rows_inserted;
  std::cout << "Insert was successful [spanner_dml_standard_insert]\n";
}

C#

Utiliza el método ExecuteNonQueryAsync() para ejecutar una instrucción DML.


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class InsertUsingDmlCoreAsyncSample
{
    public async Task<int> InsertUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var cmd = connection.CreateDmlCommand("INSERT Singers (SingerId, FirstName, LastName) VALUES (10, 'Virginia', 'Watson')");
        int rowCount = await cmd.ExecuteNonQueryAsync();

        Console.WriteLine($"{rowCount} row(s) inserted...");
        return rowCount;
    }
}

Go

Utiliza el método Update() para ejecutar una instrucción DML.


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func insertUsingDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `INSERT Singers (SingerId, FirstName, LastName)
					VALUES (10, 'Virginia', 'Watson')`,
		}
		rowCount, err := txn.Update(ctx, stmt)
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "%d record(s) inserted.\n", rowCount)
		return nil
	})
	return err
}

Java

Utiliza el método executeUpdate() para ejecutar una instrucción DML.

static void insertUsingDml(DatabaseClient dbClient) {
  dbClient
      .readWriteTransaction()
      .run(transaction -> {
        String sql =
            "INSERT INTO Singers (SingerId, FirstName, LastName) "
                + " VALUES (10, 'Virginia', 'Watson')";
        long rowCount = transaction.executeUpdate(Statement.of(sql));
        System.out.printf("%d record inserted.\n", rowCount);
        return null;
      });
}

Node.js

Utiliza el método runUpdate() para ejecutar una instrucción DML.

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

database.runTransaction(async (err, transaction) => {
  if (err) {
    console.error(err);
    return;
  }
  try {
    const [rowCount] = await transaction.runUpdate({
      sql: 'INSERT Singers (SingerId, FirstName, LastName) VALUES (10, @firstName, @lastName)',
      params: {
        firstName: 'Virginia',
        lastName: 'Watson',
      },
    });

    console.log(
      `Successfully inserted ${rowCount} record into the Singers table.`,
    );

    await transaction.commit();
  } catch (err) {
    console.error('ERROR:', err);
  } finally {
    // Close the database when finished.
    database.close();
  }
});

PHP

Utiliza el método executeUpdate() para ejecutar una instrucción DML.

use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;

/**
 * Inserts sample data into the given database with a DML statement.
 *
 * The database and table must already exist and can be created using
 * `create_database`.
 * Example:
 * ```
 * insert_data($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function insert_data_with_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $database->runTransaction(function (Transaction $t) {
        $rowCount = $t->executeUpdate(
            'INSERT Singers (SingerId, FirstName, LastName) '
            . " VALUES (10, 'Virginia', 'Watson')");
        $t->commit();
        printf('Inserted %d row(s).' . PHP_EOL, $rowCount);
    });
}

Python

Utiliza el método execute_update() para ejecutar una instrucción DML.

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

def insert_singers(transaction):
    row_ct = transaction.execute_update(
        "INSERT INTO Singers (SingerId, FirstName, LastName) "
        " VALUES (10, 'Virginia', 'Watson')"
    )

    print("{} record(s) inserted.".format(row_ct))

database.run_in_transaction(insert_singers)

Ruby

Utiliza el método execute_update() para ejecutar una instrucción DML.

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner   = Google::Cloud::Spanner.new project: project_id
client    = spanner.client instance_id, database_id
row_count = 0

client.transaction do |transaction|
  row_count = transaction.execute_update(
    "INSERT INTO Singers (SingerId, FirstName, LastName) VALUES (10, 'Virginia', 'Watson')"
  )
end

puts "#{row_count} record inserted."

En el siguiente ejemplo de código se actualiza la columna MarketingBudget de la tabla Albums en función de una cláusula WHERE.

C++

void DmlStandardUpdate(google::cloud::spanner::Client client) {
  using ::google::cloud::StatusOr;
  namespace spanner = ::google::cloud::spanner;
  auto commit_result = client.Commit(
      [&client](spanner::Transaction txn) -> StatusOr<spanner::Mutations> {
        auto update = client.ExecuteDml(
            std::move(txn),
            spanner::SqlStatement(
                "UPDATE Albums SET MarketingBudget = MarketingBudget * 2"
                "  WHERE SingerId = 1 AND AlbumId = 1"));
        if (!update) return std::move(update).status();
        return spanner::Mutations{};
      });
  if (!commit_result) throw std::move(commit_result).status();
  std::cout << "Update was successful [spanner_dml_standard_update]\n";
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class UpdateUsingDmlCoreAsyncSample
{
    public async Task<int> UpdateUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 1 and AlbumId = 1");
        int rowCount = await cmd.ExecuteNonQueryAsync();

        Console.WriteLine($"{rowCount} row(s) updated...");
        return rowCount;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func updateUsingDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `UPDATE Albums
				SET MarketingBudget = MarketingBudget * 2
				WHERE SingerId = 1 and AlbumId = 1`,
		}
		rowCount, err := txn.Update(ctx, stmt)
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "%d record(s) updated.\n", rowCount)
		return nil
	})
	return err
}

Java

static void updateUsingDml(DatabaseClient dbClient) {
  dbClient
      .readWriteTransaction()
      .run(transaction -> {
        String sql =
            "UPDATE Albums "
                + "SET MarketingBudget = MarketingBudget * 2 "
                + "WHERE SingerId = 1 and AlbumId = 1";
        long rowCount = transaction.executeUpdate(Statement.of(sql));
        System.out.printf("%d record updated.\n", rowCount);
        return null;
      });
}

Node.js

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

database.runTransaction(async (err, transaction) => {
  if (err) {
    console.error(err);
    return;
  }
  try {
    const [rowCount] = await transaction.runUpdate({
      sql: `UPDATE Albums SET MarketingBudget = MarketingBudget * 2
        WHERE SingerId = 1 and AlbumId = 1`,
    });

    console.log(`Successfully updated ${rowCount} record.`);
    await transaction.commit();
  } catch (err) {
    console.error('ERROR:', err);
  } finally {
    // Close the database when finished.
    database.close();
  }
});

PHP

use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;

/**
 * Updates sample data in the database with a DML statement.
 *
 * This requires the `MarketingBudget` column which must be created before
 * running this sample. You can add the column by running the `add_column`
 * sample or by running this DDL statement against your database:
 *
 *     ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
 *
 * Example:
 * ```
 * update_data($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function update_data_with_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $database->runTransaction(function (Transaction $t) {
        $rowCount = $t->executeUpdate(
            'UPDATE Albums '
            . 'SET MarketingBudget = MarketingBudget * 2 '
            . 'WHERE SingerId = 1 and AlbumId = 1');
        $t->commit();
        printf('Updated %d row(s).' . PHP_EOL, $rowCount);
    });
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

def update_albums(transaction):
    row_ct = transaction.execute_update(
        "UPDATE Albums "
        "SET MarketingBudget = MarketingBudget * 2 "
        "WHERE SingerId = 1 and AlbumId = 1"
    )

    print("{} record(s) updated.".format(row_ct))

database.run_in_transaction(update_albums)

Ruby

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id
row_count = 0

client.transaction do |transaction|
  row_count = transaction.execute_update(
    "UPDATE Albums
     SET MarketingBudget = MarketingBudget * 2
     WHERE SingerId = 1 and AlbumId = 1"
  )
end

puts "#{row_count} record updated."

En el siguiente ejemplo de código se eliminan todas las filas de la tabla Singers en las que la columna FirstName es Alice.

C++

void DmlStandardDelete(google::cloud::spanner::Client client) {
  using ::google::cloud::StatusOr;
  namespace spanner = ::google::cloud::spanner;
  auto commit_result = client.Commit([&client](spanner::Transaction txn)
                                         -> StatusOr<spanner::Mutations> {
    auto dele = client.ExecuteDml(
        std::move(txn),
        spanner::SqlStatement("DELETE FROM Singers WHERE FirstName = 'Alice'"));
    if (!dele) return std::move(dele).status();
    return spanner::Mutations{};
  });
  if (!commit_result) throw std::move(commit_result).status();
  std::cout << "Delete was successful [spanner_dml_standard_delete]\n";
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class DeleteUsingDmlCoreAsyncSample
{
    public async Task<int> DeleteUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE FirstName = 'Alice'");
        int rowCount = await cmd.ExecuteNonQueryAsync();

        Console.WriteLine($"{rowCount} row(s) deleted...");
        return rowCount;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func deleteUsingDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{SQL: `DELETE FROM Singers WHERE FirstName = 'Alice'`}
		rowCount, err := txn.Update(ctx, stmt)
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "%d record(s) deleted.\n", rowCount)
		return nil
	})
	return err
}

Java

static void deleteUsingDml(DatabaseClient dbClient) {
  dbClient
      .readWriteTransaction()
      .run(transaction -> {
        String sql = "DELETE FROM Singers WHERE FirstName = 'Alice'";
        long rowCount = transaction.executeUpdate(Statement.of(sql));
        System.out.printf("%d record deleted.\n", rowCount);
        return null;
      });
}

Node.js

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

database.runTransaction(async (err, transaction) => {
  if (err) {
    console.error(err);
    return;
  }
  try {
    const [rowCount] = await transaction.runUpdate({
      sql: "DELETE FROM Singers WHERE FirstName = 'Alice'",
    });

    console.log(`Successfully deleted ${rowCount} record.`);
    await transaction.commit();
  } catch (err) {
    console.error('ERROR:', err);
  } finally {
    // Close the database when finished.
    database.close();
  }
});

PHP

use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;

/**
 * Deletes sample data in the database with a DML statement.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function delete_data_with_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $database->runTransaction(function (Transaction $t) {
        $rowCount = $t->executeUpdate(
            "DELETE FROM Singers WHERE FirstName = 'Alice'");
        $t->commit();
        printf('Deleted %d row(s).' . PHP_EOL, $rowCount);
    });
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

def delete_singers(transaction):
    row_ct = transaction.execute_update(
        "DELETE FROM Singers WHERE FirstName = 'Alice'"
    )

    print("{} record(s) deleted.".format(row_ct))

database.run_in_transaction(delete_singers)

Ruby

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id
row_count = 0

client.transaction do |transaction|
  row_count = transaction.execute_update(
    "DELETE FROM Singers WHERE FirstName = 'Alice'"
  )
end

puts "#{row_count} record deleted."

En el siguiente ejemplo, que solo se aplica a bases de datos con dialecto GoogleSQL, se usa una STRUCT con parámetros enlazados para actualizar LastName en las filas filtradas por FirstName y LastName.

GoogleSQL

C++

void DmlStructs(google::cloud::spanner::Client client) {
  namespace spanner = ::google::cloud::spanner;
  std::int64_t rows_modified = 0;
  auto commit_result =
      client.Commit([&client, &rows_modified](spanner::Transaction const& txn)
                        -> google::cloud::StatusOr<spanner::Mutations> {
        auto singer_info = std::make_tuple("Marc", "Richards");
        auto sql = spanner::SqlStatement(
            "UPDATE Singers SET FirstName = 'Keith' WHERE "
            "STRUCT<FirstName String, LastName String>(FirstName, LastName) "
            "= @name",
            {{"name", spanner::Value(std::move(singer_info))}});
        auto dml_result = client.ExecuteDml(txn, std::move(sql));
        if (!dml_result) return std::move(dml_result).status();
        rows_modified = dml_result->RowsModified();
        return spanner::Mutations{};
      });
  if (!commit_result) throw std::move(commit_result).status();
  std::cout << rows_modified
            << " update was successful [spanner_dml_structs]\n";
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class UpdateUsingDmlWithStructCoreAsyncSample
{
    public async Task<int> UpdateUsingDmlWithStructCoreAsync(string projectId, string instanceId, string databaseId)
    {
        var nameStruct = new SpannerStruct
        {
            { "FirstName", SpannerDbType.String, "Timothy" },
            { "LastName", SpannerDbType.String, "Campbell" }
        };
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var cmd = connection.CreateDmlCommand("UPDATE Singers SET LastName = 'Grant' WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) = @name");
        cmd.Parameters.Add("name", nameStruct.GetSpannerDbType(), nameStruct);
        int rowCount = await cmd.ExecuteNonQueryAsync();

        Console.WriteLine($"{rowCount} row(s) updated...");
        return rowCount;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func updateUsingDMLStruct(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		type name struct {
			FirstName string
			LastName  string
		}
		var singerInfo = name{"Timothy", "Campbell"}

		stmt := spanner.Statement{
			SQL: `Update Singers Set LastName = 'Grant'
				WHERE STRUCT<FirstName String, LastName String>(Firstname, LastName) = @name`,
			Params: map[string]interface{}{"name": singerInfo},
		}
		rowCount, err := txn.Update(ctx, stmt)
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "%d record(s) inserted.\n", rowCount)
		return nil
	})
	return err
}

Java

static void updateUsingDmlWithStruct(DatabaseClient dbClient) {
  Struct name =
      Struct.newBuilder().set("FirstName").to("Timothy").set("LastName").to("Campbell").build();
  Statement s =
      Statement.newBuilder(
              "UPDATE Singers SET LastName = 'Grant' "
                  + "WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) "
                  + "= @name")
          .bind("name")
          .to(name)
          .build();
  dbClient
      .readWriteTransaction()
      .run(transaction -> {
        long rowCount = transaction.executeUpdate(s);
        System.out.printf("%d record updated.\n", rowCount);
        return null;
      });
}

Node.js

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

const nameStruct = Spanner.struct({
  FirstName: 'Timothy',
  LastName: 'Campbell',
});

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

database.runTransaction(async (err, transaction) => {
  if (err) {
    console.error(err);
    return;
  }
  try {
    const [rowCount] = await transaction.runUpdate({
      sql: `UPDATE Singers SET LastName = 'Grant'
      WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) = @name`,
      params: {
        name: nameStruct,
      },
    });

    console.log(`Successfully updated ${rowCount} record.`);
    await transaction.commit();
  } catch (err) {
    console.error('ERROR:', err);
  } finally {
    // Close the database when finished.
    database.close();
  }
});

PHP

use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Database;
use Google\Cloud\Spanner\Transaction;
use Google\Cloud\Spanner\StructType;
use Google\Cloud\Spanner\StructValue;

/**
 * Update data with a DML statement using Structs.
 *
 * The database and table must already exist and can be created using
 * `create_database`.
 * Example:
 * ```
 * insert_data($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function update_data_with_dml_structs(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $database->runTransaction(function (Transaction $t) {
        $nameValue = (new StructValue)
            ->add('FirstName', 'Timothy')
            ->add('LastName', 'Campbell');
        $nameType = (new StructType)
            ->add('FirstName', Database::TYPE_STRING)
            ->add('LastName', Database::TYPE_STRING);

        $rowCount = $t->executeUpdate(
            "UPDATE Singers SET LastName = 'Grant' "
             . 'WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) '
             . '= @name',
            [
                'parameters' => [
                    'name' => $nameValue
                ],
                'types' => [
                    'name' => $nameType
                ]
            ]);
        $t->commit();
        printf('Updated %d row(s).' . PHP_EOL, $rowCount);
    });
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

record_type = param_types.Struct(
    [
        param_types.StructField("FirstName", param_types.STRING),
        param_types.StructField("LastName", param_types.STRING),
    ]
)
record_value = ("Timothy", "Campbell")

def write_with_struct(transaction):
    row_ct = transaction.execute_update(
        "UPDATE Singers SET LastName = 'Grant' "
        "WHERE STRUCT<FirstName STRING, LastName STRING>"
        "(FirstName, LastName) = @name",
        params={"name": record_value},
        param_types={"name": record_type},
    )
    print("{} record(s) updated.".format(row_ct))

database.run_in_transaction(write_with_struct)

Ruby

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id
row_count = 0
name_struct = { FirstName: "Timothy", LastName: "Campbell" }

client.transaction do |transaction|
  row_count = transaction.execute_update(
    "UPDATE Singers SET LastName = 'Grant'
     WHERE STRUCT<FirstName STRING, LastName STRING>(FirstName, LastName) = @name",
    params: { name: name_struct }
  )
end

puts "#{row_count} record updated."

Modificar datos con las instrucciones DML de devolución

La cláusula THEN RETURN (bases de datos con dialecto de GoogleSQL) o la cláusula RETURNING (bases de datos con dialecto de PostgreSQL) se usan en situaciones en las que quieres obtener datos de filas modificadas. Esto es especialmente útil cuando quieres ver valores no especificados en las instrucciones DML, los valores predeterminados o las columnas generadas.

Para ejecutar instrucciones de DML de retorno mediante la biblioteca de cliente, sigue estos pasos:

Crea una transacción de lectura y escritura.
Llama al método de la biblioteca de cliente para ejecutar la consulta y pasa la instrucción DML de devolución para obtener los resultados.

En el siguiente ejemplo de código se inserta una fila en la tabla Singers y se devuelve la columna FullName generada de los registros insertados.

GoogleSQL

C++

void InsertUsingDmlReturning(google::cloud::spanner::Client client) {
  // Insert records into SINGERS table and return the generated column
  // FullName of the inserted records using `THEN RETURN FullName`.
  auto commit = client.Commit(
      [&client](google::cloud::spanner::Transaction txn)
          -> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
        auto sql = google::cloud::spanner::SqlStatement(R"""(
            INSERT INTO Singers (SingerId, FirstName, LastName)
              VALUES (12, 'Melissa', 'Garcia'),
                     (13, 'Russell', 'Morales'),
                     (14, 'Jacqueline', 'Long'),
                     (15, 'Dylan', 'Shaw')
              THEN RETURN FullName
        )""");
        using RowType = std::tuple<std::string>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
        // Note: This mutator might be re-run, or its effects discarded, so
        // changing non-transactional state (e.g., by producing output) is,
        // in general, not something to be imitated.
        for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "FullName: " << std::get<0>(*row) << "\n";
        }
        std::cout << "Inserted row(s) count: " << rows.RowsModified() << "\n";
        return google::cloud::spanner::Mutations{};
      });
  if (!commit) throw std::move(commit).status();
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;

public class InsertUsingDmlReturningAsyncSample
{
    public async Task<List<string>> InsertUsingDmlReturningAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        // Insert records into the SINGERS table and return the
        // generated column FullName of the inserted records using
        // 'THEN RETURN FullName'.
        // It is also possible to return all columns of all the
        // inserted records by using 'THEN RETURN *'.
        using var cmd = connection.CreateDmlCommand(
            @"INSERT INTO Singers(SingerId, FirstName, LastName) VALUES
            (6, 'Melissa', 'Garcia'), 
            (7, 'Russell', 'Morales'), 
            (8, 'Jacqueline', 'Long'), 
            (9, 'Dylan', 'Shaw') THEN RETURN FullName");

        var reader = await cmd.ExecuteReaderAsync();
        var insertedSingerNames = new List<string>();
        while (await reader.ReadAsync())
        {
            insertedSingerNames.Add(reader.GetFieldValue<string>("FullName"));
        }

        Console.WriteLine($"{insertedSingerNames.Count} row(s) inserted...");
        return insertedSingerNames;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func insertUsingDMLReturning(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	// Insert records into the SINGERS table and returns the
	// generated column FullName of the inserted records using
	// 'THEN RETURN FullName'.
	// It is also possible to return all columns of all the
	// inserted records by using 'THEN RETURN *'.
	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `INSERT INTO Singers (SingerId, FirstName, LastName)
			        VALUES (21, 'Melissa', 'Garcia'),
			               (22, 'Russell', 'Morales'),
			               (23, 'Jacqueline', 'Long'),
			               (24, 'Dylan', 'Shaw')
			        THEN RETURN FullName`,
		}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()
		for {
			row, err := iter.Next()
			if err == iterator.Done {
				break
			}
			if err != nil {
				return err
			}
			var fullName string
			if err := row.Columns(&fullName); err != nil {
				return err
			}
			fmt.Fprintf(w, "%s\n", fullName)
		}
		fmt.Fprintf(w, "%d record(s) inserted.\n", iter.RowCount)
		return nil
	})
	return err
}

Java


import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;

public class InsertUsingDmlReturningSample {

  static void insertUsingDmlReturning() {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "my-project";
    final String instanceId = "my-instance";
    final String databaseId = "my-database";
    insertUsingDmlReturning(projectId, instanceId, databaseId);
  }

  static void insertUsingDmlReturning(String projectId, String instanceId, String databaseId) {
    try (Spanner spanner =
        SpannerOptions.newBuilder()
            .setProjectId(projectId)
            .build()
            .getService()) {
      final DatabaseClient dbClient =
          spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
      // Insert records into the SINGERS table and returns the
      // generated column FullName of the inserted records using
      // ‘THEN RETURN FullName’.
      // It is also possible to return all columns of all the
      // inserted records by using ‘THEN RETURN *’.
      dbClient
          .readWritreadWriteTransaction     .run(
              transaction -> {
                String sql =
                    "INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
                        + "(12, 'Melissa', 'Garcia'), "
                        + "(13, 'Russell', 'Morales'), "
                        + "(14, 'Jacqueline', 'Long'), "
                        + "(15, 'Dylan', 'Shaw') THEN RETURN FullName";

                // readWriteTransaction.executeQuery(..) API should be used for executing
                // DML statements with RETURNING clause.
                try (ResultSeResultSetet = transaction.executeQuery(StatemenStatement)) {
                  while (resultSet.next()) {
                    System.out.println(resultSet.getString(0));
                  }
                  System.out.printf(
                      "Inserted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
                }
                return null;
              });
    }
  }
}

Node.js

// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

function insertUsingDmlReturning(instanceId, databaseId) {
  // Gets a reference to a Cloud Spanner instance and database.
  const instance = spanner.instance(instanceId);
  const database = instance.database(databaseId);

  database.runTransaction(async (err, transaction) => {
    if (err) {
      console.error(err);
      return;
    }
    try {
      const [rows, stats] = await transaction.run({
        sql: 'INSERT Singers (SingerId, FirstName, LastName) VALUES (@id, @firstName, @lastName) THEN RETURN FullName',
        params: {
          id: 18,
          firstName: 'Virginia',
          lastName: 'Watson',
        },
      });

      const rowCount = Math.floor(stats[stats.rowCount]);
      console.log(
        `Successfully inserted ${rowCount} record into the Singers table.`,
      );
      rows.forEach(row => {
        console.log(row.toJSON().FullName);
      });

      await transaction.commit();
    } catch (err) {
      console.error('ERROR:', err);
    } finally {
      // Close the database when finished.
      database.close();
    }
  });
}
insertUsingDmlReturning(instanceId, databaseId);

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Inserts sample data into the given database using DML returning.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function insert_dml_returning(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    // Insert records into SINGERS table and returns the generated column
    // FullName of the inserted records using ‘THEN RETURN FullName’. It is also
    // possible to return all columns of all the inserted records by using
    // ‘THEN RETURN *’.

    $sql = 'INSERT INTO Singers (SingerId, FirstName, LastName) '
        . "VALUES (12, 'Melissa', 'Garcia'), "
        . "(13, 'Russell', 'Morales'), "
        . "(14, 'Jacqueline', 'Long'), "
        . "(15, 'Dylan', 'Shaw') "
        . 'THEN RETURN FullName';

    $transaction = $database->transaction();
    $result = $transaction->execute($sql);
    foreach ($result->rows() as $row) {
        printf(
            '%s inserted.' . PHP_EOL,
            $row['FullName'],
        );
    }
    printf(
        'Inserted row(s) count: %d' . PHP_EOL,
        $result->stats()['rowCountExact']
    );
    $transaction->commit();
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

# Insert records into the SINGERS table and returns the
# generated column FullName of the inserted records using
# 'THEN RETURN FullName'.
# It is also possible to return all columns of all the
# inserted records by using 'THEN RETURN *'.
def insert_singers(transaction):
    results = transaction.execute_sql(
        "INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
        "(21, 'Luann', 'Chizoba'), "
        "(22, 'Denis', 'Patricio'), "
        "(23, 'Felxi', 'Ronan'), "
        "(24, 'Dominik', 'Martyna') "
        "THEN RETURN FullName"
    )
    for result in results:
        print("FullName: {}".format(*result))
    print("{} record(s) inserted.".format(results.stats.row_count_exact))

database.run_in_transaction(insert_singers)

Ruby

require "google/cloud/spanner"

##
# This is a snippet for showcasing how to use DML return feature with insert
# operation.
#
# @param project_id  [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_insert_dml_returning project_id:, instance_id:, database_id:
  spanner = Google::Cloud::Spanner.new project: project_id
  client = spanner.client instance_id, database_id

  client.transaction do |transaction|
    # Insert records into the SINGERS table and returns the generated column
    # FullName of the inserted records using ‘THEN RETURN FullName’.
    # It is also possible to return all columns of all the inserted records
    # by using ‘THEN RETURN *’.
    results = transaction.execute_query "INSERT INTO Singers (SingerId, FirstName, LastName)
                                         VALUES (12, 'Melissa', 'Garcia'), (13, 'Russell', 'Morales'), (14, 'Jacqueline', 'Long'), (15, 'Dylan', 'Shaw')
                                         THEN RETURN FullName"
    results.rows.each do |row|
      puts "Inserted singers with FullName: #{row[:FullName]}"
    end
    puts "Inserted row(s) count: #{results.row_count}"
  end
end

PostgreSQL

C++

void InsertUsingDmlReturning(google::cloud::spanner::Client client) {
  // Insert records into SINGERS table and return the generated column
  // FullName of the inserted records using `RETURNING FullName`.
  auto commit = client.Commit(
      [&client](google::cloud::spanner::Transaction txn)
          -> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
        auto sql = google::cloud::spanner::SqlStatement(R"""(
            INSERT INTO Singers (SingerId, FirstName, LastName)
                VALUES (12, 'Melissa', 'Garcia'),
                       (13, 'Russell', 'Morales'),
                       (14, 'Jacqueline', 'Long'),
                       (15, 'Dylan', 'Shaw')
                RETURNING FullName
        )""");
        using RowType = std::tuple<std::string>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
        for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "FullName: " << std::get<0>(*row) << "\n";
        }
        std::cout << "Inserted row(s) count: " << rows.RowsModified() << "\n";
        return google::cloud::spanner::Mutations{};
      });
  if (!commit) throw std::move(commit).status();
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;

public class InsertUsingDmlReturningAsyncPostgresSample
{
    public async Task<List<string>> InsertUsingDmlReturningAsyncPostgres(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        // Insert records into SINGERS table and return the
        // generated column FullName of the inserted records
        // using 'RETURNING FullName'.
        // It is also possible to return all columns of all the
        // inserted records by using 'RETURNING *'.
        using var cmd = connection.CreateDmlCommand(
            @"INSERT INTO Singers(SingerId, FirstName, LastName) VALUES
            (6, 'Melissa', 'Garcia'), 
            (7, 'Russell', 'Morales'), 
            (8, 'Jacqueline', 'Long'), 
            (9, 'Dylan', 'Shaw') RETURNING FullName");

        var reader = await cmd.ExecuteReaderAsync();
        var insertedSingerNames = new List<string>();
        while (await reader.ReadAsync())
        {
            insertedSingerNames.Add(reader.GetFieldValue<string>("fullname"));
        }

        Console.WriteLine($"{insertedSingerNames.Count} row(s) inserted...");
        return insertedSingerNames;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func pgInsertUsingDMLReturning(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	// Insert records into the SINGERS table and returns the
	// generated column FullName of the inserted records using
	// 'RETURNING FullName'.
	// It is also possible to return all columns of all the
	// inserted records by using 'RETURNING *'.
	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `INSERT INTO Singers (SingerId, FirstName, LastName)
			        VALUES (21, 'Melissa', 'Garcia'),
			               (22, 'Russell', 'Morales'),
			               (23, 'Jacqueline', 'Long'),
			               (24, 'Dylan', 'Shaw')
			        RETURNING FullName`,
		}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()
		for {
			row, err := iter.Next()
			if err == iterator.Done {
				break
			}
			if err != nil {
				return err
			}
			var fullName string
			if err := row.Columns(&fullName); err != nil {
				return err
			}
			fmt.Fprintf(w, "%s\n", fullName)
		}
		fmt.Fprintf(w, "%d record(s) inserted.\n", iter.RowCount)
		return nil
	})
	return err
}

Java


import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;

public class PgInsertUsingDmlReturningSample {

  static void insertUsingDmlReturning() {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "my-project";
    final String instanceId = "my-instance";
    final String databaseId = "my-database";
    insertUsingDmlReturning(projectId, instanceId, databaseId);
  }

  static void insertUsingDmlReturning(String projectId, String instanceId, String databaseId) {
    try (Spanner spanner =
        SpannerOptions.newBuilder()
            .setProjectId(projectId)
            .build()
            .getService()) {
      final DatabaseClient dbClient =
          spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
      // Insert records into SINGERS table and returns the
      // generated column FullName of the inserted records
      // using ‘RETURNING FullName’.
      // It is also possible to return all columns of all the
      // inserted records by using ‘RETURNING *’.
      dbClient
          .readWritreadWriteTransaction     .run(
              transaction -> {
                String sql =
                    "INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
                        + "(12, 'Melissa', 'Garcia'), "
                        + "(13, 'Russell', 'Morales'), "
                        + "(14, 'Jacqueline', 'Long'), "
                        + "(15, 'Dylan', 'Shaw') RETURNING FullName";

                // readWriteTransaction.executeQuery(..) API should be used for executing
                // DML statements with RETURNING clause.
                try (ResultSeResultSetet = transaction.executeQuery(StatemenStatement)) {
                  while (resultSet.next()) {
                    System.out.println(resultSet.getString(0));
                  }
                  System.out.printf(
                      "Inserted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
                }
                return null;
              });
    }
  }
}

Node.js

// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

function pgInsertUsingDmlReturning(instanceId, databaseId) {
  // Gets a reference to a Cloud Spanner instance and database.
  const instance = spanner.instance(instanceId);
  const database = instance.database(databaseId);

  database.runTransaction(async (err, transaction) => {
    if (err) {
      console.error(err);
      return;
    }
    try {
      const [rows, stats] = await transaction.run({
        sql: 'INSERT Into Singers (SingerId, FirstName, LastName) VALUES ($1, $2, $3) RETURNING FullName',
        params: {
          p1: 18,
          p2: 'Virginia',
          p3: 'Watson',
        },
      });

      const rowCount = Math.floor(stats[stats.rowCount]);
      console.log(
        `Successfully inserted ${rowCount} record into the Singers table.`,
      );
      rows.forEach(row => {
        console.log(row.toJSON().fullname);
      });

      await transaction.commit();
    } catch (err) {
      console.error('ERROR:', err);
    } finally {
      // Close the database when finished.
      database.close();
    }
  });
}
pgInsertUsingDmlReturning(instanceId, databaseId);

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Inserts sample data into the given postgresql database using DML returning.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function pg_insert_dml_returning(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    // Insert records into SINGERS table and returns the generated column
    // FullName of the inserted records using ‘RETURNING FullName’. It is also
    // possible to return all columns of all the inserted records by using
    // ‘RETURNING *’.

    $sql = 'INSERT INTO Singers (Singerid, FirstName, LastName) '
      . "VALUES (12, 'Melissa', 'Garcia'), "
      . "(13, 'Russell', 'Morales'), "
      . "(14, 'Jacqueline', 'Long'), "
      . "(15, 'Dylan', 'Shaw') "
      . 'RETURNING FullName';

    $transaction = $database->transaction();
    $result = $transaction->execute($sql);
    foreach ($result->rows() as $row) {
        printf(
            '%s inserted.' . PHP_EOL,
            $row['fullname'],
        );
    }
    printf(
        'Inserted row(s) count: %d' . PHP_EOL,
        $result->stats()['rowCountExact']
    );
    $transaction->commit();
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

# Insert records into the SINGERS table and returns the
# generated column FullName of the inserted records using
# 'RETURNING FullName'.
# It is also possible to return all columns of all the
# inserted records by using 'RETURNING *'.
def insert_singers(transaction):
    results = transaction.execute_sql(
        "INSERT INTO Singers (SingerId, FirstName, LastName) VALUES "
        "(21, 'Luann', 'Chizoba'), "
        "(22, 'Denis', 'Patricio'), "
        "(23, 'Felxi', 'Ronan'), "
        "(24, 'Dominik', 'Martyna') "
        "RETURNING FullName"
    )
    for result in results:
        print("FullName: {}".format(*result))
    print("{} record(s) inserted.".format(results.stats.row_count_exact))

database.run_in_transaction(insert_singers)

Ruby

require "google/cloud/spanner"

##
# This is a snippet for showcasing how to use DML return feature with insert
# operation in PostgreSql.
#
# @param project_id  [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_postgresql_insert_dml_returning project_id:, instance_id:, database_id:
  spanner = Google::Cloud::Spanner.new project: project_id
  client = spanner.client instance_id, database_id

  client.transaction do |transaction|
    # Insert records into SINGERS table and returns the generated column
    # FullName of the inserted records using ‘RETURNING FullName’.
    # It is also possible to return all columns of all the inserted
    # records by using ‘RETURNING *’.
    results = transaction.execute_query "INSERT INTO Singers (SingerId, FirstName, LastName)
                                         VALUES (12, 'Melissa', 'Garcia'), (13, 'Russell', 'Morales'), (14, 'Jacqueline', 'Long'), (15, 'Dylan', 'Shaw')
                                         RETURNING FullName"
    results.rows.each do |row|
      puts "Inserted singers with FullName: #{row[:fullname]}"
    end
    puts "Inserted row(s) count: #{results.row_count}"
  end
end

En el siguiente ejemplo de código se actualiza la columna MarketingBudget de la tabla Albums en función de una cláusula WHERE y se devuelve la columna MarketingBudget modificada de los registros actualizados.

GoogleSQL

C++

void UpdateUsingDmlReturning(google::cloud::spanner::Client client) {
  // Update MarketingBudget column for records satisfying a particular
  // condition and return the modified MarketingBudget column of the
  // updated records using `THEN RETURN MarketingBudget`.
  auto commit = client.Commit(
      [&client](google::cloud::spanner::Transaction txn)
          -> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
        auto sql = google::cloud::spanner::SqlStatement(R"""(
            UPDATE Albums SET MarketingBudget = MarketingBudget * 2
              WHERE SingerId = 1 AND AlbumId = 1
              THEN RETURN MarketingBudget
        )""");
        using RowType = std::tuple<absl::optional<std::int64_t>>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
        // Note: This mutator might be re-run, or its effects discarded, so
        // changing non-transactional state (e.g., by producing output) is,
        // in general, not something to be imitated.
        for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "MarketingBudget: ";
          if (std::get<0>(*row).has_value()) {
            std::cout << *std::get<0>(*row);
          } else {
            std::cout << "NULL";
          }
          std::cout << "\n";
        }
        std::cout << "Updated row(s) count: " << rows.RowsModified() << "\n";
        return google::cloud::spanner::Mutations{};
      });
  if (!commit) throw std::move(commit).status();
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;

public class UpdateUsingDmlReturningAsyncSample
{
    public async Task<List<long>> UpdateUsingDmlReturningAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        // Update MarketingBudget column for records satisfying
        // a particular condition and return the modified
        // MarketingBudget column of the updated records using
        // 'THEN RETURN MarketingBudget'.
        // It is also possible to return all columns of all the
        // updated records by using 'THEN RETURN *'.
        using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 1 and AlbumId = 1 THEN RETURN MarketingBudget");
        var reader = await cmd.ExecuteReaderAsync();
        var updatedMarketingBudgets = new List<long>();
        while (await reader.ReadAsync())
        {
            updatedMarketingBudgets.Add(reader.GetFieldValue<long>("MarketingBudget"));
        }

        Console.WriteLine($"{updatedMarketingBudgets.Count} row(s) updated...");
        return updatedMarketingBudgets;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func updateUsingDMLReturning(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	// Update MarketingBudget column for records satisfying
	// a particular condition and returns the modified
	// MarketingBudget column of the updated records using
	// 'THEN RETURN MarketingBudget'.
	// It is also possible to return all columns of all the
	// updated records by using 'THEN RETURN *'.
	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `UPDATE Albums
				SET MarketingBudget = MarketingBudget * 2
				WHERE SingerId = 1 and AlbumId = 1
				THEN RETURN MarketingBudget`,
		}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()
		for {
			row, err := iter.Next()
			if err == iterator.Done {
				break
			}
			if err != nil {
				return err
			}
			var marketingBudget int64
			if err := row.Columns(&marketingBudget); err != nil {
				return err
			}
			fmt.Fprintf(w, "%d\n", marketingBudget)
		}
		fmt.Fprintf(w, "%d record(s) updated.\n", iter.RowCount)
		return nil
	})
	return err
}

Java


import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;

public class UpdateUsingDmlReturningSample {

  static void updateUsingDmlReturning() {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "my-project";
    final String instanceId = "my-instance";
    final String databaseId = "my-database";
    updateUsingDmlReturning(projectId, instanceId, databaseId);
  }

  static void updateUsingDmlReturning(String projectId, String instanceId, String databaseId) {
    try (Spanner spanner =
        SpannerOptions.newBuilder()
            .setProjectId(projectId)
            .build()
            .getService()) {
      final DatabaseClient dbClient =
          spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
      // Update MarketingBudget column for records satisfying
      // a particular condition and returns the modified
      // MarketingBudget column of the updated records using
      // ‘THEN RETURN MarketingBudget’.
      // It is also possible to return all columns of all the
      // updated records by using ‘THEN RETURN *’.
      dbClient
          .readWritreadWriteTransaction     .run(
              transaction -> {
                String sql =
                    "UPDATE Albums "
                        + "SET MarketingBudget = MarketingBudget * 2 "
                        + "WHERE SingerId = 1 and AlbumId = 1 "
                        + "THEN RETURN MarketingBudget";

                // readWriteTransaction.executeQuery(..) API should be used for executing
                // DML statements with RETURNING clause.
                try (ResultSeResultSetet = transaction.executeQuery(StatemenStatement)) {
                  while (resultSet.next()) {
                    System.out.printf("%d\n", resultSet.getLong(0));
                  }
                  System.out.printf(
                      "Updated row(s) count: %d\n", resultSet.getStats().getRowCountExact());
                }
                return null;
              });
    }
  }
}

Node.js

// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

function updateUsingDmlReturning(instanceId, databaseId) {
  // Gets a reference to a Cloud Spanner instance and database.
  const instance = spanner.instance(instanceId);
  const database = instance.database(databaseId);

  database.runTransaction(async (err, transaction) => {
    if (err) {
      console.error(err);
      return;
    }
    try {
      const [rows, stats] = await transaction.run({
        sql: 'UPDATE Albums SET MarketingBudget = 2000000 WHERE SingerId = 1 and AlbumId = 1 THEN RETURN MarketingBudget',
      });

      const rowCount = Math.floor(stats[stats.rowCount]);
      console.log(
        `Successfully updated ${rowCount} record into the Albums table.`,
      );
      rows.forEach(row => {
        console.log(row.toJSON().MarketingBudget);
      });

      await transaction.commit();
    } catch (err) {
      console.error('ERROR:', err);
    } finally {
      // Close the database when finished.
      database.close();
    }
  });
}
updateUsingDmlReturning(instanceId, databaseId);

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Update the given database using DML returning.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function update_dml_returning(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $transaction = $database->transaction();

    // Update MarketingBudget column for records satisfying a particular
    // condition and returns the modified MarketingBudget column of the updated
    // records using ‘THEN RETURN MarketingBudget’. It is also possible to return
    // all columns of all the updated records by using ‘THEN RETURN *’.

    $result = $transaction->execute(
        'UPDATE Albums '
        . 'SET MarketingBudget = MarketingBudget * 2 '
        . 'WHERE SingerId = 1 and AlbumId = 1 '
        . 'THEN RETURN MarketingBudget'
    );
    foreach ($result->rows() as $row) {
        printf('MarketingBudget: %s' . PHP_EOL, $row['MarketingBudget']);
    }
    printf(
        'Updated row(s) count: %d' . PHP_EOL,
        $result->stats()['rowCountExact']
    );
    $transaction->commit();
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

# Update MarketingBudget column for records satisfying
# a particular condition and returns the modified
# MarketingBudget column of the updated records using
# 'THEN RETURN MarketingBudget'.
# It is also possible to return all columns of all the
# updated records by using 'THEN RETURN *'.
def update_albums(transaction):
    results = transaction.execute_sql(
        "UPDATE Albums "
        "SET MarketingBudget = MarketingBudget * 2 "
        "WHERE SingerId = 1 and AlbumId = 1 "
        "THEN RETURN MarketingBudget"
    )
    for result in results:
        print("MarketingBudget: {}".format(*result))
    print("{} record(s) updated.".format(results.stats.row_count_exact))

database.run_in_transaction(update_albums)

Ruby

require "google/cloud/spanner"

##
# This is a snippet for showcasing how to use DML return feature with update
# operation.
#
# @param project_id  [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_update_dml_returning project_id:, instance_id:, database_id:
  spanner = Google::Cloud::Spanner.new project: project_id
  client = spanner.client instance_id, database_id

  client.transaction do |transaction|
    # Update MarketingBudget column for records satisfying a particular
    # condition and returns the modified MarketingBudget column of the
    # updated records using ‘THEN RETURN MarketingBudget’.
    #
    # It is also possible to return all columns of all the updated records
    # by using ‘THEN RETURN *’.
    results = transaction.execute_query "UPDATE Albums SET MarketingBudget = MarketingBudget * 2
                                         WHERE SingerId = 1 and AlbumId = 1
                                         THEN RETURN MarketingBudget"
    results.rows.each do |row|
      puts "Updated Album with MarketingBudget: #{row[:MarketingBudget]}"
    end
    puts "Updated row(s) count: #{results.row_count}"
  end
end

PostgreSQL

C++

void UpdateUsingDmlReturning(google::cloud::spanner::Client client) {
  // Update MarketingBudget column for records satisfying a particular
  // condition and return the modified MarketingBudget column of the
  // updated records using `RETURNING MarketingBudget`.
  auto commit = client.Commit(
      [&client](google::cloud::spanner::Transaction txn)
          -> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
        auto sql = google::cloud::spanner::SqlStatement(R"""(
            UPDATE Albums SET MarketingBudget = MarketingBudget * 2
              WHERE SingerId = 1 AND AlbumId = 1
              RETURNING MarketingBudget
        )""");
        using RowType = std::tuple<absl::optional<std::int64_t>>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
        for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "MarketingBudget: ";
          if (std::get<0>(*row).has_value()) {
            std::cout << *std::get<0>(*row);
          } else {
            std::cout << "NULL";
          }
          std::cout << "\n";
        }
        std::cout << "Updated row(s) count: " << rows.RowsModified() << "\n";
        return google::cloud::spanner::Mutations{};
      });
  if (!commit) throw std::move(commit).status();
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;

public class UpdateUsingDmlReturningAsyncPostgresSample
{
    public async Task<List<long>> UpdateUsingDmlReturningAsyncPostgres(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        // Update MarketingBudget column for records satisfying
        // a particular condition and return the modified
        // MarketingBudget column of the updated records using
        // 'RETURNING MarketingBudget'.
        // It is also possible to return all columns of all the
        // updated records by using 'RETURNING *'.
        using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 14 and AlbumId = 20 RETURNING MarketingBudget");

        var reader = await cmd.ExecuteReaderAsync();
        var updatedMarketingBudgets = new List<long>();
        while (await reader.ReadAsync())
        {
            updatedMarketingBudgets.Add(reader.GetFieldValue<long>("marketingbudget"));
        }

        Console.WriteLine($"{updatedMarketingBudgets.Count} row(s) updated...");
        return updatedMarketingBudgets;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func pgUpdateUsingDMLReturning(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	// Update MarketingBudget column for records satisfying
	// a particular condition and returns the modified
	// MarketingBudget column of the updated records using
	// 'RETURNING MarketingBudget'.
	// It is also possible to return all columns of all the
	// updated records by using 'RETURNING *'.
	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `UPDATE Albums
				SET MarketingBudget = MarketingBudget * 2
				WHERE SingerId = 1 and AlbumId = 1
				RETURNING MarketingBudget`,
		}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()
		for {
			row, err := iter.Next()
			if err == iterator.Done {
				break
			}
			if err != nil {
				return err
			}
			var marketingBudget int64
			if err := row.Columns(&marketingBudget); err != nil {
				return err
			}
			fmt.Fprintf(w, "%d\n", marketingBudget)
		}
		fmt.Fprintf(w, "%d record(s) updated.\n", iter.RowCount)
		return nil
	})
	return err
}

Java


import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;

public class PgUpdateUsingDmlReturningSample {

  static void updateUsingDmlReturning() {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "my-project";
    final String instanceId = "my-instance";
    final String databaseId = "my-database";
    updateUsingDmlReturning(projectId, instanceId, databaseId);
  }

  static void updateUsingDmlReturning(String projectId, String instanceId, String databaseId) {
    try (Spanner spanner =
        SpannerOptions.newBuilder()
            .setProjectId(projectId)
            .build()
            .getService()) {
      final DatabaseClient dbClient =
          spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
      // Update MarketingBudget column for records satisfying
      // a particular condition and returns the modified
      // MarketingBudget column of the updated records using
      // ‘RETURNING MarketingBudget’.
      // It is also possible to return all columns of all the
      // updated records by using ‘RETURNING *’.
      dbClient
          .readWritreadWriteTransaction     .run(
              transaction -> {
                String sql =
                    "UPDATE Albums "
                        + "SET MarketingBudget = MarketingBudget * 2 "
                        + "WHERE SingerId = 1 and AlbumId = 1 "
                        + "RETURNING MarketingBudget";

                // readWriteTransaction.executeQuery(..) API should be used for executing
                // DML statements with RETURNING clause.
                try (ResultSeResultSetet = transaction.executeQuery(StatemenStatement)) {
                  while (resultSet.next()) {
                    System.out.printf("%d\n", resultSet.getLong(0));
                  }
                  System.out.printf(
                      "Updated row(s) count: %d\n", resultSet.getStats().getRowCountExact());
                }
                return null;
              });
    }
  }
}

Node.js

// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

function pgUpdateUsingDmlReturning(instanceId, databaseId) {
  // Gets a reference to a Cloud Spanner instance and database.
  const instance = spanner.instance(instanceId);
  const database = instance.database(databaseId);

  database.runTransaction(async (err, transaction) => {
    if (err) {
      console.error(err);
      return;
    }
    try {
      const [rows, stats] = await transaction.run({
        sql: 'UPDATE singers SET FirstName = $1, LastName = $2 WHERE singerid = $3 RETURNING FullName',
        params: {
          p1: 'Virginia1',
          p2: 'Watson1',
          p3: 18,
        },
      });

      const rowCount = Math.floor(stats[stats.rowCount]);
      console.log(
        `Successfully updated ${rowCount} record into the Singers table.`,
      );
      rows.forEach(row => {
        console.log(row.toJSON().fullname);
      });

      await transaction.commit();
    } catch (err) {
      console.error('ERROR:', err);
    } finally {
      // Close the database when finished.
      database.close();
    }
  });
}
pgUpdateUsingDmlReturning(instanceId, databaseId);

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Update the given postgresql database using DML returning.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function pg_update_dml_returning(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $transaction = $database->transaction();

    // Update MarketingBudget column for records satisfying a particular
    // condition and returns the modified MarketingBudget column of the updated
    // records using ‘RETURNING MarketingBudget’. It is also possible to return
    // all columns of all the updated records by using ‘RETURNING *’.

    $result = $transaction->execute(
        'UPDATE Albums '
        . 'SET MarketingBudget = MarketingBudget * 2 '
        . 'WHERE SingerId = 1 and AlbumId = 1 '
        . 'RETURNING MarketingBudget'
    );
    foreach ($result->rows() as $row) {
        printf('MarketingBudget: %s' . PHP_EOL, $row['marketingbudget']);
    }
    printf(
        'Updated row(s) count: %d' . PHP_EOL,
        $result->stats()['rowCountExact']
    );
    $transaction->commit();
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

# Update MarketingBudget column for records satisfying
# a particular condition and returns the modified
# MarketingBudget column of the updated records using
# 'RETURNING MarketingBudget'.
# It is also possible to return all columns of all the
# updated records by using 'RETURNING *'.
def update_albums(transaction):
    results = transaction.execute_sql(
        "UPDATE Albums "
        "SET MarketingBudget = MarketingBudget * 2 "
        "WHERE SingerId = 1 and AlbumId = 1 "
        "RETURNING MarketingBudget"
    )
    for result in results:
        print("MarketingBudget: {}".format(*result))
    print("{} record(s) updated.".format(results.stats.row_count_exact))

database.run_in_transaction(update_albums)

Ruby

require "google/cloud/spanner"

##
# This is a snippet for showcasing how to use DML return feature with update
# operation in PostgreSql.
#
# @param project_id  [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_postgresql_update_dml_returning project_id:, instance_id:, database_id:
  spanner = Google::Cloud::Spanner.new project: project_id
  client = spanner.client instance_id, database_id

  client.transaction do |transaction|
    # Update MarketingBudget column for records satisfying a particular
    # condition and returns the modified MarketingBudget column of the
    # updated records using ‘RETURNING MarketingBudget’.
    # It is also possible to return all columns of all the updated records
    # by using ‘RETURNING *’.
    results = transaction.execute_query "UPDATE Albums SET MarketingBudget = MarketingBudget * 2
                                         WHERE SingerId = 1 and AlbumId = 1
                                         RETURNING MarketingBudget"
    results.rows.each do |row|
      puts "Updated Albums with MarketingBudget: #{row[:marketingbudget]}"
    end
    puts "Updated row(s) count: #{results.row_count}"
  end
end

En el siguiente ejemplo de código se eliminan todas las filas de la tabla Singers en las que la columna FirstName es Alice y se devuelven las columnas SingerId y FullName de los registros eliminados.

GoogleSQL

C++

void DeleteUsingDmlReturning(google::cloud::spanner::Client client) {
  // Delete records from SINGERS table satisfying a particular condition
  // and return the SingerId and FullName column of the deleted records
  // using `THEN RETURN SingerId, FullName'.
  auto commit = client.Commit(
      [&client](google::cloud::spanner::Transaction txn)
          -> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
        auto sql = google::cloud::spanner::SqlStatement(R"""(
            DELETE FROM Singers
              WHERE FirstName = 'Alice'
              THEN RETURN SingerId, FullName
        )""");
        using RowType = std::tuple<std::int64_t, std::string>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
        // Note: This mutator might be re-run, or its effects discarded, so
        // changing non-transactional state (e.g., by producing output) is,
        // in general, not something to be imitated.
        for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "SingerId: " << std::get<0>(*row) << " ";
          std::cout << "FullName: " << std::get<1>(*row) << "\n";
        }
        std::cout << "Deleted row(s) count: " << rows.RowsModified() << "\n";
        return google::cloud::spanner::Mutations{};
      });
  if (!commit) throw std::move(commit).status();
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;

public class DeleteUsingDmlReturningAsyncSample
{
    public async Task<List<string>> DeleteUsingDmlReturningAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        // Delete records from SINGERS table satisfying a
        // particular condition and return the SingerId
        // and FullName column of the deleted records using
        // 'THEN RETURN SingerId, FullName'.
        // It is also possible to return all columns of all the
        // deleted records by using 'THEN RETURN *'.
        using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE FirstName = 'Alice' THEN RETURN SingerId, FullName");
        var reader = await cmd.ExecuteReaderAsync();
        var deletedSingerNames = new List<string>();
        while (await reader.ReadAsync())
        {
            deletedSingerNames.Add(reader.GetFieldValue<string>("FullName"));
        }

        Console.WriteLine($"{deletedSingerNames.Count} row(s) deleted...");
        return deletedSingerNames;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func deleteUsingDMLReturning(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	// Delete records from SINGERS table satisfying a
	// particular condition and returns the SingerId
	// and FullName column of the deleted records using
	// 'THEN RETURN SingerId, FullName'.
	// It is also possible to return all columns of all the
	// deleted records by using 'THEN RETURN *'.
	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `DELETE FROM Singers WHERE FirstName = 'Alice'
			        THEN RETURN SingerId, FullName`,
		}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()
		for {
			row, err := iter.Next()
			if err == iterator.Done {
				break
			}
			if err != nil {
				return err
			}
			var (
				singerID int64
				fullName string
			)
			if err := row.Columns(&singerID, &fullName); err != nil {
				return err
			}
			fmt.Fprintf(w, "%d %s\n", singerID, fullName)
		}
		fmt.Fprintf(w, "%d record(s) deleted.\n", iter.RowCount)
		return nil
	})
	return err
}

Java


import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;

public class DeleteUsingDmlReturningSample {

  static void deleteUsingDmlReturningSample() {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "my-project";
    final String instanceId = "my-instance";
    final String databaseId = "my-database";
    deleteUsingDmlReturningSample(projectId, instanceId, databaseId);
  }

  static void deleteUsingDmlReturningSample(
      String projectId, String instanceId, String databaseId) {
    try (Spanner spanner =
        SpannerOptions.newBuilder()
            .setProjectId(projectId)
            .build()
            .getService()) {
      final DatabaseClient dbClient =
          spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
      // Delete records from SINGERS table satisfying a
      // particular condition and returns the SingerId
      // and FullName column of the deleted records using
      // ‘THEN RETURN SingerId, FullName’.
      // It is also possible to return all columns of all the
      // deleted records by using ‘THEN RETURN *’.
      dbClient
          .readWritreadWriteTransaction     .run(
              transaction -> {
                String sql =
                    "DELETE FROM Singers WHERE FirstName = 'Alice' THEN RETURN SingerId, FullName";

                // readWriteTransaction.executeQuery(..) API should be used for executing
                // DML statements with RETURNING clause.
                try (ResultSeResultSetet = transaction.executeQuery(StatemenStatement)) {
                  while (resultSet.next()) {
                    System.out.printf("%d %s\n", resultSet.getLong(0), resultSet.getString(1));
                  }
                  System.out.printf(
                      "Deleted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
                }
                return null;
              });
    }
  }
}

Node.js

// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

function deleteUsingDmlReturning(instanceId, databaseId) {
  // Gets a reference to a Cloud Spanner instance and database.
  const instance = spanner.instance(instanceId);
  const database = instance.database(databaseId);

  database.runTransaction(async (err, transaction) => {
    if (err) {
      console.error(err);
      return;
    }
    try {
      const [rows, stats] = await transaction.run({
        sql: 'DELETE FROM Singers WHERE SingerId = 18 THEN RETURN FullName',
      });

      const rowCount = Math.floor(stats[stats.rowCount]);
      console.log(
        `Successfully deleted ${rowCount} record from the Singers table.`,
      );
      rows.forEach(row => {
        console.log(row.toJSON().FullName);
      });

      await transaction.commit();
    } catch (err) {
      console.error('ERROR:', err);
    } finally {
      // Close the database when finished.
      database.close();
    }
  });
}
deleteUsingDmlReturning(instanceId, databaseId);

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Delete data from the given database using DML returning.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function delete_dml_returning(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $transaction = $database->transaction();

    // Delete records from SINGERS table satisfying a particular condition and
    // returns the SingerId and FullName column of the deleted records using
    // 'THEN RETURN SingerId, FullName'. It is also possible to return all columns
    //  of all the deleted records by using 'THEN RETURN *'.

    $result = $transaction->execute(
        "DELETE FROM Singers WHERE FirstName = 'Alice' "
        . 'THEN RETURN SingerId, FullName',
    );
    foreach ($result->rows() as $row) {
        printf(
            '%d %s.' . PHP_EOL,
            $row['SingerId'],
            $row['FullName']
        );
    }
    printf(
        'Deleted row(s) count: %d' . PHP_EOL,
        $result->stats()['rowCountExact']
    );
    $transaction->commit();
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

# Delete records from SINGERS table satisfying a
# particular condition and returns the SingerId
# and FullName column of the deleted records using
# 'THEN RETURN SingerId, FullName'.
# It is also possible to return all columns of all the
# deleted records by using 'THEN RETURN *'.
def delete_singers(transaction):
    results = transaction.execute_sql(
        "DELETE FROM Singers WHERE FirstName = 'David' "
        "THEN RETURN SingerId, FullName"
    )
    for result in results:
        print("SingerId: {}, FullName: {}".format(*result))
    print("{} record(s) deleted.".format(results.stats.row_count_exact))

database.run_in_transaction(delete_singers)

Ruby

require "google/cloud/spanner"

##
# This is a snippet for showcasing how to use DML return feature with delete
# operation.
#
# @param project_id  [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_delete_dml_returning project_id:, instance_id:, database_id:
  spanner = Google::Cloud::Spanner.new project: project_id
  client = spanner.client instance_id, database_id

  client.transaction do |transaction|
    # Delete records from SINGERS table satisfying a particular condition and
    # returns the SingerId and FullName column of the deleted records using
    # ‘THEN RETURN SingerId, FullName’.
    # It is also possible to return all columns of all the deleted records
    # by using ‘THEN RETURN *’.
    results = transaction.execute_query "DELETE FROM Singers WHERE FirstName = 'Alice' THEN RETURN SingerId, FullName"
    results.rows.each do |row|
      puts "Deleted singer with SingerId: #{row[:SingerId]}, FullName: #{row[:FullName]}"
    end
    puts "Deleted row(s) count: #{results.row_count}"
  end
end

PostgreSQL

C++

void DeleteUsingDmlReturning(google::cloud::spanner::Client client) {
  // Delete records from SINGERS table satisfying a particular condition
  // and return the SingerId and FullName column of the deleted records
  // using `RETURNING SingerId, FullName'.
  auto commit = client.Commit(
      [&client](google::cloud::spanner::Transaction txn)
          -> google::cloud::StatusOr<google::cloud::spanner::Mutations> {
        auto sql = google::cloud::spanner::SqlStatement(R"""(
            DELETE FROM Singers
              WHERE FirstName = 'Alice'
              RETURNING SingerId, FullName
        )""");
        using RowType = std::tuple<std::int64_t, std::string>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(sql));
        for (auto& row : google::cloud::spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "SingerId: " << std::get<0>(*row) << " ";
          std::cout << "FullName: " << std::get<1>(*row) << "\n";
        }
        std::cout << "Deleted row(s) count: " << rows.RowsModified() << "\n";
        return google::cloud::spanner::Mutations{};
      });
  if (!commit) throw std::move(commit).status();
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Threading.Tasks;

public class DeleteUsingDmlReturningAsyncPostgresSample
{
    public async Task<List<string>> DeleteUsingDmlReturningAsyncPostgres(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        // Delete records from SINGERS table satisfying a
        // particular condition and return the SingerId
        // and FullName column of the deleted records using
        // 'RETURNING SingerId, FullName'.
        // It is also possible to return all columns of all the
        // deleted records by using 'RETURNING *'.
        using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE FirstName = 'Lata' RETURNING SingerId, FullName");
        var reader = await cmd.ExecuteReaderAsync();
        var deletedSingerNames = new List<string>();
        while (await reader.ReadAsync())
        {
            deletedSingerNames.Add(reader.GetFieldValue<string>("fullname"));
        }

        Console.WriteLine($"{deletedSingerNames.Count} row(s) deleted...");
        return deletedSingerNames;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func pgDeleteUsingDMLReturning(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	// Delete records from SINGERS table satisfying a
	// particular condition and returns the SingerId
	// and FullName column of the deleted records using
	// 'RETURNING SingerId, FullName'.
	// It is also possible to return all columns of all the
	// deleted records by using 'RETURNING *'.
	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmt := spanner.Statement{
			SQL: `DELETE FROM Singers WHERE FirstName = 'Alice'
			        RETURNING SingerId, FullName`,
		}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()
		for {
			row, err := iter.Next()
			if err == iterator.Done {
				break
			}
			if err != nil {
				return err
			}
			var (
				singerID int64
				fullName string
			)
			if err := row.Columns(&singerID, &fullName); err != nil {
				return err
			}
			fmt.Fprintf(w, "%d %s\n", singerID, fullName)
		}
		fmt.Fprintf(w, "%d record(s) deleted.\n", iter.RowCount)
		return nil
	})
	return err
}

Java


import com.google.cloud.spanner.DatabaseClient;
import com.google.cloud.spanner.DatabaseId;
import com.google.cloud.spanner.ResultSet;
import com.google.cloud.spanner.Spanner;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.spanner.Statement;

public class PgDeleteUsingDmlReturningSample {

  static void deleteUsingDmlReturningSample() {
    // TODO(developer): Replace these variables before running the sample.
    final String projectId = "my-project";
    final String instanceId = "my-instance";
    final String databaseId = "my-database";
    deleteUsingDmlReturningSample(projectId, instanceId, databaseId);
  }

  static void deleteUsingDmlReturningSample(
      String projectId, String instanceId, String databaseId) {
    try (Spanner spanner =
        SpannerOptions.newBuilder()
            .setProjectId(projectId)
            .build()
            .getService()) {
      final DatabaseClient dbClient =
          spanner.getDatabaseClient(DatabaseId.of(projectId, instanceId, databaseId));
      // Delete records from SINGERS table satisfying a
      // particular condition and returns the SingerId
      // and FullName column of the deleted records using
      // ‘RETURNING SingerId, FullName’.
      // It is also possible to return all columns of all the
      // deleted records by using ‘RETURNING *’.
      dbClient
          .readWritreadWriteTransaction     .run(
              transaction -> {
                String sql =
                    "DELETE FROM Singers WHERE FirstName = 'Alice' RETURNING SingerId, FullName";

                // readWriteTransaction.executeQuery(..) API should be used for executing
                // DML statements with RETURNING clause.
                try (ResultSeResultSetet = transaction.executeQuery(StatemenStatement)) {
                  while (resultSet.next()) {
                    System.out.printf("%d %s\n", resultSet.getLong(0), resultSet.getString(1));
                  }
                  System.out.printf(
                      "Deleted row(s) count: %d\n", resultSet.getStats().getRowCountExact());
                }
                return null;
              });
    }
  }
}

Node.js

// Imports the Google Cloud client library.
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

function pgDeleteUsingDmlReturning(instanceId, databaseId) {
  // Gets a reference to a Cloud Spanner instance and database.
  const instance = spanner.instance(instanceId);
  const database = instance.database(databaseId);

  database.runTransaction(async (err, transaction) => {
    if (err) {
      console.error(err);
      return;
    }
    try {
      const [rows, stats] = await transaction.run({
        sql: 'DELETE FROM Singers WHERE SingerId = 18 RETURNING FullName',
      });

      const rowCount = Math.floor(stats[stats.rowCount]);
      console.log(
        `Successfully deleted ${rowCount} record from the Singers table.`,
      );
      rows.forEach(row => {
        console.log(row.toJSON().fullname);
      });

      await transaction.commit();
    } catch (err) {
      console.error('ERROR:', err);
    } finally {
      // Close the database when finished.
      database.close();
    }
  });
}
pgDeleteUsingDmlReturning(instanceId, databaseId);

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Delete data from the given postgresql database using DML returning.
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function pg_delete_dml_returning(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $transaction = $database->transaction();

    // Delete records from SINGERS table satisfying a particular condition and
    // returns the SingerId and FullName column of the deleted records using
    // ‘RETURNING SingerId, FullName’. It is also possible to return all columns
    //  of all the deleted records by using ‘RETURNING *’.

    $result = $transaction->execute(
        "DELETE FROM Singers WHERE FirstName = 'Alice' "
        . 'RETURNING SingerId, FullName',
    );
    foreach ($result->rows() as $row) {
        printf(
            '%d %s.' . PHP_EOL,
            $row['singerid'],
            $row['fullname']
        );
    }
    printf(
        'Deleted row(s) count: %d' . PHP_EOL,
        $result->stats()['rowCountExact']
    );
    $transaction->commit();
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

# Delete records from SINGERS table satisfying a
# particular condition and returns the SingerId
# and FullName column of the deleted records using
# 'RETURNING SingerId, FullName'.
# It is also possible to return all columns of all the
# deleted records by using 'RETURNING *'.
def delete_singers(transaction):
    results = transaction.execute_sql(
        "DELETE FROM Singers WHERE FirstName = 'David' "
        "RETURNING SingerId, FullName"
    )
    for result in results:
        print("SingerId: {}, FullName: {}".format(*result))
    print("{} record(s) deleted.".format(results.stats.row_count_exact))

database.run_in_transaction(delete_singers)

Ruby

require "google/cloud/spanner"

##
# This is a snippet for showcasing how to use DML return feature with delete
# operation in PostgreSql.
#
# @param project_id  [String] The ID of the Google Cloud project.
# @param instance_id [String] The ID of the spanner instance.
# @param database_id [String] The ID of the database.
#
def spanner_postgresql_delete_dml_returning project_id:, instance_id:, database_id:
  spanner = Google::Cloud::Spanner.new project: project_id
  client = spanner.client instance_id, database_id

  client.transaction do |transaction|
    # Delete records from SINGERS table satisfying a particular condition and
    # returns the SingerId and FullName column of the deleted records using
    # ‘RETURNING SingerId, FullName’.
    # It is also possible to return all columns of all the deleted records
    # by using ‘RETURNING *’.
    results = transaction.execute_query "DELETE FROM singers WHERE firstname = 'Alice' RETURNING SingerId, FullName"
    results.rows.each do |row|
      puts "Deleted singer with SingerId: #{row[:singerid]}, FullName: #{row[:fullname]}"
    end
    puts "Deleted row(s) count: #{results.row_count}"
  end
end

Leer datos escritos en la misma transacción

Los cambios que hagas con instrucciones DML se podrán ver en las instrucciones posteriores de la misma transacción. Esto es diferente de usar mutaciones, donde los cambios no se ven hasta que se confirma la transacción.

Spanner comprueba las restricciones después de cada instrucción DML. Esto es diferente de usar mutaciones, donde Spanner almacena en búfer las mutaciones en el cliente hasta que se confirman y comprueba las restricciones en el momento de la confirmación. Al evaluar las restricciones después de cada instrucción, Spanner puede garantizar que los datos que devuelve una instrucción DML sean coherentes con el esquema.

En el siguiente ejemplo se actualiza una fila de la tabla Singers y, a continuación, se ejecuta una instrucción SELECT para imprimir los nuevos valores.

C++

void DmlWriteThenRead(google::cloud::spanner::Client client) {
  namespace spanner = ::google::cloud::spanner;
  using ::google::cloud::StatusOr;

  auto commit_result = client.Commit(
      [&client](spanner::Transaction txn) -> StatusOr<spanner::Mutations> {
        auto insert = client.ExecuteDml(
            txn, spanner::SqlStatement(
                     "INSERT INTO Singers (SingerId, FirstName, LastName)"
                     "  VALUES (11, 'Timothy', 'Campbell')"));
        if (!insert) return std::move(insert).status();
        // Read newly inserted record.
        spanner::SqlStatement select(
            "SELECT FirstName, LastName FROM Singers where SingerId = 11");
        using RowType = std::tuple<std::string, std::string>;
        auto rows = client.ExecuteQuery(std::move(txn), std::move(select));
        // Note: This mutator might be re-run, or its effects discarded, so
        // changing non-transactional state (e.g., by producing output) is,
        // in general, not something to be imitated.
        for (auto const& row : spanner::StreamOf<RowType>(rows)) {
          if (!row) return std::move(row).status();
          std::cout << "FirstName: " << std::get<0>(*row) << "\t";
          std::cout << "LastName: " << std::get<1>(*row) << "\n";
        }
        return spanner::Mutations{};
      });
  if (!commit_result) throw std::move(commit_result).status();
  std::cout << "Write then read succeeded [spanner_dml_write_then_read]\n";
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class WriteAndReadUsingDmlCoreAsyncSample
{
    public async Task<int> WriteAndReadUsingDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var createDmlCmd = connection.CreateDmlCommand(@"INSERT Singers (SingerId, FirstName, LastName) VALUES (11, 'Timothy', 'Campbell')");
        int rowCount = await createDmlCmd.ExecuteNonQueryAsync();
        Console.WriteLine($"{rowCount} row(s) inserted...");

        // Read newly inserted record.
        using var createSelectCmd = connection.CreateSelectCommand(@"SELECT FirstName, LastName FROM Singers WHERE SingerId = 11");
        using var reader = await createSelectCmd.ExecuteReaderAsync();
        while (await reader.ReadAsync())
        {
            Console.WriteLine($"{reader.GetFieldValue<string>("FirstName")}  {reader.GetFieldValue<string>("LastName")}");
        }
        return rowCount;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
	"google.golang.org/api/iterator"
)

func writeAndReadUsingDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		// Insert Record
		stmt := spanner.Statement{
			SQL: `INSERT Singers (SingerId, FirstName, LastName)
				VALUES (11, 'Timothy', 'Campbell')`,
		}
		rowCount, err := txn.Update(ctx, stmt)
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "%d record(s) inserted.\n", rowCount)

		// Read newly inserted record
		stmt = spanner.Statement{SQL: `SELECT FirstName, LastName FROM Singers WHERE SingerId = 11`}
		iter := txn.Query(ctx, stmt)
		defer iter.Stop()

		for {
			row, err := iter.Next()
			if err == iterator.Done || err != nil {
				break
			}
			var firstName, lastName string
			if err := row.ColumnByName("FirstName", &firstName); err != nil {
				return err
			}
			if err := row.ColumnByName("LastName", &lastName); err != nil {
				return err
			}
			fmt.Fprintf(w, "Found record name with %s, %s", firstName, lastName)
		}
		return err
	})
	return err
}

Java

static void writeAndReadUsingDml(DatabaseClient dbClient) {
  dbClient
      .readWriteTransaction()
      .run(transaction -> {
        // Insert record.
        String sql =
            "INSERT INTO Singers (SingerId, FirstName, LastName) "
                + " VALUES (11, 'Timothy', 'Campbell')";
        long rowCount = transaction.executeUpdate(Statement.of(sql));
        System.out.printf("%d record inserted.\n", rowCount);
        // Read newly inserted record.
        sql = "SELECT FirstName, LastName FROM Singers WHERE SingerId = 11";
        // We use a try-with-resource block to automatically release resources held by
        // ResultSet.
        try (ResultSet resultSet = transaction.executeQuery(Statement.of(sql))) {
          while (resultSet.next()) {
            System.out.printf(
                "%s %s\n",
                resultSet.getString("FirstName"), resultSet.getString("LastName"));
          }
        }
        return null;
      });
}

Node.js

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

database.runTransaction(async (err, transaction) => {
  if (err) {
    console.error(err);
    return;
  }
  try {
    await transaction.runUpdate({
      sql: `INSERT Singers (SingerId, FirstName, LastName)
        VALUES (11, 'Timothy', 'Campbell')`,
    });

    const [rows] = await transaction.run({
      sql: 'SELECT FirstName, LastName FROM Singers',
    });
    rows.forEach(row => {
      const json = row.toJSON();
      console.log(`${json.FirstName} ${json.LastName}`);
    });

    await transaction.commit();
  } catch (err) {
    console.error('ERROR:', err);
  } finally {
    // Close the database when finished.
    database.close();
  }
});

PHP

use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;

/**
 * Writes then reads data inside a Transaction with a DML statement.
 *
 * The database and table must already exist and can be created using
 * `create_database`.
 * Example:
 * ```
 * insert_data($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function write_read_with_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $database->runTransaction(function (Transaction $t) {
        $rowCount = $t->executeUpdate(
            'INSERT Singers (SingerId, FirstName, LastName) '
            . " VALUES (11, 'Timothy', 'Campbell')");

        printf('Inserted %d row(s).' . PHP_EOL, $rowCount);

        $results = $t->execute('SELECT FirstName, LastName FROM Singers WHERE SingerId = 11');

        foreach ($results as $row) {
            printf('%s %s' . PHP_EOL, $row['FirstName'], $row['LastName']);
        }

        $t->commit();
    });
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

def write_then_read(transaction):
    # Insert record.
    row_ct = transaction.execute_update(
        "INSERT INTO Singers (SingerId, FirstName, LastName) "
        " VALUES (11, 'Timothy', 'Campbell')"
    )
    print("{} record(s) inserted.".format(row_ct))

    # Read newly inserted record.
    results = transaction.execute_sql(
        "SELECT FirstName, LastName FROM Singers WHERE SingerId = 11"
    )
    for result in results:
        print("FirstName: {}, LastName: {}".format(*result))

database.run_in_transaction(write_then_read)

Ruby

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id
row_count = 0

client.transaction do |transaction|
  row_count = transaction.execute_update(
    "INSERT INTO Singers (SingerId, FirstName, LastName) VALUES (11, 'Timothy', 'Campbell')"
  )
  puts "#{row_count} record updated."
  transaction.execute("SELECT FirstName, LastName FROM Singers WHERE SingerId = 11").rows.each do |row|
    puts "#{row[:FirstName]} #{row[:LastName]}"
  end
end

Obtener el plan de consulta

Puedes obtener un plan de consulta mediante la consola de Google Cloud , las bibliotecas de cliente y la herramienta de línea de comandos gcloud.

Usar DML particionado

DML particionado se ha diseñado para realizar actualizaciones y eliminaciones en bloque, sobre todo para tareas de limpieza y relleno periódicas.

Ejecutar instrucciones con Google Cloud CLI

Para ejecutar una declaración de DML particionado, usa el comando gcloud spanner databases execute-sql con la opción --enable-partitioned-dml. En el siguiente ejemplo se actualizan las filas de la tabla Albums.

gcloud spanner databases execute-sql example-db \
    --instance=test-instance --enable-partitioned-dml \
    --sql='UPDATE Albums SET MarketingBudget = 0 WHERE MarketingBudget IS NULL'

Modificar datos con la biblioteca de cliente

En el siguiente ejemplo de código se actualiza la columna MarketingBudget de la tabla Albums.

C++

Usa la función ExecutePartitionedDml() para ejecutar una instrucción DML con particiones.

void DmlPartitionedUpdate(google::cloud::spanner::Client client) {
  namespace spanner = ::google::cloud::spanner;
  auto result = client.ExecutePartitionedDml(
      spanner::SqlStatement("UPDATE Albums SET MarketingBudget = 100000"
                            "  WHERE SingerId > 1"));
  if (!result) throw std::move(result).status();
  std::cout << "Updated at least " << result->row_count_lower_bound
            << " row(s) [spanner_dml_partitioned_update]\n";
}

C#

Usa el método ExecutePartitionedUpdateAsync() para ejecutar una declaración de DML particionado.


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class UpdateUsingPartitionedDmlCoreAsyncSample
{
    public async Task<long> UpdateUsingPartitionedDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var cmd = connection.CreateDmlCommand("UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1");
        long rowCount = await cmd.ExecutePartitionedUpdateAsync();

        Console.WriteLine($"{rowCount} row(s) updated...");
        return rowCount;
    }
}

Go

Usa el método PartitionedUpdate() para ejecutar una declaración de DML particionado.


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func updateUsingPartitionedDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	stmt := spanner.Statement{SQL: "UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1"}
	rowCount, err := client.PartitionedUpdate(ctx, stmt)
	if err != nil {
		return err
	}
	fmt.Fprintf(w, "%d record(s) updated.\n", rowCount)
	return nil
}

Java

Usa el método executePartitionedUpdate() para ejecutar una declaración de DML particionado.

static void updateUsingPartitionedDml(DatabaseClient dbClient) {
  String sql = "UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1";
  long rowCount = dbClient.executePartitionedUpdate(Statement.of(sql));
  System.out.printf("%d records updated.\n", rowCount);
}

Node.js

Usa el método runPartitionedUpdate() para ejecutar una declaración de DML particionado.

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

try {
  const [rowCount] = await database.runPartitionedUpdate({
    sql: 'UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1',
  });
  console.log(`Successfully updated ${rowCount} records.`);
} catch (err) {
  console.error('ERROR:', err);
} finally {
  // Close the database when finished.
  database.close();
}

PHP

Usa el método executePartitionedUpdate() para ejecutar una declaración de DML particionado.

use Google\Cloud\Spanner\SpannerClient;

/**
 * Updates sample data in the database by partition with a DML statement.
 *
 * This updates the `MarketingBudget` column which must be created before
 * running this sample. You can add the column by running the `add_column`
 * sample or by running this DDL statement against your database:
 *
 *     ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
 *
 * Example:
 * ```
 * update_data($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function update_data_with_partitioned_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $rowCount = $database->executePartitionedUpdate(
        'UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1'
    );

    printf('Updated %d row(s).' . PHP_EOL, $rowCount);
}

Python

Usa el método execute_partitioned_dml() para ejecutar una declaración de DML particionado.

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

row_ct = database.execute_partitioned_dml(
    "UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1"
)

print("{} records updated.".format(row_ct))

Ruby

Usa el método execute_partitioned_update() para ejecutar una declaración de DML particionado.

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id

row_count = client.execute_partition_update(
  "UPDATE Albums SET MarketingBudget = 100000 WHERE SingerId > 1"
)

puts "#{row_count} records updated."

En el siguiente ejemplo de código se eliminan filas de la tabla Singers en función de la columna SingerId.

C++

void DmlPartitionedDelete(google::cloud::spanner::Client client) {
  namespace spanner = ::google::cloud::spanner;
  auto result = client.ExecutePartitionedDml(
      spanner::SqlStatement("DELETE FROM Singers WHERE SingerId > 10"));
  if (!result) throw std::move(result).status();
  std::cout << "Deleted at least " << result->row_count_lower_bound
            << " row(s) [spanner_dml_partitioned_delete]\n";
}

C#


using Google.Cloud.Spanner.Data;
using System;
using System.Threading.Tasks;

public class DeleteUsingPartitionedDmlCoreAsyncSample
{
    public async Task<long> DeleteUsingPartitionedDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        using var cmd = connection.CreateDmlCommand("DELETE FROM Singers WHERE SingerId > 10");
        long rowCount = await cmd.ExecutePartitionedUpdateAsync();

        Console.WriteLine($"{rowCount} row(s) deleted...");
        return rowCount;
    }
}

Go


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func deleteUsingPartitionedDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	stmt := spanner.Statement{SQL: "DELETE FROM Singers WHERE SingerId > 10"}
	rowCount, err := client.PartitionedUpdate(ctx, stmt)
	if err != nil {
		return err

	}
	fmt.Fprintf(w, "%d record(s) deleted.", rowCount)
	return nil
}

Java

static void deleteUsingPartitionedDml(DatabaseClient dbClient) {
  String sql = "DELETE FROM Singers WHERE SingerId > 10";
  long rowCount = dbClient.executePartitionedUpdate(Statement.of(sql));
  System.out.printf("%d records deleted.\n", rowCount);
}

Node.js

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

try {
  const [rowCount] = await database.runPartitionedUpdate({
    sql: 'DELETE FROM Singers WHERE SingerId > 10',
  });
  console.log(`Successfully deleted ${rowCount} records.`);
} catch (err) {
  console.error('ERROR:', err);
} finally {
  // Close the database when finished.
  database.close();
}

PHP

use Google\Cloud\Spanner\SpannerClient;

/**
 * Delete sample data in the database by partition with a DML statement.
 *
 * This updates the `MarketingBudget` column which must be created before
 * running this sample. You can add the column by running the `add_column`
 * sample or by running this DDL statement against your database:
 *
 *     ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
 *
 * Example:
 * ```
 * update_data($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function delete_data_with_partitioned_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $rowCount = $database->executePartitionedUpdate(
        'DELETE FROM Singers WHERE SingerId > 10'
    );

    printf('Deleted %d row(s).' . PHP_EOL, $rowCount);
}

Python

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

row_ct = database.execute_partitioned_dml("DELETE FROM Singers WHERE SingerId > 10")

print("{} record(s) deleted.".format(row_ct))

Ruby

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id

row_count = client.execute_partition_update(
  "DELETE FROM Singers WHERE SingerId > 10"
)

puts "#{row_count} records deleted."

Usar DML por lotes

Si quieres evitar la latencia adicional que se produce al enviar varias solicitudes en serie, usa DML por lotes para enviar varias instrucciones INSERT, UPDATE o DELETE en una sola transacción:

C++

Usa la función ExecuteBatchDml() para ejecutar una lista de instrucciones de DML.

void DmlBatchUpdate(google::cloud::spanner::Client client) {
  namespace spanner = ::google::cloud::spanner;

  auto commit_result =
      client.Commit([&client](spanner::Transaction const& txn)
                        -> google::cloud::StatusOr<spanner::Mutations> {
        std::vector<spanner::SqlStatement> statements = {
            spanner::SqlStatement("INSERT INTO Albums"
                                  " (SingerId, AlbumId, AlbumTitle,"
                                  " MarketingBudget)"
                                  " VALUES (1, 3, 'Test Album Title', 10000)"),
            spanner::SqlStatement("UPDATE Albums"
                                  " SET MarketingBudget = MarketingBudget * 2"
                                  "  WHERE SingerId = 1 and AlbumId = 3")};
        auto result = client.ExecuteBatchDml(txn, statements);
        if (!result) return std::move(result).status();
        // Note: This mutator might be re-run, or its effects discarded, so
        // changing non-transactional state (e.g., by producing output) is,
        // in general, not something to be imitated.
        for (std::size_t i = 0; i < result->stats.size(); ++i) {
          std::cout << result->stats[i].row_count << " rows affected"
                    << " for the statement " << (i + 1) << ".\n";
        }
        // Batch operations may have partial failures, in which case
        // ExecuteBatchDml returns with success, but the application should
        // verify that all statements completed successfully
        if (!result->status.ok()) return result->status;
        return spanner::Mutations{};
      });
  if (!commit_result) throw std::move(commit_result).status();
  std::cout << "Update was successful [spanner_dml_batch_update]\n";
}

C#

Usa el método connection.CreateBatchDmlCommand() para crear tu comando por lotes, el método Add para añadir instrucciones DML y el método ExecuteNonQueryAsync() para ejecutar las instrucciones.


using Google.Cloud.Spanner.Data;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Threading.Tasks;

public class UpdateUsingBatchDmlCoreAsyncSample
{
    public async Task<int> UpdateUsingBatchDmlCoreAsync(string projectId, string instanceId, string databaseId)
    {
        string connectionString = $"Data Source=projects/{projectId}/instances/{instanceId}/databases/{databaseId}";

        using var connection = new SpannerConnection(connectionString);
        await connection.OpenAsync();

        SpannerBatchCommand cmd = connection.CreateBatchDmlCommand();

        cmd.Add("INSERT INTO Albums (SingerId, AlbumId, AlbumTitle, MarketingBudget) VALUES (1, 3, 'Test Album Title', 10000)");

        cmd.Add("UPDATE Albums SET MarketingBudget = MarketingBudget * 2 WHERE SingerId = 1 and AlbumId = 3");

        IEnumerable<long> affectedRows = await cmd.ExecuteNonQueryAsync();

        Console.WriteLine($"Executed {affectedRows.Count()} " + "SQL statements using Batch DML.");
        return affectedRows.Count();
    }
}

Go

Usa el método BatchUpdate() para ejecutar una matriz de objetos Statement de DML.


import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/spanner"
)

func updateUsingBatchDML(w io.Writer, db string) error {
	ctx := context.Background()
	client, err := spanner.NewClient(ctx, db)
	if err != nil {
		return err
	}
	defer client.Close()

	_, err = client.ReadWriteTransaction(ctx, func(ctx context.Context, txn *spanner.ReadWriteTransaction) error {
		stmts := []spanner.Statement{
			{SQL: `INSERT INTO Albums
				(SingerId, AlbumId, AlbumTitle, MarketingBudget)
				VALUES (1, 3, 'Test Album Title', 10000)`},
			{SQL: `UPDATE Albums
				SET MarketingBudget = MarketingBudget * 2
				WHERE SingerId = 1 and AlbumId = 3`},
		}
		rowCounts, err := txn.BatchUpdate(ctx, stmts)
		if err != nil {
			return err
		}
		fmt.Fprintf(w, "Executed %d SQL statements using Batch DML.\n", len(rowCounts))
		return nil
	})
	return err
}

Java

Usa el método transaction.batchUpdate() para ejecutar un ArrayList de varios objetos Statement de DML.

static void updateUsingBatchDml(DatabaseClient dbClient) {
  dbClient
      .readWriteTransaction()
      .run(transaction -> {
        List<Statement> stmts = new ArrayList<Statement>();
        String sql =
            "INSERT INTO Albums "
                + "(SingerId, AlbumId, AlbumTitle, MarketingBudget) "
                + "VALUES (1, 3, 'Test Album Title', 10000) ";
        stmts.add(Statement.of(sql));
        sql =
            "UPDATE Albums "
                + "SET MarketingBudget = MarketingBudget * 2 "
                + "WHERE SingerId = 1 and AlbumId = 3";
        stmts.add(Statement.of(sql));
        long[] rowCounts;
        try {
          rowCounts = transaction.batchUpdate(stmts);
        } catch (SpannerBatchUpdateException e) {
          rowCounts = e.getUpdateCounts();
        }
        for (int i = 0; i < rowCounts.length; i++) {
          System.out.printf("%d record updated by stmt %d.\n", rowCounts[i], i);
        }
        return null;
      });
}

Node.js

Usa transaction.batchUpdate() para ejecutar una lista de instrucciones DML.

// Imports the Google Cloud client library
const {Spanner} = require('@google-cloud/spanner');

/**
 * TODO(developer): Uncomment the following lines before running the sample.
 */
// const projectId = 'my-project-id';
// const instanceId = 'my-instance';
// const databaseId = 'my-database';

// Creates a client
const spanner = new Spanner({
  projectId: projectId,
});

// Gets a reference to a Cloud Spanner instance and database
const instance = spanner.instance(instanceId);
const database = instance.database(databaseId);

const insert = {
  sql: `INSERT INTO Albums (SingerId, AlbumId, AlbumTitle, MarketingBudget)
    VALUES (1, 3, "Test Album Title", 10000)`,
};

const update = {
  sql: `UPDATE Albums SET MarketingBudget = MarketingBudget * 2
    WHERE SingerId = 1 and AlbumId = 3`,
};

const dmlStatements = [insert, update];

try {
  await database.runTransactionAsync(async transaction => {
    const [rowCounts] = await transaction.batchUpdate(dmlStatements);
    await transaction.commit();
    console.log(
      `Successfully executed ${rowCounts.length} SQL statements using Batch DML.`,
    );
  });
} catch (err) {
  console.error('ERROR:', err);
  throw err;
} finally {
  // Close the database when finished.
  database.close();
}

PHP

Usa executeUpdateBatch() para crear una lista de instrucciones DML y, a continuación, usa commit() para ejecutar las instrucciones.

use Google\Cloud\Spanner\SpannerClient;
use Google\Cloud\Spanner\Transaction;

/**
 * Updates sample data in the database with Batch DML.
 *
 * This requires the `MarketingBudget` column which must be created before
 * running this sample. You can add the column by running the `add_column`
 * sample or by running this DDL statement against your database:
 *
 *     ALTER TABLE Albums ADD COLUMN MarketingBudget INT64
 *
 * Example:
 * ```
 * update_data_with_batch_dml($instanceId, $databaseId);
 * ```
 *
 * @param string $instanceId The Spanner instance ID.
 * @param string $databaseId The Spanner database ID.
 */
function update_data_with_batch_dml(string $instanceId, string $databaseId): void
{
    $spanner = new SpannerClient();
    $instance = $spanner->instance($instanceId);
    $database = $instance->database($databaseId);

    $batchDmlResult = $database->runTransaction(function (Transaction $t) {
        $result = $t->executeUpdateBatch([
            [
                'sql' => 'INSERT INTO Albums '
                . '(SingerId, AlbumId, AlbumTitle, MarketingBudget) '
                . "VALUES (1, 3, 'Test Album Title', 10000)"
            ],
            [
                'sql' => 'UPDATE Albums '
                . 'SET MarketingBudget = MarketingBudget * 2 '
                . 'WHERE SingerId = 1 and AlbumId = 3'
            ],
        ]);
        $t->commit();
        $rowCounts = count($result->rowCounts());
        printf('Executed %s SQL statements using Batch DML.' . PHP_EOL,
            $rowCounts);
    });
}

Python

Usa transaction.batch_update() para ejecutar varias cadenas de instrucciones DML.

from google.rpc.code_pb2 import OK

# instance_id = "your-spanner-instance"
# database_id = "your-spanner-db-id"

spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)
database = instance.database(database_id)

insert_statement = (
    "INSERT INTO Albums "
    "(SingerId, AlbumId, AlbumTitle, MarketingBudget) "
    "VALUES (1, 3, 'Test Album Title', 10000)"
)

update_statement = (
    "UPDATE Albums "
    "SET MarketingBudget = MarketingBudget * 2 "
    "WHERE SingerId = 1 and AlbumId = 3"
)

def update_albums(transaction):
    status, row_cts = transaction.batch_update([insert_statement, update_statement])

    if status.code != OK:
        # Do handling here.
        # Note: the exception will still be raised when
        # `commit` is called by `run_in_transaction`.
        return

    print("Executed {} SQL statements using Batch DML.".format(len(row_cts)))

database.run_in_transaction(update_albums)

Ruby

Usa transaction.batch_update para ejecutar varias cadenas de instrucciones DML.

# project_id  = "Your Google Cloud project ID"
# instance_id = "Your Spanner instance ID"
# database_id = "Your Spanner database ID"

require "google/cloud/spanner"

spanner = Google::Cloud::Spanner.new project: project_id
client  = spanner.client instance_id, database_id

row_counts = nil
client.transaction do |transaction|
  row_counts = transaction.batch_update do |b|
    b.batch_update(
      "INSERT INTO Albums " \
      "(SingerId, AlbumId, AlbumTitle, MarketingBudget) " \
      "VALUES (1, 3, 'Test Album Title', 10000)"
    )
    b.batch_update(
      "UPDATE Albums " \
      "SET MarketingBudget = MarketingBudget * 2 " \
      "WHERE SingerId = 1 and AlbumId = 3"
    )
  end
end

statement_count = row_counts.count

puts "Executed #{statement_count} SQL statements using Batch DML."

Insertar, actualizar y eliminar datos con el lenguaje de manipulación de datos (DML) Organízate con las colecciones Guarda y clasifica el contenido según tus preferencias.

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Insertar, actualizar y eliminar datos con el lenguaje de manipulación de datos (DML)