Comienza a usar Spanner y PGAdapter

---

Objetivos

En este instructivo, se explican los siguientes pasos para usar Spanner Proxy local de PGAdapter para controladores de PostgreSQL:

• Crea una base de datos y una instancia de Spanner.
• Escribe, lee y ejecuta consultas de SQL sobre datos en la base de datos.
• Actualiza el esquema de la base de datos.
• Actualiza los datos mediante una transacción de lectura y escritura.
• Agrega un índice secundario a la base de datos.
• Usa el índice para leer y ejecutar consultas de SQL sobre datos.
• Recupera datos con una transacción de solo lectura.

Costos

En este instructivo, se usa Spanner, que es un componente facturable del en Google Cloud. Para obtener información sobre el costo de usar Spanner, consulta Precios.

Antes de comenzar

Completa los pasos descritos en Configuración, que abarcan la creación y configuración de un proyecto de Google Cloud predeterminado, la facturación, la habilitación de la API de Cloud Spanner y la configuración de OAuth 2.0 para obtener credenciales de autenticación para usar la API de Cloud Spanner.

En especial, asegúrate de ejecutar gcloud auth application-default login para configurar tu entorno de desarrollo local con credenciales de autenticación.

Nota: Si no planeas conservar los recursos que creaste en este instructivo, considera crear un proyecto nuevo de Google Cloud en lugar de seleccionar uno existente. Cuando termines el instructivo, puedes borrar el proyecto y quitar todos los recursos asociados con él.

Prepara tu entorno local de PGAdapter

Puedes usar controladores de PostgreSQL junto con PGAdapter para conectarse a Spanner. PGAdapter es un proxy local que traduce el protocolo de red de PostgreSQL al Protocolo gRPC de Spanner.

Sugerencia: Consulta Comparaciones de latencia para comparativas que comparan la latencia de PGAdapter Bibliotecas cliente de Spanner.

PGAdapter requiere Java o Docker para ejecutarse.

1. Instala una de las siguientes opciones en tu máquina de desarrollo si aún no tienes ninguna de ellas:

   • JDK de Java 8 (descarga).
   • Docker (descarga).

2. Clona el repositorio de la app de muestra en tu máquina local:

   git clone https://github.com/GoogleCloudPlatform/pgadapter.git
   

3. Ve al directorio que contiene el código de muestra de Spanner:

   psql

   cd pgadapter/samples/snippets/psql-snippets
   

   Java

   cd pgadapter/samples/snippets/java-snippets
   mvn package -DskipTests
   

   Go

   cd pgadapter/samples/snippets/golang-snippets
   

   Node.js

   cd pgadapter/samples/snippets/nodejs-snippets
   npm install
   

   Python

   cd pgadapter/samples/snippets/python-snippets
   python -m venv ./venv
   pip install -r requirements.txt
   cd samples
   

   C#

   cd pgadapter/samples/snippets/dotnet-snippets
   

Crea una instancia

Nota: Puedes omitir este paso si usas PGAdapter con el Emulador. PGAdapter creará automáticamente la instancia en el emulador cuando te conectes a PGAdapter.

Cuando usas Spanner por primera vez, debes crear una instancia, que es una asignación de recursos que usan las bases de datos de Spanner. Cuando creas una instancia, debes elegir una configuración de instancia, que determina dónde se almacenan tus datos y también la cantidad de nodos que se usarán, lo que, a su vez, determina la cantidad de recursos de entrega y almacenamiento de tu instancia.

Ejecuta el siguiente comando para crear una instancia de Spanner en la región us-central1 con 1 nodo:

gcloud spanner instances create test-instance --config=regional-us-central1 \
    --description="Test Instance" --nodes=1

Ten en cuenta que esto crea una instancia con las siguientes características:

• ID de instancia: test-instance
• Nombre visible: Test Instance
• Configuración de la instancia: regional-us-central1 (la configuración regional almacena datos en una región, mientras que la multirregional distribuye datos en varias regiones; Para obtener más información, consulta Acerca de las instancias.
• Recuento de nodos: 1 (node_count corresponde a la cantidad de recursos de procesamiento y almacenamiento disponibles para las bases de datos de la instancia; Obtén más información en Nodos y unidades de procesamiento de datos).

Deberías ver lo siguiente:

Creating instance...done.

Examina archivos de muestra

El repositorio de muestras contiene una muestra que indica cómo usar Spanner con PGAdapter.

Echa un vistazo a la carpeta samples/snippets, que muestra cómo usar Spanner El código es un instructivo sobre cómo crear y usar una base de datos nueva. Los datos utilizan el esquema de ejemplo de la página Esquema y modelo de datos.

Inicia PGAdapter

Inicia PGAdapter en tu máquina de desarrollo local y diríjalo a la instancia que creaste.

En los siguientes comandos, se da por sentado que ejecutaste gcloud auth application-default login.

Aplicación Java

wget https://storage.googleapis.com/pgadapter-jar-releases/pgadapter.tar.gz \
    && tar -xzvf pgadapter.tar.gz
java -jar pgadapter.jar -i test-instance

Docker

docker pull gcr.io/cloud-spanner-pg-adapter/pgadapter
docker run \
    --name pgadapter \
    --rm -d -p 5432:5432 \
    -v "$HOME/.config/gcloud":/gcloud:ro \
    --env CLOUDSDK_CONFIG=/gcloud \
    gcr.io/cloud-spanner-pg-adapter/pgadapter \
    -i test-instance -x

Nota: Reemplaza $HOME/.config/gcloud/ por %APPDATA%\gcloud si usas Windows, o bien ejecuta gcloud info --format='value(config.paths.global_config_dir)' para encontrar la carpeta de configuración gcloud actual.

Emulator

docker pull gcr.io/cloud-spanner-pg-adapter/pgadapter-emulator
docker run \
    --name pgadapter-emulator \
    --rm -d \
    -p 5432:5432 \
    -p 9010:9010 \
    -p 9020:9020 \
    gcr.io/cloud-spanner-pg-adapter/pgadapter-emulator

Esto inicia PGAdapter con un Spanner incorporado. emulador. Este emulador incorporado crea automáticamente cualquier instancia o base de datos de Spanner a la que te conectes sin necesidad de crearlas manualmente con anterioridad.

Te recomendamos que ejecutes PGAdapter en producción como un contenedor de sidecar o como una dependencia en proceso. Para obtener más información sobre la implementación PGAdapter en producción, consulta Elige un método para ejecutar PGAdapter.

Crea una base de datos

Para crear una base de datos llamada example-db en la instancia test-instance, ejecuta lo siguiente en la línea de comandos:

Nota: Puedes omitir este paso si usas PGAdapter con el Emulador. PGAdapter crea automáticamente la base de datos en la cuando te conectas a PGAdapter.

gcloud spanner databases create example-db --instance=test-instance \
    --database-dialect=POSTGRESQL

Deberías ver lo siguiente:

Creating database...done.

Crear tablas

El siguiente código crea dos tablas en la base de datos.

Nota: En los siguientes ejemplos de código, se usan estas dos tablas. Si no realizas este código y, luego, crear las tablas con la consola de Google Cloud o gcloud CLI. Para obtener más información, consulta el esquema de ejemplo.

psql

#!/bin/bash

# Set the connection variables for psql.
# The following statements use the existing value of the variable if it has
# already been set, and otherwise assigns a default value.
export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Create two tables in one batch.
psql << SQL
-- Create the singers table
CREATE TABLE singers (
  singer_id   bigint not null primary key,
  first_name  character varying(1024),
  last_name   character varying(1024),
  singer_info bytea,
  full_name   character varying(2048) GENERATED ALWAYS
          AS (first_name || ' ' || last_name) STORED
);

-- Create the albums table. This table is interleaved in the parent table
-- "singers".
CREATE TABLE albums (
  singer_id     bigint not null,
  album_id      bigint not null,
  album_title   character varying(1024),
  primary key (singer_id, album_id)
)
-- The 'interleave in parent' clause is a Spanner-specific extension to
-- open-source PostgreSQL.
INTERLEAVE IN PARENT singers ON DELETE CASCADE;
SQL

echo "Created Singers & Albums tables in database: [${PGDATABASE}]"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
import java.sql.Statement;

class CreateTables {
  static void createTables(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      try (Statement statement = connection.createStatement()) {
        // Create two tables in one batch.
        statement.addBatch(
            "create table singers ("
                + "  singer_id   bigint primary key not null,"
                + "  first_name  varchar(1024),"
                + "  last_name   varchar(1024),"
                + "  singer_info bytea,"
                + "  full_name   varchar(2048) generated always as (\n"
                + "      case when first_name is null then last_name\n"
                + "          when last_name  is null then first_name\n"
                + "          else first_name || ' ' || last_name\n"
                + "      end) stored"
                + ")");
        statement.addBatch(
            "create table albums ("
                + "  singer_id     bigint not null,"
                + "  album_id      bigint not null,"
                + "  album_title   varchar,"
                + "  primary key (singer_id, album_id)"
                + ") interleave in parent singers on delete cascade");
        statement.executeBatch();
        System.out.println("Created Singers & Albums tables in database: [" + database + "]");
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func CreateTables(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Create two tables in one batch on Spanner.
	br := conn.SendBatch(ctx, &pgx.Batch{QueuedQueries: []*pgx.QueuedQuery{
		{SQL: "create table singers (" +
			"  singer_id   bigint primary key not null," +
			"  first_name  character varying(1024)," +
			"  last_name   character varying(1024)," +
			"  singer_info bytea," +
			"  full_name   character varying(2048) generated " +
			"  always as (first_name || ' ' || last_name) stored" +
			")"},
		{SQL: "create table albums (" +
			"  singer_id     bigint not null," +
			"  album_id      bigint not null," +
			"  album_title   character varying(1024)," +
			"  primary key (singer_id, album_id)" +
			") interleave in parent singers on delete cascade"},
	}})
	cmd, err := br.Exec()
	if err != nil {
		return err
	}
	if cmd.String() != "CREATE" {
		return fmt.Errorf("unexpected command tag: %v", cmd.String())
	}
	if err := br.Close(); err != nil {
		return err
	}
	fmt.Printf("Created Singers & Albums tables in database: [%s]\n", database)

	return nil
}

Node.js

import { Client } from 'pg';

async function createTables(host: string, port: number, database: string): Promise<void> {
  // Connect to Spanner through PGAdapter.
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Create two tables in one batch.
  await connection.query("start batch ddl");
  await connection.query("create table singers (" +
      "  singer_id   bigint primary key not null," +
      "  first_name  character varying(1024)," +
      "  last_name   character varying(1024)," +
      "  singer_info bytea," +
      "  full_name   character varying(2048) generated " +
      "  always as (first_name || ' ' || last_name) stored" +
      ")");
  await connection.query("create table albums (" +
      "  singer_id     bigint not null," +
      "  album_id      bigint not null," +
      "  album_title   character varying(1024)," +
      "  primary key (singer_id, album_id)" +
      ") interleave in parent singers on delete cascade");
  await connection.query("run batch");
  console.log(`Created Singers & Albums tables in database: [${database}]`);

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def create_tables(host: string, port: int, database: string):
    # Connect to Cloud Spanner using psycopg3 through PGAdapter.
    with psycopg.connect("host={host} port={port} "
                         "dbname={database} "
                         "sslmode=disable".format(host=host, port=port,
                                                  database=database)) as conn:
        # Enable autocommit to execute DDL statements, as psycopg otherwise
        # tries to use a read/write transaction.
        conn.autocommit = True

        # Use a pipeline to execute multiple DDL statements in one batch.
        with conn.pipeline():
            conn.execute("create table singers ("
                         + "  singer_id   bigint primary key not null,"
                         + "  first_name  character varying(1024),"
                         + "  last_name   character varying(1024),"
                         + "  singer_info bytea,"
                         + "  full_name   character varying(2048) generated "
                         + "  always as (first_name || ' ' || last_name) stored"
                         + ")")
            conn.execute("create table albums ("
                         + "  singer_id     bigint not null,"
                         + "  album_id      bigint not null,"
                         + "  album_title   character varying(1024),"
                         + "  primary key (singer_id, album_id)"
                         + ") interleave in parent singers on delete cascade")
        print("Created Singers & Albums tables in database: [{database}]"
              .format(database=database))

C#

using Npgsql;

namespace dotnet_snippets;

public static class CreateTablesSample
{
    public static void CreateTables(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Create two tables in one batch.
        var batch = connection.CreateBatch();
        batch.BatchCommands.Add(new NpgsqlBatchCommand(
            "create table singers ("
            + "  singer_id   bigint primary key not null,"
            + "  first_name  varchar(1024),"
            + "  last_name   varchar(1024),"
            + "  singer_info bytea,"
            + "  full_name   varchar(2048) generated always as (\n"
            + "      case when first_name is null then last_name\n"
            + "          when last_name  is null then first_name\n"
            + "          else first_name || ' ' || last_name\n"
            + "      end) stored"
            + ")"));
        batch.BatchCommands.Add(new NpgsqlBatchCommand(
            "create table albums ("
            + "  singer_id     bigint not null,"
            + "  album_id      bigint not null,"
            + "  album_title   varchar,"
            + "  primary key (singer_id, album_id)"
            + ") interleave in parent singers on delete cascade"));
        batch.ExecuteNonQuery();
        Console.WriteLine($"Created Singers & Albums tables in database: [{database}]");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./create_tables.sh example-db

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar createtables example-db

Go

go run sample_runner.go createtables example-db

Node.js

npm start createtables example-db

Python

python create_tables.py example-db

C#

dotnet run createtables example-db

El siguiente paso consiste en escribir datos en tu base de datos.

Crear una conexión

Para poder realizar operaciones de lectura o escritura, debes crear una conexión a PGAdapter. Todas tus interacciones con Spanner deben pasar por un Connection. El nombre de la base de datos se especifica en la cadena de conexión.

psql

#!/bin/bash

# Set the connection variables for psql.
# The following statements use the existing value of the variable if it has
# already been set, and otherwise assigns a default value.
export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Connect to Cloud Spanner using psql through PGAdapter
# and execute a simple query.
psql -c "select 'Hello world!' as hello"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;

class CreateConnection {
  static void createConnection(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      try (ResultSet resultSet =
          connection.createStatement().executeQuery("select 'Hello world!' as hello")) {
        while (resultSet.next()) {
          System.out.printf("Greeting from Cloud Spanner PostgreSQL: %s\n", resultSet.getString(1));
        }
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func CreateConnection(host string, port int, database string) error {
	ctx := context.Background()
	// Connect to Cloud Spanner using pgx through PGAdapter.
	// 'sslmode=disable' is optional, but adding it reduces the connection time,
	// as pgx will then skip first trying to create an SSL connection.
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	row := conn.QueryRow(ctx, "select 'Hello world!' as hello")
	var msg string
	if err := row.Scan(&msg); err != nil {
		return err
	}
	fmt.Printf("Greeting from Cloud Spanner PostgreSQL: %s\n", msg)

	return nil
}

Node.js

import { Client } from 'pg';

async function createConnection(host: string, port: number, database: string): Promise<void> {
  // Connect to Spanner through PGAdapter.
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  const result = await connection.query("select 'Hello world!' as hello");
  console.log(`Greeting from Cloud Spanner PostgreSQL: ${result.rows[0]['hello']}`);

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def create_connection(host: string, port: int, database: string):
    # Connect to Cloud Spanner using psycopg3 through PGAdapter.
    # 'sslmode=disable' is optional, but adding it reduces the connection time,
    # as psycopg3 will then skip first trying to create an SSL connection.
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.execute("select 'Hello world!' as hello")
            print("Greeting from Cloud Spanner PostgreSQL:", cur.fetchone()[0])

C#

using Npgsql;

namespace dotnet_snippets;

public static class CreateConnectionSample
{
    public static void CreateConnection(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        using var cmd = new NpgsqlCommand("select 'Hello World!' as hello", connection);
        using var reader = cmd.ExecuteReader();
        while (reader.Read())
        {
            var greeting = reader.GetString(0);
            Console.WriteLine($"Greeting from Cloud Spanner PostgreSQL: {greeting}");
        }
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./create_connection.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar createconnection example-db

Go

go run sample_runner.go createconnection example-db

Node.js

npm start createconnection example-db

Python

python create_connection.py example-db

C#

dotnet run createconnection example-db

Escribe datos con DML

Puedes insertar datos mediante el lenguaje de manipulación de datos (DML) en una transacción de lectura y escritura.

En estas muestras, se indica cómo ejecutar una declaración DML en Spanner con un controlador de PostgreSQL.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql -c "INSERT INTO singers (singer_id, first_name, last_name) VALUES
                             (12, 'Melissa', 'Garcia'),
                             (13, 'Russel', 'Morales'),
                             (14, 'Jacqueline', 'Long'),
                             (15, 'Dylan', 'Shaw')"

echo "4 records inserted"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.SQLException;
import java.util.Arrays;
import java.util.List;

class WriteDataWithDml {
  static class Singer {
    private final long singerId;
    private final String firstName;
    private final String lastName;

    Singer(final long id, final String first, final String last) {
      this.singerId = id;
      this.firstName = first;
      this.lastName = last;
    }
  }

  static void writeDataWithDml(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Add 4 rows in one statement.
      // JDBC always uses '?' as a parameter placeholder.
      try (PreparedStatement preparedStatement =
          connection.prepareStatement(
              "INSERT INTO singers (singer_id, first_name, last_name) VALUES "
                  + "(?, ?, ?), "
                  + "(?, ?, ?), "
                  + "(?, ?, ?), "
                  + "(?, ?, ?)")) {

        final List<Singer> singers =
            Arrays.asList(
                new Singer(/* SingerId = */ 12L, "Melissa", "Garcia"),
                new Singer(/* SingerId = */ 13L, "Russel", "Morales"),
                new Singer(/* SingerId = */ 14L, "Jacqueline", "Long"),
                new Singer(/* SingerId = */ 15L, "Dylan", "Shaw"));

        // Note that JDBC parameters start at index 1.
        int paramIndex = 0;
        for (Singer singer : singers) {
          preparedStatement.setLong(++paramIndex, singer.singerId);
          preparedStatement.setString(++paramIndex, singer.firstName);
          preparedStatement.setString(++paramIndex, singer.lastName);
        }

        int updateCount = preparedStatement.executeUpdate();
        System.out.printf("%d records inserted.\n", updateCount);
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func WriteDataWithDml(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	tag, err := conn.Exec(ctx,
		"INSERT INTO singers (singer_id, first_name, last_name) "+
			"VALUES ($1, $2, $3), ($4, $5, $6), "+
			"       ($7, $8, $9), ($10, $11, $12)",
		12, "Melissa", "Garcia",
		13, "Russel", "Morales",
		14, "Jacqueline", "Long",
		15, "Dylan", "Shaw")
	if err != nil {
		return err
	}
	fmt.Printf("%v records inserted\n", tag.RowsAffected())

	return nil
}

Node.js

import { Client } from 'pg';

async function writeDataWithDml(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  const result = await connection.query("INSERT INTO singers (singer_id, first_name, last_name) " +
      "VALUES ($1, $2, $3), ($4, $5, $6), " +
      "       ($7, $8, $9), ($10, $11, $12)",
       [12, "Melissa", "Garcia",
        13, "Russel", "Morales",
        14, "Jacqueline", "Long",
        15, "Dylan", "Shaw"])
  console.log(`${result.rowCount} records inserted`);

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def write_data_with_dml(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.execute("INSERT INTO singers (singer_id, first_name, last_name)"
                        " VALUES (%s, %s, %s), (%s, %s, %s), "
                        "        (%s, %s, %s), (%s, %s, %s)",
                        (12, "Melissa", "Garcia",
                         13, "Russel", "Morales",
                         14, "Jacqueline", "Long",
                         15, "Dylan", "Shaw",))
            print("%d records inserted" % cur.rowcount)

C#

using Npgsql;

namespace dotnet_snippets;

public static class WriteDataWithDmlSample
{
    readonly struct Singer
    {
        public Singer(long singerId, string firstName, string lastName)
        {
            SingerId = singerId;
            FirstName = firstName;
            LastName = lastName;
        }

        public long SingerId { get; }
        public string FirstName { get; }
        public string LastName { get; }
    }

    public static void WriteDataWithDml(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();
        // Add 4 rows in one statement.
        using var cmd = new NpgsqlCommand("INSERT INTO singers (singer_id, first_name, last_name) VALUES "
                                          + "($1, $2, $3), "
                                          + "($4, $5, $6), "
                                          + "($7, $8, $9), "
                                          + "($10, $11, $12)", connection);
        List<Singer> singers =
        [
            new Singer(/* SingerId = */ 12L, "Melissa", "Garcia"),
            new Singer(/* SingerId = */ 13L, "Russel", "Morales"),
            new Singer(/* SingerId = */ 14L, "Jacqueline", "Long"),
            new Singer(/* SingerId = */ 15L, "Dylan", "Shaw")
        ];
        foreach (var singer in singers)
        {
            cmd.Parameters.Add(new NpgsqlParameter { Value = singer.SingerId });
            cmd.Parameters.Add(new NpgsqlParameter { Value = singer.FirstName });
            cmd.Parameters.Add(new NpgsqlParameter { Value = singer.LastName });
        }
        var updateCount = cmd.ExecuteNonQuery();
        Console.WriteLine($"{updateCount} records inserted.");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./write_data_with_dml.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar writeusingdml example-db

Go

go run sample_runner.go writeusingdml example-db

Node.js

npm start writeusingdml example-db

Python

python write_data_with_dml.py example-db

C#

dotnet run writeusingdml example-db

Deberías ver la siguiente respuesta:

 4 records inserted.

Nota: Existen límites para confirmar el tamaño. Consulta el límite de CRUD. para obtener más información.

Escribe datos con un lote de DML

PGAdapter admite la ejecución de lotes de DML. Enviar varias instrucciones DML en un lote reduce la cantidad de viajes de ida y vuelta a Spanner y mejora el rendimiento de tu aplicación.

Sugerencia: También puedes ejecutar lotes de DML con el comando START BATCH DML.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Create a prepared insert statement and execute this prepared
# insert statement three times in one SQL string. The single
# SQL string with three insert statements will be executed as
# a single DML batch on Spanner.
psql -c "PREPARE insert_singer AS
           INSERT INTO singers (singer_id, first_name, last_name)
           VALUES (\$1, \$2, \$3)" \
     -c "EXECUTE insert_singer (16, 'Sarah', 'Wilson');
         EXECUTE insert_singer (17, 'Ethan', 'Miller');
         EXECUTE insert_singer (18, 'Maya', 'Patel');"

echo "3 records inserted"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.SQLException;
import java.util.Arrays;
import java.util.List;

class WriteDataWithDmlBatch {
  static class Singer {
    private final long singerId;
    private final String firstName;
    private final String lastName;

    Singer(final long id, final String first, final String last) {
      this.singerId = id;
      this.firstName = first;
      this.lastName = last;
    }
  }

  static void writeDataWithDmlBatch(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Add multiple rows in one DML batch.
      // JDBC always uses '?' as a parameter placeholder.
      try (PreparedStatement preparedStatement =
          connection.prepareStatement(
              "INSERT INTO singers (singer_id, first_name, last_name) VALUES (?, ?, ?)")) {
        final List<Singer> singers =
            Arrays.asList(
                new Singer(/* SingerId = */ 16L, "Sarah", "Wilson"),
                new Singer(/* SingerId = */ 17L, "Ethan", "Miller"),
                new Singer(/* SingerId = */ 18L, "Maya", "Patel"));

        for (Singer singer : singers) {
          // Note that JDBC parameters start at index 1.
          int paramIndex = 0;
          preparedStatement.setLong(++paramIndex, singer.singerId);
          preparedStatement.setString(++paramIndex, singer.firstName);
          preparedStatement.setString(++paramIndex, singer.lastName);
          preparedStatement.addBatch();
        }

        int[] updateCounts = preparedStatement.executeBatch();
        System.out.printf("%d records inserted.\n", Arrays.stream(updateCounts).sum());
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func WriteDataWithDmlBatch(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	sql := "INSERT INTO singers (singer_id, first_name, last_name) " +
		"VALUES ($1, $2, $3)"
	batch := &pgx.Batch{}
	batch.Queue(sql, 16, "Sarah", "Wilson")
	batch.Queue(sql, 17, "Ethan", "Miller")
	batch.Queue(sql, 18, "Maya", "Patel")
	br := conn.SendBatch(ctx, batch)
	_, err = br.Exec()
	if err := br.Close(); err != nil {
		return err
	}

	if err != nil {
		return err
	}
	fmt.Printf("%v records inserted\n", batch.Len())

	return nil
}

Node.js

import { Client } from 'pg';

async function writeDataWithDmlBatch(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // node-postgres does not support PostgreSQL pipeline mode, so we must use the
  // `start batch dml` / `run batch` statements to execute a DML batch.
  const sql = "INSERT INTO singers (singer_id, first_name, last_name) VALUES ($1, $2, $3)";
  await connection.query("start batch dml");
  await connection.query(sql, [16, "Sarah", "Wilson"]);
  await connection.query(sql, [17, "Ethan", "Miller"]);
  await connection.query(sql, [18, "Maya", "Patel"]);
  const result = await connection.query("run batch");
  // RUN BATCH returns the update counts as an array of strings, with one element for each
  // DML statement in the batch. This calculates the total number of affected rows from that array.
  const updateCount = result.rows[0]["UPDATE_COUNTS"]
      .map((s: string) => parseInt(s))
      .reduce((c: number, current: number) => c + current, 0);
  console.log(`${updateCount} records inserted`);

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def write_data_with_dml_batch(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.executemany("INSERT INTO singers "
                            "(singer_id, first_name, last_name) "
                            "VALUES (%s, %s, %s)",
                            [(16, "Sarah", "Wilson",),
                             (17, "Ethan", "Miller",),
                             (18, "Maya", "Patel",), ])
            print("%d records inserted" % cur.rowcount)

C#

using Npgsql;

namespace dotnet_snippets;

public static class WriteDataWithDmlBatchSample
{
    readonly struct Singer
    {
        public Singer(long singerId, string firstName, string lastName)
        {
            SingerId = singerId;
            FirstName = firstName;
            LastName = lastName;
        }

        public long SingerId { get; }
        public string FirstName { get; }
        public string LastName { get; }
    }

    public static void WriteDataWithDmlBatch(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Add multiple rows in one DML batch.
        const string sql = "INSERT INTO singers (singer_id, first_name, last_name) VALUES ($1, $2, $3)";
        List<Singer> singers =
        [
            new Singer(/* SingerId = */ 16L, "Sarah", "Wilson"),
            new Singer(/* SingerId = */ 17L, "Ethan", "Miller"),
            new Singer(/* SingerId = */ 18L, "Maya", "Patel")
        ];
        using var batch = new NpgsqlBatch(connection);
        foreach (var singer in singers)
        {
            batch.BatchCommands.Add(new NpgsqlBatchCommand
            {
                CommandText = sql,
                Parameters =
                {
                    new NpgsqlParameter {Value = singer.SingerId},
                    new NpgsqlParameter {Value = singer.FirstName},
                    new NpgsqlParameter {Value = singer.LastName}
                }
            });
        }
        var updateCount = batch.ExecuteNonQuery();
        Console.WriteLine($"{updateCount} records inserted.");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./write_data_with_dml_batch.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar writeusingdmlbatch example-db

Go

go run sample_runner.go writeusingdmlbatch example-db

Node.js

npm start writeusingdmlbatch example-db

Python

python write_data_with_dml_batch.py example-db

C#

dotnet run writeusingdmlbatch example-db

Deberías ver lo siguiente:

3 records inserted.

Escribe datos con mutaciones

También puedes insertar datos mediante mutaciones.

PGAdapter traduce el comando COPY de PostgreSQL a mutaciones de los datos. Usar COPY es la forma más eficiente de insertar datos rápidamente en tu base de datos de Spanner.

Las operaciones de COPY son atómicas de forma predeterminada. Las operaciones atómicas en Spanner están limitadas por el límite de tamaño de confirmación. Consulta el límite de CRUD para obtener más información.

En estos ejemplos, se muestra cómo ejecutar una operación COPY no atómica. Esto permite que la operación COPY supere el límite de tamaño de confirmación.

Sugerencia: Consulta Compatibilidad con COPIAS para obtener más información sobre cómo copiar datos directamente desde PostgreSQL a Spanner También puedes importar datos directamente desde MySQL con el comando COPY.

psql

#!/bin/bash

# Get the source directory of this script.
directory=${BASH_SOURCE%/*}/

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Copy data to Spanner from a tab-separated text file using the COPY command.
psql -c "COPY singers (singer_id, first_name, last_name) FROM STDIN" \
  < "${directory}singers_data.txt"
psql -c "COPY albums FROM STDIN" \
  < "${directory}albums_data.txt"

echo "Copied singers and albums"

Java

import java.io.IOException;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
import org.postgresql.PGConnection;
import org.postgresql.copy.CopyManager;

class WriteDataWithCopy {

  static void writeDataWithCopy(String host, int port, String database)
      throws SQLException, IOException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Unwrap the PostgreSQL JDBC connection interface to get access to
      // a CopyManager.
      PGConnection pgConnection = connection.unwrap(PGConnection.class);
      CopyManager copyManager = pgConnection.getCopyAPI();

      // Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
      // will succeed even if it exceeds Spanner's mutation limit per transaction.
      connection
          .createStatement()
          .execute("set spanner.autocommit_dml_mode='partitioned_non_atomic'");
      long numSingers =
          copyManager.copyIn(
              "COPY singers (singer_id, first_name, last_name) FROM STDIN",
              WriteDataWithCopy.class.getResourceAsStream("singers_data.txt"));
      System.out.printf("Copied %d singers\n", numSingers);

      long numAlbums =
          copyManager.copyIn(
              "COPY albums FROM STDIN",
              WriteDataWithCopy.class.getResourceAsStream("albums_data.txt"));
      System.out.printf("Copied %d albums\n", numAlbums);
    }
  }
}

Go

import (
	"context"
	"fmt"
	"os"

	"github.com/jackc/pgx/v5"
)

func WriteDataWithCopy(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
	// will succeed even if it exceeds Spanner's mutation limit per transaction.
	conn.Exec(ctx, "set spanner.autocommit_dml_mode='partitioned_non_atomic'")

	file, err := os.Open("samples/singers_data.txt")
	if err != nil {
		return err
	}
	tag, err := conn.PgConn().CopyFrom(ctx, file,
		"copy singers (singer_id, first_name, last_name) from stdin")
	if err != nil {
		return err
	}
	fmt.Printf("Copied %v singers\n", tag.RowsAffected())

	file, err = os.Open("samples/albums_data.txt")
	if err != nil {
		return err
	}
	tag, err = conn.PgConn().CopyFrom(ctx, file,
		"copy albums from stdin")
	if err != nil {
		return err
	}
	fmt.Printf("Copied %v albums\n", tag.RowsAffected())

	return nil
}

Node.js

import { Client } from 'pg';
import { pipeline } from 'node:stream/promises'
import fs from 'node:fs'
import { from as copyFrom } from 'pg-copy-streams'
import path from "path";

async function writeDataWithCopy(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
  // will succeed even if it exceeds Spanner's mutation limit per transaction.
  await connection.query("set spanner.autocommit_dml_mode='partitioned_non_atomic'");
  // Copy data from a csv file to Spanner using the COPY command.
  // Note that even though the command says 'from stdin', the actual input comes from a file.
  const copySingersStream = copyFrom('copy singers (singer_id, first_name, last_name) from stdin');
  const ingestSingersStream = connection.query(copySingersStream);
  const sourceSingersStream = fs.createReadStream(path.join(__dirname, 'singers_data.txt'));
  await pipeline(sourceSingersStream, ingestSingersStream);
  console.log(`Copied ${copySingersStream.rowCount} singers`);

  const copyAlbumsStream = copyFrom('copy albums from stdin');
  const ingestAlbumsStream = connection.query(copyAlbumsStream);
  const sourceAlbumsStream = fs.createReadStream(path.join(__dirname, 'albums_data.txt'));
  await pipeline(sourceAlbumsStream, ingestAlbumsStream);
  console.log(`Copied ${copyAlbumsStream.rowCount} albums`);

  // Close the connection.
  await connection.end();
}

Python

import os
import string
import psycopg


def write_data_with_copy(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:

        script_dir = os.path.dirname(os.path.abspath(__file__))
        singers_file_path = os.path.join(script_dir, "singers_data.txt")
        albums_file_path = os.path.join(script_dir, "albums_data.txt")

        conn.autocommit = True
        block_size = 1024
        with conn.cursor() as cur:
            with open(singers_file_path, "r") as f:
                with cur.copy("COPY singers (singer_id, first_name, last_name) "
                              "FROM STDIN") as copy:
                    while data := f.read(block_size):
                        copy.write(data)
            print("Copied %d singers" % cur.rowcount)

            with open(albums_file_path, "r") as f:
                with cur.copy("COPY albums "
                              "FROM STDIN") as copy:
                    while data := f.read(block_size):
                        copy.write(data)
            print("Copied %d albums" % cur.rowcount)

C#

using Npgsql;

namespace dotnet_snippets;

public static class WriteDataWithCopySample
{
    public static void WriteDataWithCopy(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
        // will succeed even if it exceeds Spanner's mutation limit per transaction.
        using var cmd = new NpgsqlCommand("set spanner.autocommit_dml_mode='partitioned_non_atomic'", connection);
        cmd.ExecuteNonQuery();

        var singerCount = 0;
        using var singerReader = new StreamReader("singers_data.txt");
        using (var singerWriter = connection.BeginTextImport("COPY singers (singer_id, first_name, last_name) FROM STDIN"))
        {
            while (singerReader.ReadLine() is { } line)
            {
                singerWriter.WriteLine(line);
                singerCount++;
            }
        }
        Console.WriteLine($"Copied {singerCount} singers");

        var albumCount = 0;
        using var albumReader = new StreamReader("albums_data.txt");
        using (var albumWriter = connection.BeginTextImport("COPY albums FROM STDIN"))
        {
            while (albumReader.ReadLine() is { } line)
            {
                albumWriter.WriteLine(line);
                albumCount++;
            }
        }
        Console.WriteLine($"Copied {albumCount} albums");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./write_data_with_copy.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar write example-db

Go

go run sample_runner.go write example-db

Node.js

npm start write example-db

Python

python write_data_with_copy.py example-db

C#

dotnet run write example-db

Deberías ver lo siguiente:

Copied 5 singers
Copied 5 albums

Nota: Existen límites para confirmar el tamaño. Consulta el límite de CRUD. para obtener más información.

Consulta datos mediante SQL

Spanner admite una interfaz de SQL para leer datos, a la que puedes acceder desde la línea de comandos con Google Cloud CLI o de manera programática con un controlador de PostgreSQL.

En la línea de comandos

Ejecuta la siguiente instrucción de SQL para leer los valores de todas las columnas de la tabla Albums:

gcloud spanner databases execute-sql example-db --instance=test-instance \
    --sql='SELECT singer_id, album_id, album_title FROM albums'

Nota: Para obtener la referencia de GoogleSQL, visita Sintaxis de consultas en GoogleSQL y, como referencia de PostgreSQL, consulta Estructura léxica y sintaxis de PostgreSQL.

El resultado debería ser este:

SingerId AlbumId AlbumTitle
1        1       Total Junk
1        2       Go, Go, Go
2        1       Green
2        2       Forever Hold Your Peace
2        3       Terrified

Usa un controlador de PostgreSQL

Además de ejecutar una instrucción de SQL en la línea de comandos, puedes emitir la misma instrucción de SQL de manera programática con un controlador de PostgreSQL.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql -c "SELECT singer_id, album_id, album_title
         FROM albums"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;

class QueryData {
  static void queryData(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      try (ResultSet resultSet =
          connection
              .createStatement()
              .executeQuery("SELECT singer_id, album_id, album_title FROM albums")) {
        while (resultSet.next()) {
          System.out.printf(
              "%d %d %s\n",
              resultSet.getLong("singer_id"),
              resultSet.getLong("album_id"),
              resultSet.getString("album_title"));
        }
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func QueryData(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	rows, err := conn.Query(ctx, "SELECT singer_id, album_id, album_title "+
		"FROM albums")
	defer rows.Close()
	if err != nil {
		return err
	}
	for rows.Next() {
		var singerId, albumId int64
		var title string
		err = rows.Scan(&singerId, &albumId, &title)
		if err != nil {
			return err
		}
		fmt.Printf("%v %v %v\n", singerId, albumId, title)
	}

	return rows.Err()
}

Node.js

import { Client } from 'pg';

async function queryData(host: string, port: number, database: string): Promise<void> {
  // Connect to Spanner through PGAdapter.
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  const result = await connection.query("SELECT singer_id, album_id, album_title " +
      "FROM albums");
  for (const row of result.rows) {
    console.log(`${row["singer_id"]} ${row["album_id"]} ${row["album_title"]}`);
  }

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def query_data(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.execute("SELECT singer_id, album_id, album_title "
                        "FROM albums")
            for album in cur:
                print(album)

C#

using Npgsql;

namespace dotnet_snippets;

public static class QueryDataSample
{
    public static void QueryData(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        using var cmd = new NpgsqlCommand("SELECT singer_id, album_id, album_title FROM albums", connection);
        using var reader = cmd.ExecuteReader();
        while (reader.Read())
        {
            Console.WriteLine($"{reader.GetInt64(0)} {reader.GetInt64(1)} {reader.GetString(2)}");
        }
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./query_data.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar query example-db

Go

go run sample_runner.go query example-db

Node.js

npm start query example-db

Python

python query_data.py example-db

C#

dotnet run query example-db

Deberías ver el siguiente resultado:

1 1 Total Junk
1 2 Go, Go, Go
2 1 Green
2 2 Forever Hold Your Peace
2 3 Terrified

Consulta mediante un parámetro de SQL

Si tu aplicación tiene una consulta ejecutada con frecuencia, puedes mejorar su rendimiento. al parametrizarlo. La consulta paramétrica resultante puede almacenarse en caché y volverse a usar, lo que reduce los costos de compilación. Para obtener más información, consulta Usa parámetros de consulta para acelerar las consultas que se ejecutan con frecuencia.

Este es un ejemplo del uso de un parámetro en la cláusula WHERE para Consultar registros que contengan un valor específico para LastName.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Create a prepared statement to use a query parameter.
# Using a prepared statement for executing the same SQL string multiple
# times increases the execution speed of the statement.
psql -c "PREPARE select_singer AS
         SELECT singer_id, first_name, last_name
         FROM singers
         WHERE last_name = \$1" \
     -c "EXECUTE select_singer ('Garcia')"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

class QueryDataWithParameter {
  static void queryDataWithParameter(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      try (PreparedStatement statement =
          connection.prepareStatement(
              "SELECT singer_id, first_name, last_name "
                  + "FROM singers "
                  + "WHERE last_name = ?")) {
        statement.setString(1, "Garcia");
        try (ResultSet resultSet = statement.executeQuery()) {
          while (resultSet.next()) {
            System.out.printf(
                "%d %s %s\n",
                resultSet.getLong("singer_id"),
                resultSet.getString("first_name"),
                resultSet.getString("last_name"));
          }
        }
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func QueryDataWithParameter(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	rows, err := conn.Query(ctx,
		"SELECT singer_id, first_name, last_name "+
			"FROM singers "+
			"WHERE last_name = $1", "Garcia")
	defer rows.Close()
	if err != nil {
		return err
	}
	for rows.Next() {
		var singerId int64
		var firstName, lastName string
		err = rows.Scan(&singerId, &firstName, &lastName)
		if err != nil {
			return err
		}
		fmt.Printf("%v %v %v\n", singerId, firstName, lastName)
	}

	return rows.Err()
}

Node.js

import { Client } from 'pg';

async function queryWithParameter(host: string, port: number, database: string): Promise<void> {
  // Connect to Spanner through PGAdapter.
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  const result = await connection.query(
      "SELECT singer_id, first_name, last_name " +
      "FROM singers " +
      "WHERE last_name = $1", ["Garcia"]);
  for (const row of result.rows) {
    console.log(`${row["singer_id"]} ${row["first_name"]} ${row["last_name"]}`);
  }

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def query_data_with_parameter(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.execute("SELECT singer_id, first_name, last_name "
                        "FROM singers "
                        "WHERE last_name = %s", ("Garcia",))
            for singer in cur:
                print(singer)

C#

using Npgsql;

namespace dotnet_snippets;

public static class QueryDataWithParameterSample
{
    public static void QueryDataWithParameter(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        using var cmd = new NpgsqlCommand("SELECT singer_id, first_name, last_name "
                                          + "FROM singers "
                                          + "WHERE last_name = $1", connection);
        cmd.Parameters.Add(new NpgsqlParameter { Value = "Garcia" });
        using var reader = cmd.ExecuteReader();
        while (reader.Read())
        {
            Console.WriteLine($"{reader["singer_id"]} {reader["first_name"]} {reader["last_name"]}");
        }
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./query_data_with_parameter.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar querywithparameter example-db

Go

go run sample_runner.go querywithparameter example-db

Node.js

npm start querywithparameter example-db

Python

python query_data_with_parameter.py example-db

C#

dotnet run querywithparameter example-db

Deberías ver el siguiente resultado:

12 Melissa Garcia

Actualiza el esquema de la base de datos

Supongamos que necesitas agregar una columna nueva llamada MarketingBudget a la tabla Albums. Para agregar una columna nueva a una tabla existente, es necesario actualizar el esquema de la base de datos. Spanner admite actualizaciones de esquema en una base de datos, mientras que base de datos siga entregando tráfico. Las actualizaciones de esquema no requieren que la base de datos esté sin conexión y no bloquean tablas ni columnas completas. Puedes continuar escribiendo datos en la base de datos durante la actualización del esquema. Obtén más información sobre las actualizaciones admitidas del esquema y el rendimiento de los cambios de esquema en Cómo realizar actualizaciones de esquema.

Agrega una columna

Puedes agregar una columna en la línea de comandos con la CLI de Google Cloud o de manera programática con un controlador de PostgreSQL.

En la línea de comandos

Usa el siguiente comando ALTER TABLE para agregar la columna nueva a la tabla:

gcloud spanner databases ddl update example-db --instance=test-instance \
    --ddl='ALTER TABLE albums ADD COLUMN marketing_budget BIGINT'

Deberías ver lo siguiente:

Schema updating...done.

Usa un controlador de PostgreSQL

Ejecuta la instrucción de DDL con un controlador de PostgreSQL para modificar el esquema:

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql -c "ALTER TABLE albums ADD COLUMN marketing_budget bigint"
echo "Added marketing_budget column"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;

class AddColumn {
  static void addColumn(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      connection.createStatement().execute("alter table albums add column marketing_budget bigint");
      System.out.println("Added marketing_budget column");
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func AddColumn(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	_, err = conn.Exec(ctx,
		"ALTER TABLE albums "+
			"ADD COLUMN marketing_budget bigint")
	if err != nil {
		return err
	}
	fmt.Println("Added marketing_budget column")

	return nil
}

Node.js

import { Client } from 'pg';

async function addColumn(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  await connection.query(
      "ALTER TABLE albums " +
      "ADD COLUMN marketing_budget bigint");
  console.log("Added marketing_budget column");

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def add_column(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        # DDL can only be executed when autocommit=True.
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.execute("ALTER TABLE albums "
                        "ADD COLUMN marketing_budget bigint")
            print("Added marketing_budget column")

C#

using Npgsql;

namespace dotnet_snippets;

public static class AddColumnSample
{
    public static void AddColumn(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        using var cmd = connection.CreateCommand();
        cmd.CommandText = "alter table albums add column marketing_budget bigint";
        cmd.ExecuteNonQuery();
        Console.WriteLine("Added marketing_budget column");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./add_column.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar addmarketingbudget example-db

Go

go run sample_runner.go addmarketingbudget example-db

Node.js

npm start addmarketingbudget example-db

Python

python add_column.py example-db

C#

dotnet run addmarketingbudget example-db

Deberías ver lo siguiente:

Added marketing_budget column

Ejecuta un lote de DDL

Se recomienda ejecutar varias modificaciones de esquemas en un solo lote. Puedes ejecutar varias instrucciones DDL en un lote con la función de procesamiento por lotes integrada de tu controlador de PostgreSQL, enviando todas las instrucciones DDL como una cadena SQL separada por punto y coma, o con las instrucciones START BATCH DDL y RUN BATCH.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Use a single SQL command to batch multiple statements together.
# Executing multiple DDL statements as one batch is more efficient
# than executing each statement individually.
# Separate the statements with semicolons.
psql << SQL

CREATE TABLE venues (
  venue_id    bigint not null primary key,
  name        varchar(1024),
  description jsonb
);

CREATE TABLE concerts (
  concert_id bigint not null primary key ,
  venue_id   bigint not null,
  singer_id  bigint not null,
  start_time timestamptz,
  end_time   timestamptz,
  constraint fk_concerts_venues foreign key
    (venue_id) references venues (venue_id),
  constraint fk_concerts_singers foreign key
    (singer_id) references singers (singer_id)
);

SQL

echo "Added venues and concerts tables"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
import java.sql.Statement;

class DdlBatch {
  static void ddlBatch(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      try (Statement statement = connection.createStatement()) {
        // Create two new tables in one batch.
        statement.addBatch(
            "CREATE TABLE venues ("
                + "  venue_id    bigint not null primary key,"
                + "  name        varchar(1024),"
                + "  description jsonb"
                + ")");
        statement.addBatch(
            "CREATE TABLE concerts ("
                + "  concert_id bigint not null primary key ,"
                + "  venue_id   bigint not null,"
                + "  singer_id  bigint not null,"
                + "  start_time timestamptz,"
                + "  end_time   timestamptz,"
                + "  constraint fk_concerts_venues foreign key"
                + "    (venue_id) references venues (venue_id),"
                + "  constraint fk_concerts_singers foreign key"
                + "    (singer_id) references singers (singer_id)"
                + ")");
        statement.executeBatch();
      }
      System.out.println("Added venues and concerts tables");
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func DdlBatch(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Executing multiple DDL statements as one batch is
	// more efficient than executing each statement
	// individually.
	br := conn.SendBatch(ctx, &pgx.Batch{QueuedQueries: []*pgx.QueuedQuery{
		{SQL: "CREATE TABLE venues (" +
			"  venue_id    bigint not null primary key," +
			"  name        varchar(1024)," +
			"  description jsonb" +
			")"},
		{SQL: "CREATE TABLE concerts (" +
			"  concert_id bigint not null primary key ," +
			"  venue_id   bigint not null," +
			"  singer_id  bigint not null," +
			"  start_time timestamptz," +
			"  end_time   timestamptz," +
			"  constraint fk_concerts_venues foreign key" +
			"    (venue_id) references venues (venue_id)," +
			"  constraint fk_concerts_singers foreign key" +
			"    (singer_id) references singers (singer_id)" +
			")"},
	}})
	if _, err := br.Exec(); err != nil {
		return err
	}
	if err := br.Close(); err != nil {
		return err
	}
	fmt.Println("Added venues and concerts tables")

	return nil
}

Node.js

import { Client } from 'pg';

async function ddlBatch(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Executing multiple DDL statements as one batch is
  // more efficient than executing each statement
  // individually.
  await connection.query("start batch ddl");
  await connection.query("CREATE TABLE venues (" +
      "  venue_id    bigint not null primary key," +
      "  name        varchar(1024)," +
      "  description jsonb" +
      ")");
  await connection.query("CREATE TABLE concerts (" +
      "  concert_id bigint not null primary key ," +
      "  venue_id   bigint not null," +
      "  singer_id  bigint not null," +
      "  start_time timestamptz," +
      "  end_time   timestamptz," +
      "  constraint fk_concerts_venues foreign key" +
      "    (venue_id) references venues (venue_id)," +
      "  constraint fk_concerts_singers foreign key" +
      "    (singer_id) references singers (singer_id)" +
      ")");
  await connection.query("run batch");
  console.log("Added venues and concerts tables");

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def ddl_batch(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        # DDL can only be executed when autocommit=True.
        conn.autocommit = True
        # Use a pipeline to batch multiple statements together.
        # Executing multiple DDL statements as one batch is
        # more efficient than executing each statement
        # individually.
        with conn.pipeline():
            # The following statements are buffered on PGAdapter
            # until the pipeline ends.
            conn.execute("CREATE TABLE venues ("
                         "  venue_id    bigint not null primary key,"
                         "  name        varchar(1024),"
                         "  description jsonb"
                         ")")
            conn.execute("CREATE TABLE concerts ("
                         "  concert_id bigint not null primary key ,"
                         "  venue_id   bigint not null,"
                         "  singer_id  bigint not null,"
                         "  start_time timestamptz,"
                         "  end_time   timestamptz,"
                         "  constraint fk_concerts_venues foreign key"
                         "    (venue_id) references venues (venue_id),"
                         "  constraint fk_concerts_singers foreign key"
                         "    (singer_id) references singers (singer_id)"
                         ")")
        print("Added venues and concerts tables")

C#

using Npgsql;

namespace dotnet_snippets;

public static class DdlBatchSample
{
    public static void DdlBatch(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Create two new tables in one batch.
        var batch = connection.CreateBatch();
        batch.BatchCommands.Add(new NpgsqlBatchCommand(
            "CREATE TABLE venues ("
            + "  venue_id    bigint not null primary key,"
            + "  name        varchar(1024),"
            + "  description jsonb"
            + ")"));
        batch.BatchCommands.Add(new NpgsqlBatchCommand(
            "CREATE TABLE concerts ("
            + "  concert_id bigint not null primary key ,"
            + "  venue_id   bigint not null,"
            + "  singer_id  bigint not null,"
            + "  start_time timestamptz,"
            + "  end_time   timestamptz,"
            + "  constraint fk_concerts_venues foreign key"
            + "    (venue_id) references venues (venue_id),"
            + "  constraint fk_concerts_singers foreign key"
            + "    (singer_id) references singers (singer_id)"
            + ")"));
        batch.ExecuteNonQuery();
        Console.WriteLine("Added venues and concerts tables");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./ddl_batch.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar ddlbatch example-db

Go

go run sample_runner.go ddlbatch example-db

Node.js

npm start ddlbatch example-db

Python

python ddl_batch.py example-db

C#

dotnet run ddlbatch example-db

Deberías ver lo siguiente:

Added venues and concerts tables

Escribe datos en la columna nueva

Con el siguiente código, se escriben datos en la columna nueva. Establece MarketingBudget en 100000 para la fila marcada por Albums(1, 1) y en 500000 para la fila marcada por Albums(2, 2).

PGAdapter traduce el comando COPY de PostgreSQL a mutaciones. De forma predeterminada, los comandos COPY se traducen a mutaciones Insert. Ejecuta set spanner.copy_upsert=true para traducir los comandos de COPY al InsertOrUpdate. Esto se puede usar para actualizar los datos existentes en Spanner

Sugerencia: Para obtener una lista completa de los comandos que se pueden usar para acceder a las funciones de Spanner con PGAdapter, consulta Comandos de administración de sesiones de PGAdapter.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Instruct PGAdapter to use insert-or-update for COPY statements.
# This enables us to use COPY to update data.
psql -c "set spanner.copy_upsert=true" \
     -c "COPY albums (singer_id, album_id, marketing_budget) FROM STDIN
         WITH (DELIMITER ';')" \
<< DATA
1;1;100000
2;2;500000
DATA

echo "Copied albums using upsert"

Java

import java.io.IOException;
import java.io.StringReader;
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;
import org.postgresql.PGConnection;
import org.postgresql.copy.CopyManager;

class UpdateDataWithCopy {

  static void updateDataWithCopy(String host, int port, String database)
      throws SQLException, IOException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Unwrap the PostgreSQL JDBC connection interface to get access to
      // a CopyManager.
      PGConnection pgConnection = connection.unwrap(PGConnection.class);
      CopyManager copyManager = pgConnection.getCopyAPI();

      // Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
      // will succeed even if it exceeds Spanner's mutation limit per transaction.
      connection
          .createStatement()
          .execute("set spanner.autocommit_dml_mode='partitioned_non_atomic'");

      // Instruct PGAdapter to use insert-or-update for COPY statements.
      // This enables us to use COPY to update existing data.
      connection.createStatement().execute("set spanner.copy_upsert=true");

      // COPY uses mutations to insert or update existing data in Spanner.
      long numAlbums =
          copyManager.copyIn(
              "COPY albums (singer_id, album_id, marketing_budget) FROM STDIN",
              new StringReader("1\t1\t100000\n" + "2\t2\t500000\n"));
      System.out.printf("Updated %d albums\n", numAlbums);
    }
  }
}

Go

import (
	"context"
	"fmt"
	"io"

	"github.com/jackc/pgx/v5"
)

func UpdateDataWithCopy(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Enable non-atomic mode. This makes the COPY operation non-atomic,
	// and allows it to exceed the Spanner mutation limit.
	if _, err := conn.Exec(ctx,
		"set spanner.autocommit_dml_mode='partitioned_non_atomic'"); err != nil {
		return err
	}
	// Instruct PGAdapter to use insert-or-update for COPY statements.
	// This enables us to use COPY to update data.
	if _, err := conn.Exec(ctx, "set spanner.copy_upsert=true"); err != nil {
		return err
	}

	// Create a pipe that can be used to write the data manually that we want to copy.
	reader, writer := io.Pipe()
	// Write the data to the pipe using a separate goroutine. This allows us to stream the data
	// to the COPY operation row-by-row.
	go func() error {
		for _, record := range []string{"1\t1\t100000\n", "2\t2\t500000\n"} {
			if _, err := writer.Write([]byte(record)); err != nil {
				return err
			}
		}
		if err := writer.Close(); err != nil {
			return err
		}
		return nil
	}()
	tag, err := conn.PgConn().CopyFrom(ctx, reader, "COPY albums (singer_id, album_id, marketing_budget) FROM STDIN")
	if err != nil {
		return err
	}
	fmt.Printf("Updated %v albums\n", tag.RowsAffected())

	return nil
}

Node.js

import { Client } from 'pg';
import { pipeline } from 'node:stream/promises'
import { from as copyFrom } from 'pg-copy-streams'
import {Readable} from "stream";

async function updateDataWithCopy(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
  // will succeed even if it exceeds Spanner's mutation limit per transaction.
  await connection.query("set spanner.autocommit_dml_mode='partitioned_non_atomic'");

  // Instruct PGAdapter to use insert-or-update for COPY statements.
  // This enables us to use COPY to update existing data.
  await connection.query("set spanner.copy_upsert=true");

  // Copy data to Spanner using the COPY command.
  const copyStream = copyFrom('COPY albums (singer_id, album_id, marketing_budget) FROM STDIN');
  const ingestStream = connection.query(copyStream);

  // Create a source stream and attach the source to the destination.
  const sourceStream = new Readable();
  const operation = pipeline(sourceStream, ingestStream);
  // Manually push data to the source stream to write data to Spanner.
  sourceStream.push("1\t1\t100000\n");
  sourceStream.push("2\t2\t500000\n");
  // Push a 'null' to indicate the end of the stream.
  sourceStream.push(null);
  // Wait for the copy operation to finish.
  await operation;
  console.log(`Updated ${copyStream.rowCount} albums`);

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def update_data_with_copy(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            # Instruct PGAdapter to use insert-or-update for COPY statements.
            # This enables us to use COPY to update data.
            cur.execute("set spanner.copy_upsert=true")

            # COPY uses mutations to insert or update existing data in Spanner.
            with cur.copy("COPY albums (singer_id, album_id, marketing_budget) "
                          "FROM STDIN") as copy:
                copy.write_row((1, 1, 100000))
                copy.write_row((2, 2, 500000))
            print("Updated %d albums" % cur.rowcount)

C#

using Npgsql;

namespace dotnet_snippets;

public static class UpdateDataWithCopySample
{
    public static void UpdateDataWithCopy(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Enable 'partitioned_non_atomic' mode. This ensures that the COPY operation
        // will succeed even if it exceeds Spanner's mutation limit per transaction.
        using var cmd = connection.CreateCommand();
        cmd.CommandText = "set spanner.autocommit_dml_mode='partitioned_non_atomic'";
        cmd.ExecuteNonQuery();

        // Instruct PGAdapter to use insert-or-update for COPY statements.
        // This enables us to use COPY to update existing data.
        cmd.CommandText = "set spanner.copy_upsert=true";
        cmd.ExecuteNonQuery();

        // COPY uses mutations to insert or update existing data in Spanner.
        using (var albumWriter = connection.BeginTextImport(
                   "COPY albums (singer_id, album_id, marketing_budget) FROM STDIN"))
        {
            albumWriter.WriteLine("1\t1\t100000");
            albumWriter.WriteLine("2\t2\t500000");
        }
        Console.WriteLine($"Updated 2 albums");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./update_data_with_copy.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar update example-db

Go

go run sample_runner.go update example-db

Node.js

npm start update example-db

Python

python update_data_with_copy.py example-db

C#

dotnet run update example-db

Deberías ver lo siguiente:

Updated 2 albums

También puedes ejecutar una consulta de SQL para obtener los valores que acabas de escribir.

Este es el código para ejecutar la consulta:

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql -c "SELECT singer_id, album_id, marketing_budget
         FROM albums
         ORDER BY singer_id, album_id"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;

class QueryDataWithNewColumn {
  static void queryDataWithNewColumn(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      try (ResultSet resultSet =
          connection
              .createStatement()
              .executeQuery(
                  "SELECT singer_id, album_id, marketing_budget "
                      + "FROM albums "
                      + "ORDER BY singer_id, album_id")) {
        while (resultSet.next()) {
          System.out.printf(
              "%d %d %s\n",
              resultSet.getLong("singer_id"),
              resultSet.getLong("album_id"),
              resultSet.getString("marketing_budget"));
        }
      }
    }
  }
}

Go

import (
	"context"
	"database/sql"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func QueryDataWithNewColumn(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	rows, err := conn.Query(ctx, "SELECT singer_id, album_id, marketing_budget "+
		"FROM albums "+
		"ORDER BY singer_id, album_id")
	defer rows.Close()
	if err != nil {
		return err
	}
	for rows.Next() {
		var singerId, albumId int64
		var marketingBudget sql.NullString
		err = rows.Scan(&singerId, &albumId, &marketingBudget)
		if err != nil {
			return err
		}
		var budget string
		if marketingBudget.Valid {
			budget = marketingBudget.String
		} else {
			budget = "NULL"
		}
		fmt.Printf("%v %v %v\n", singerId, albumId, budget)
	}

	return rows.Err()
}

Node.js

import { Client } from 'pg';

async function queryDataWithNewColumn(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  const result = await connection.query(
      "SELECT singer_id, album_id, marketing_budget "
      + "FROM albums "
      + "ORDER BY singer_id, album_id"
  );
  for (const row of result.rows) {
    console.log(`${row["singer_id"]} ${row["album_id"]} ${row["marketing_budget"]}`);
  }

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def query_data_with_new_column(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            cur.execute("SELECT singer_id, album_id, marketing_budget "
                        "FROM albums "
                        "ORDER BY singer_id, album_id")
            for album in cur:
                print(album)

C#

using Npgsql;

namespace dotnet_snippets;

public static class QueryDataWithNewColumnSample
{
    public static void QueryWithNewColumnData(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        using var cmd = new NpgsqlCommand("SELECT singer_id, album_id, marketing_budget "
                                          + "FROM albums "
                                          + "ORDER BY singer_id, album_id", connection);
        using var reader = cmd.ExecuteReader();
        while (reader.Read())
        {
            Console.WriteLine($"{reader["singer_id"]} {reader["album_id"]} {reader["marketing_budget"]}");
        }
    }
}

Ejecuta la consulta con este comando:

psql

PGDATABASE=example-db ./query_data_with_new_column.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar querymarketingbudget example-db

Go

go run sample_runner.go querymarketingbudget example-db

Node.js

npm start querymarketingbudget example-db

Python

python query_data_with_new_column.py example-db

C#

dotnet run querymarketingbudget example-db

Deberías ver lo siguiente:

1 1 100000
1 2 null
2 1 null
2 2 500000
2 3 null

Actualiza datos

Puedes actualizar los datos mediante DML en una transacción de lectura y escritura.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql << SQL
  -- Transfer marketing budget from one album to another.
  -- We do it in a transaction to ensure that the transfer is atomic.
  -- Begin a read/write transaction.
  begin;

  -- Increase the marketing budget of album 1 if album 2 has enough budget.
  -- The condition that album 2 has enough budget is guaranteed for the
  -- duration of the transaction, as read/write transactions in Spanner use
  -- external consistency as the default isolation level.
  update albums set
    marketing_budget = marketing_budget + 200000
  where singer_id = 1
    and  album_id = 1
    and exists (
      select album_id
      from albums
      where singer_id = 2
        and  album_id = 2
        and marketing_budget > 200000
      );

  -- Decrease the marketing budget of album 2.      
  update albums set
    marketing_budget = marketing_budget - 200000
  where singer_id = 2
    and  album_id = 2
    and marketing_budget > 200000;

  -- Commit the transaction to make the changes to both marketing budgets
  -- durably stored in the database and visible to other transactions.
  commit;  
SQL

echo "Transferred marketing budget from Album 2 to Album 1"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

class UpdateDataWithTransaction {

  static void writeWithTransactionUsingDml(String host, int port, String database)
      throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Set AutoCommit=false to enable transactions.
      connection.setAutoCommit(false);

      // Transfer marketing budget from one album to another. We do it in a
      // transaction to ensure that the transfer is atomic. There is no need
      // to explicitly start the transaction. The first statement on the
      // connection will start a transaction when AutoCommit=false.
      String selectMarketingBudgetSql =
          "SELECT marketing_budget from albums WHERE singer_id = ? and album_id = ?";
      long album2Budget = 0;
      try (PreparedStatement selectMarketingBudgetStatement =
          connection.prepareStatement(selectMarketingBudgetSql)) {
        // Bind the query parameters to SingerId=2 and AlbumId=2.
        selectMarketingBudgetStatement.setLong(1, 2);
        selectMarketingBudgetStatement.setLong(2, 2);
        try (ResultSet resultSet = selectMarketingBudgetStatement.executeQuery()) {
          while (resultSet.next()) {
            album2Budget = resultSet.getLong("marketing_budget");
          }
        }
        // The transaction will only be committed if this condition still holds
        // at the time of commit. Otherwise, the transaction will be aborted.
        final long transfer = 200000;
        if (album2Budget >= transfer) {
          long album1Budget = 0;
          // Re-use the existing PreparedStatement for selecting the
          // marketing_budget to get the budget for Album 1.
          // Bind the query parameters to SingerId=1 and AlbumId=1.
          selectMarketingBudgetStatement.setLong(1, 1);
          selectMarketingBudgetStatement.setLong(2, 1);
          try (ResultSet resultSet = selectMarketingBudgetStatement.executeQuery()) {
            while (resultSet.next()) {
              album1Budget = resultSet.getLong("marketing_budget");
            }
          }

          // Transfer part of the marketing budget of Album 2 to Album 1.
          album1Budget += transfer;
          album2Budget -= transfer;
          String updateSql =
              "UPDATE albums "
                  + "SET marketing_budget = ? "
                  + "WHERE singer_id = ? and album_id = ?";
          try (PreparedStatement updateStatement = connection.prepareStatement(updateSql)) {
            // Update Album 1.
            int paramIndex = 0;
            updateStatement.setLong(++paramIndex, album1Budget);
            updateStatement.setLong(++paramIndex, 1);
            updateStatement.setLong(++paramIndex, 1);
            // Create a DML batch by calling addBatch
            // on the current PreparedStatement.
            updateStatement.addBatch();

            // Update Album 2 in the same DML batch.
            paramIndex = 0;
            updateStatement.setLong(++paramIndex, album2Budget);
            updateStatement.setLong(++paramIndex, 2);
            updateStatement.setLong(++paramIndex, 2);
            updateStatement.addBatch();

            // Execute both DML statements in one batch.
            updateStatement.executeBatch();
          }
        }
      }
      // Commit the current transaction.
      connection.commit();
      System.out.println("Transferred marketing budget from Album 2 to Album 1");
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func WriteWithTransactionUsingDml(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Transfer marketing budget from one album to another. We do it in a
	// transaction to ensure that the transfer is atomic.
	tx, err := conn.Begin(ctx)
	if err != nil {
		return err
	}
	const selectSql = "SELECT marketing_budget " +
		"from albums " +
		"WHERE singer_id = $1 and album_id = $2"
	// Get the marketing_budget of singer 2 / album 2.
	row := tx.QueryRow(ctx, selectSql, 2, 2)
	var budget2 int64
	if err := row.Scan(&budget2); err != nil {
		tx.Rollback(ctx)
		return err
	}
	const transfer = 20000
	// The transaction will only be committed if this condition still holds
	// at the time of commit. Otherwise, the transaction will be aborted.
	if budget2 >= transfer {
		// Get the marketing_budget of singer 1 / album 1.
		row := tx.QueryRow(ctx, selectSql, 1, 1)
		var budget1 int64
		if err := row.Scan(&budget1); err != nil {
			tx.Rollback(ctx)
			return err
		}
		// Transfer part of the marketing budget of Album 2 to Album 1.
		budget1 += transfer
		budget2 -= transfer
		const updateSql = "UPDATE albums " +
			"SET marketing_budget = $1 " +
			"WHERE singer_id = $2 and album_id = $3"
		// Start a DML batch and execute it as part of the current transaction.
		batch := &pgx.Batch{}
		batch.Queue(updateSql, budget1, 1, 1)
		batch.Queue(updateSql, budget2, 2, 2)
		br := tx.SendBatch(ctx, batch)
		_, err = br.Exec()
		if err := br.Close(); err != nil {
			tx.Rollback(ctx)
			return err
		}
	}
	// Commit the current transaction.
	tx.Commit(ctx)
	fmt.Println("Transferred marketing budget from Album 2 to Album 1")

	return nil
}

Node.js

import { Client } from 'pg';

async function writeWithTransactionUsingDml(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Transfer marketing budget from one album to another. We do it in a
  // transaction to ensure that the transfer is atomic. node-postgres
  // requires you to explicitly start the transaction by executing 'begin'.
  await connection.query("begin");
  const selectMarketingBudgetSql = "SELECT marketing_budget " +
      "from albums " +
      "WHERE singer_id = $1 and album_id = $2";
  // Get the marketing_budget of singer 2 / album 2.
  const album2BudgetResult = await connection.query(selectMarketingBudgetSql, [2, 2]);
  let album2Budget = album2BudgetResult.rows[0]["marketing_budget"];
  const transfer = 200000;
  // The transaction will only be committed if this condition still holds
  // at the time of commit. Otherwise, the transaction will be aborted.
  if (album2Budget >= transfer) {
    // Get the marketing budget of singer 1 / album 1.
    const album1BudgetResult = await connection.query(selectMarketingBudgetSql, [1, 1]);
    let album1Budget = album1BudgetResult.rows[0]["marketing_budget"];
    // Transfer part of the marketing budget of Album 2 to Album 1.
    album1Budget += transfer;
    album2Budget -= transfer;
    const updateSql = "UPDATE albums " +
        "SET marketing_budget = $1 " +
        "WHERE singer_id = $2 and album_id = $3";
    // Start a DML batch. This batch will become part of the current transaction.
    // TODO: Enable when https://github.com/googleapis/java-spanner/pull/3114 has been merged
    // await connection.query("start batch dml");
    // Update the marketing budget of both albums.
    await connection.query(updateSql, [album1Budget, 1, 1]);
    await connection.query(updateSql, [album2Budget, 2, 2]);
    // TODO: Enable when https://github.com/googleapis/java-spanner/pull/3114 has been merged
    // await connection.query("run batch");
  }
  // Commit the current transaction.
  await connection.query("commit");
  console.log("Transferred marketing budget from Album 2 to Album 1");

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def update_data_with_transaction(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        # Set autocommit=False to use transactions.
        # The first statement that is executed starts the transaction.
        conn.autocommit = False
        with conn.cursor() as cur:
            # Transfer marketing budget from one album to another.
            # We do it in a transaction to ensure that the transfer is atomic.
            # There is no need to explicitly start the transaction. The first
            # statement on the connection will start a transaction when
            # AutoCommit=false.
            select_marketing_budget_sql = ("SELECT marketing_budget "
                                           "from albums "
                                           "WHERE singer_id = %s "
                                           "and album_id = %s")
            # Get the marketing budget of Album #2.
            cur.execute(select_marketing_budget_sql, (2, 2))
            album2_budget = cur.fetchone()[0]
            transfer = 200000
            if album2_budget > transfer:
                # Get the marketing budget of Album #1.
                cur.execute(select_marketing_budget_sql, (1, 1))
                album1_budget = cur.fetchone()[0]
                # Transfer the marketing budgets and write the update back
                # to the database.
                album1_budget += transfer
                album2_budget -= transfer
                update_sql = ("update albums "
                              "set marketing_budget = %s "
                              "where singer_id = %s "
                              "and   album_id = %s")
                # Use a pipeline to execute two DML statements in one batch.
                with conn.pipeline():
                    cur.execute(update_sql, (album1_budget, 1, 1,))
                    cur.execute(update_sql, (album2_budget, 2, 2,))
            else:
                print("Insufficient budget to transfer")
        # Commit the transaction.
        conn.commit()
        print("Transferred marketing budget from Album 2 to Album 1")

C#

using Npgsql;
using System.Data;

namespace dotnet_snippets;

public static class TagsSample
{
    public static void Tags(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Start a transaction with isolation level Serializable.
        // Spanner only supports this isolation level. Trying to use a lower
        // isolation level (including the default isolation level READ COMMITTED),
        // will result in an error.
        var transaction = connection.BeginTransaction(IsolationLevel.Serializable);

        // Create a command that uses the current transaction.
        using var cmd = connection.CreateCommand();
        cmd.Transaction = transaction;

        // Set the TRANSACTION_TAG session variable to set a transaction tag
        // for the current transaction.
        cmd.CommandText = "set spanner.transaction_tag='example-tx-tag'";
        cmd.ExecuteNonQuery();

        // Set the STATEMENT_TAG session variable to set the request tag
        // that should be included with the next SQL statement.
        cmd.CommandText = "set spanner.statement_tag='query-marketing-budget'";
        cmd.ExecuteNonQuery();

        // Get the marketing_budget of Album (1,1).
        cmd.CommandText = "select marketing_budget from albums where singer_id=$1 and album_id=$2";
        cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
        cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
        var marketingBudget = (long?)cmd.ExecuteScalar();

        // Reduce the marketing budget by 10% if it is more than 1,000.
        if (marketingBudget > 1000L)
        {
            marketingBudget -= (long) (marketingBudget * 0.1);

            // Set the statement tag to use for the update statement.
            cmd.Parameters.Clear();
            cmd.CommandText = "set spanner.statement_tag='reduce-marketing-budget'";
            cmd.ExecuteNonQuery();

            cmd.CommandText = "update albums set marketing_budget=$1 where singer_id=$2 AND album_id=$3";
            cmd.Parameters.Add(new NpgsqlParameter { Value = marketingBudget });
            cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
            cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
            cmd.ExecuteNonQuery();
        }

        // Commit the current transaction.
        transaction.Commit();
        Console.WriteLine("Reduced marketing budget");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./update_data_with_transaction.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar writewithtransactionusingdml example-db

Go

go run sample_runner.go writewithtransactionusingdml example-db

Node.js

npm start writewithtransactionusingdml example-db

Python

python update_data_with_transaction.py example-db

C#

dotnet run writewithtransactionusingdml example-db

Deberías ver lo siguiente:

Transferred marketing budget from Album 2 to Album 1

Etiquetas de transacción y de solicitud

Utiliza etiquetas de transacción y etiquetas de solicitud. para solucionar problemas de transacciones y consultas en Spanner. Puedes configurar etiquetas de transacción y de solicitud con los atributos SPANNER.TRANSACTION_TAG y SPANNER.STATEMENT_TAG variables de sesión.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql << SQL
  -- Start a transaction.
  begin;
  -- Set the TRANSACTION_TAG session variable to set a transaction tag
  -- for the current transaction. This can only be executed at the start
  -- of the transaction.
  set spanner.transaction_TAG='example-tx-tag';

  -- Set the STATEMENT_TAG session variable to set the request tag
  -- that should be included with the next SQL statement.
  set spanner.statement_tag='query-marketing-budget';

  select marketing_budget
  from albums
  where singer_id = 1
    and album_id  = 1;

  -- Reduce the marketing budget by 10% if it is more than 1,000.
  -- Set a statement tag for the update statement.
  set spanner.statement_tag='reduce-marketing-budget';

  update albums
    set marketing_budget = marketing_budget - (marketing_budget * 0.1)::bigint
  where singer_id = 1
    and album_id  = 1
    and marketing_budget > 1000;

  commit;  
SQL

echo "Reduced marketing budget"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

class Tags {

  static void tags(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Set AutoCommit=false to enable transactions.
      connection.setAutoCommit(false);
      // Set the TRANSACTION_TAG session variable to set a transaction tag
      // for the current transaction.
      connection.createStatement().execute("set spanner.transaction_tag='example-tx-tag'");

      // Set the STATEMENT_TAG session variable to set the request tag
      // that should be included with the next SQL statement.
      connection.createStatement().execute("set spanner.statement_tag='query-marketing-budget'");
      long marketingBudget = 0L;
      long singerId = 1L;
      long albumId = 1L;
      try (PreparedStatement statement =
          connection.prepareStatement(
              "select marketing_budget from albums where singer_id=? and album_id=?")) {
        statement.setLong(1, singerId);
        statement.setLong(2, albumId);
        try (ResultSet albumResultSet = statement.executeQuery()) {
          while (albumResultSet.next()) {
            marketingBudget = albumResultSet.getLong(1);
          }
        }
      }
      // Reduce the marketing budget by 10% if it is more than 1,000.
      final long maxMarketingBudget = 1000L;
      final float reduction = 0.1f;
      if (marketingBudget > maxMarketingBudget) {
        marketingBudget -= (long) (marketingBudget * reduction);
        connection.createStatement().execute("set spanner.statement_tag='reduce-marketing-budget'");
        try (PreparedStatement statement =
            connection.prepareStatement(
                "update albums set marketing_budget=? where singer_id=? AND album_id=?")) {
          int paramIndex = 0;
          statement.setLong(++paramIndex, marketingBudget);
          statement.setLong(++paramIndex, singerId);
          statement.setLong(++paramIndex, albumId);
          statement.executeUpdate();
        }
      }

      // Commit the current transaction.
      connection.commit();
      System.out.println("Reduced marketing budget");
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func Tags(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	tx, err := conn.Begin(ctx)
	if err != nil {
		return err
	}

	// Set the TRANSACTION_TAG session variable to set a transaction tag
	// for the current transaction.
	_, _ = tx.Exec(ctx, "set spanner.transaction_tag='example-tx-tag'")

	// Set the STATEMENT_TAG session variable to set the request tag
	// that should be included with the next SQL statement.
	_, _ = tx.Exec(ctx, "set spanner.statement_tag='query-marketing-budget'")

	row := tx.QueryRow(ctx, "select marketing_budget "+
		"from albums "+
		"where singer_id=$1 and album_id=$2", 1, 1)
	var budget int64
	if err := row.Scan(&budget); err != nil {
		tx.Rollback(ctx)
		return err
	}

	// Reduce the marketing budget by 10% if it is more than 1,000.
	if budget > 1000 {
		budget = int64(float64(budget) - float64(budget)*0.1)
		_, _ = tx.Exec(ctx, "set spanner.statement_tag='reduce-marketing-budget'")
		if _, err := tx.Exec(ctx, "update albums set marketing_budget=$1 where singer_id=$2 AND album_id=$3", budget, 1, 1); err != nil {
			tx.Rollback(ctx)
			return err
		}
	}
	// Commit the current transaction.
	tx.Commit(ctx)
	fmt.Println("Reduced marketing budget")

	return nil
}

Node.js

import { Client } from 'pg';

async function tags(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  await connection.query("begin");
  // Set the TRANSACTION_TAG session variable to set a transaction tag
  // for the current transaction.
  await connection.query("set spanner.transaction_tag='example-tx-tag'");
  // Set the STATEMENT_TAG session variable to set the request tag
  // that should be included with the next SQL statement.
  await connection.query("set spanner.statement_tag='query-marketing-budget'");
  const budgetResult = await connection.query(
      "select marketing_budget " +
      "from albums " +
      "where singer_id=$1 and album_id=$2", [1, 1])
  let budget = budgetResult.rows[0]["marketing_budget"];
  // Reduce the marketing budget by 10% if it is more than 1,000.
  if (budget > 1000) {
    budget = budget - budget * 0.1;
    await connection.query("set spanner.statement_tag='reduce-marketing-budget'");
    await connection.query("update albums set marketing_budget=$1 "
        + "where singer_id=$2 AND album_id=$3", [budget, 1, 1]);
  }
  // Commit the current transaction.
  await connection.query("commit");
  console.log("Reduced marketing budget");

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def tags(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        # Set autocommit=False to enable transactions.
        conn.autocommit = False
        with conn.cursor() as cur:
            # Set the TRANSACTION_TAG session variable to set a transaction tag
            # for the current transaction.
            cur.execute("set spanner.transaction_TAG='example-tx-tag'")

            # Set the STATEMENT_TAG session variable to set the request tag
            # that should be included with the next SQL statement.
            cur.execute("set spanner.statement_tag='query-marketing-budget'")

            singer_id = 1
            album_id = 1
            cur.execute("select marketing_budget "
                        "from albums "
                        "where singer_id = %s "
                        "  and album_id  = %s",
                        (singer_id, album_id,))
            marketing_budget = cur.fetchone()[0]

            # Reduce the marketing budget by 10% if it is more than 1,000.
            max_marketing_budget = 1000
            reduction = 0.1
            if marketing_budget > max_marketing_budget:
                # Make sure the marketing_budget remains an int.
                marketing_budget -= int(marketing_budget * reduction)
                # Set a statement tag for the update statement.
                cur.execute(
                    "set spanner.statement_tag='reduce-marketing-budget'")
                cur.execute("update albums set marketing_budget = %s "
                            "where singer_id = %s "
                            "  and album_id  = %s",
                            (marketing_budget, singer_id, album_id,))
            else:
                print("Marketing budget already less than or equal to 1,000")
        # Commit the transaction.
        conn.commit()
        print("Reduced marketing budget")

C#

using Npgsql;
using System.Data;

namespace dotnet_snippets;

public static class TagsSample
{
    public static void Tags(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Start a transaction with isolation level Serializable.
        // Spanner only supports this isolation level. Trying to use a lower
        // isolation level (including the default isolation level READ COMMITTED),
        // will result in an error.
        var transaction = connection.BeginTransaction(IsolationLevel.Serializable);

        // Create a command that uses the current transaction.
        using var cmd = connection.CreateCommand();
        cmd.Transaction = transaction;

        // Set the TRANSACTION_TAG session variable to set a transaction tag
        // for the current transaction.
        cmd.CommandText = "set spanner.transaction_tag='example-tx-tag'";
        cmd.ExecuteNonQuery();

        // Set the STATEMENT_TAG session variable to set the request tag
        // that should be included with the next SQL statement.
        cmd.CommandText = "set spanner.statement_tag='query-marketing-budget'";
        cmd.ExecuteNonQuery();

        // Get the marketing_budget of Album (1,1).
        cmd.CommandText = "select marketing_budget from albums where singer_id=$1 and album_id=$2";
        cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
        cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
        var marketingBudget = (long?)cmd.ExecuteScalar();

        // Reduce the marketing budget by 10% if it is more than 1,000.
        if (marketingBudget > 1000L)
        {
            marketingBudget -= (long) (marketingBudget * 0.1);

            // Set the statement tag to use for the update statement.
            cmd.Parameters.Clear();
            cmd.CommandText = "set spanner.statement_tag='reduce-marketing-budget'";
            cmd.ExecuteNonQuery();

            cmd.CommandText = "update albums set marketing_budget=$1 where singer_id=$2 AND album_id=$3";
            cmd.Parameters.Add(new NpgsqlParameter { Value = marketingBudget });
            cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
            cmd.Parameters.Add(new NpgsqlParameter { Value = 1L });
            cmd.ExecuteNonQuery();
        }

        // Commit the current transaction.
        transaction.Commit();
        Console.WriteLine("Reduced marketing budget");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./tags.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar tags example-db

Go

go run sample_runner.go tags example-db

Node.js

npm start tags example-db

Python

python tags.py example-db

C#

dotnet run tags example-db

Sugerencia: Para obtener una lista completa de los comandos que se pueden usar para acceder a las funciones de Spanner con PGAdapter, consulta Comandos de administración de sesiones de PGAdapter.

Recupera datos mediante transacciones de solo lectura

Supongamos que quieres ejecutar más de una lectura en la misma marca de tiempo. En las transacciones de solo lectura, se observa un prefijo coherente del historial de confirmaciones de transacciones, por lo que la aplicación siempre obtiene datos coherentes. Configura la conexión como de solo lectura o usa el SQL SET TRANSACTION READ ONLY. para ejecutar una transacción de solo lectura.

Nota: PGAdapter admite varias instrucciones SQL adicionales para ejecutar tipos específicos de transacciones y lotes, y para acceder a funciones específicas de Spanner. Para obtener una lista completa de las declaraciones admitidas, consulta Comandos de administración de sesiones de PGAdapter

A continuación, se muestra cómo ejecutar una consulta y cómo realizar una lectura en la misma transacción de solo lectura:

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

psql << SQL
  -- Begin a transaction.
  begin;
  -- Change the current transaction to a read-only transaction.
  -- This statement can only be executed at the start of a transaction.
  set transaction read only;

  -- The following two queries use the same read-only transaction.
  select singer_id, album_id, album_title
  from albums
  order by singer_id, album_id;

  select singer_id, album_id, album_title
  from albums
  order by album_title;

  -- Read-only transactions must also be committed or rolled back to mark
  -- the end of the transaction. There is no semantic difference between
  -- rolling back or committing a read-only transaction.
  commit;  
SQL

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;

class ReadOnlyTransaction {
  static void readOnlyTransaction(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Set AutoCommit=false to enable transactions.
      connection.setAutoCommit(false);
      // This SQL statement instructs the JDBC driver to use
      // a read-only transaction.
      connection.createStatement().execute("set transaction read only");

      try (ResultSet resultSet =
          connection
              .createStatement()
              .executeQuery(
                  "SELECT singer_id, album_id, album_title "
                      + "FROM albums "
                      + "ORDER BY singer_id, album_id")) {
        while (resultSet.next()) {
          System.out.printf(
              "%d %d %s\n",
              resultSet.getLong("singer_id"),
              resultSet.getLong("album_id"),
              resultSet.getString("album_title"));
        }
      }
      try (ResultSet resultSet =
          connection
              .createStatement()
              .executeQuery(
                  "SELECT singer_id, album_id, album_title "
                      + "FROM albums "
                      + "ORDER BY album_title")) {
        while (resultSet.next()) {
          System.out.printf(
              "%d %d %s\n",
              resultSet.getLong("singer_id"),
              resultSet.getLong("album_id"),
              resultSet.getString("album_title"));
        }
      }
      // End the read-only transaction by calling commit().
      connection.commit();
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func ReadOnlyTransaction(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Start a read-only transaction by supplying additional transaction options.
	tx, err := conn.BeginTx(ctx, pgx.TxOptions{AccessMode: pgx.ReadOnly})

	albumsOrderedById, err := tx.Query(ctx, "SELECT singer_id, album_id, album_title FROM albums ORDER BY singer_id, album_id")
	defer albumsOrderedById.Close()
	if err != nil {
		return err
	}
	for albumsOrderedById.Next() {
		var singerId, albumId int64
		var title string
		err = albumsOrderedById.Scan(&singerId, &albumId, &title)
		if err != nil {
			return err
		}
		fmt.Printf("%v %v %v\n", singerId, albumId, title)
	}

	albumsOrderedTitle, err := tx.Query(ctx, "SELECT singer_id, album_id, album_title FROM albums ORDER BY album_title")
	defer albumsOrderedTitle.Close()
	if err != nil {
		return err
	}
	for albumsOrderedTitle.Next() {
		var singerId, albumId int64
		var title string
		err = albumsOrderedTitle.Scan(&singerId, &albumId, &title)
		if err != nil {
			return err
		}
		fmt.Printf("%v %v %v\n", singerId, albumId, title)
	}

	// End the read-only transaction by calling Commit().
	return tx.Commit(ctx)
}

Node.js

import { Client } from 'pg';

async function readOnlyTransaction(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Start a transaction.
  await connection.query("begin");
  // This SQL statement instructs the PGAdapter to make it a read-only transaction.
  await connection.query("set transaction read only");

  const albumsOrderById = await connection.query(
      "SELECT singer_id, album_id, album_title "
      + "FROM albums "
      + "ORDER BY singer_id, album_id");
  for (const row of albumsOrderById.rows) {
    console.log(`${row["singer_id"]} ${row["album_id"]} ${row["album_title"]}`);
  }
  const albumsOrderByTitle = await connection.query(
      "SELECT singer_id, album_id, album_title "
      + "FROM albums "
      + "ORDER BY album_title");
  for (const row of albumsOrderByTitle.rows) {
    console.log(`${row["singer_id"]} ${row["album_id"]} ${row["album_title"]}`);
  }
  // End the read-only transaction by executing commit.
  await connection.query("commit");

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def read_only_transaction(host: string, port: int, database: string):
    with (psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn):
        # Set autocommit=False to enable transactions.
        conn.autocommit = False

        with conn.cursor() as cur:
            # Change the current transaction to a read-only transaction.
            # This statement can only be executed at the start of a transaction.
            cur.execute("set transaction read only")

            # The following two queries use the same read-only transaction.
            cur.execute("select singer_id, album_id, album_title "
                        "from albums "
                        "order by singer_id, album_id")
            for album in cur:
                print(album)

            cur.execute("select singer_id, album_id, album_title "
                        "from albums "
                        "order by album_title")
            for album in cur:
                print(album)

        # Read-only transactions must also be committed or rolled back to mark
        # the end of the transaction. There is no semantic difference between
        # rolling back or committing a read-only transaction.
        conn.commit()

C#

using Npgsql;
using System.Data;

namespace dotnet_snippets;

public static class ReadOnlyTransactionSample
{
    public static void ReadOnlyTransaction(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Start a read-only transaction.
        // You must specify Serializable as the isolation level, as the npgsql driver
        // will otherwise automatically set the isolation level to read-committed.
        var transaction = connection.BeginTransaction(IsolationLevel.Serializable);
        using var cmd = connection.CreateCommand();
        cmd.Transaction = transaction;
        // This SQL statement instructs the npgsql driver to use
        // a read-only transaction.
        cmd.CommandText = "set transaction read only";
        cmd.ExecuteNonQuery();

        cmd.CommandText = "SELECT singer_id, album_id, album_title " +
                          "FROM albums " +
                          "ORDER BY singer_id, album_id";
        using (var reader = cmd.ExecuteReader())
        {
            while (reader.Read())
            {
                Console.WriteLine($"{reader["singer_id"]} {reader["album_id"]} {reader["album_title"]}");
            }
        }
        cmd.CommandText = "SELECT singer_id, album_id, album_title "
                          + "FROM albums "
                          + "ORDER BY album_title";
        using (var reader = cmd.ExecuteReader())
        {
            while (reader.Read())
            {
                Console.WriteLine($"{reader["singer_id"]} {reader["album_id"]} {reader["album_title"]}");
            }
        }
        // End the read-only transaction by calling commit().
        transaction.Commit();
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./read_only_transaction.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar readonlytransaction example-db

Go

go run sample_runner.go readonlytransaction example-db

Node.js

npm start readonlytransaction example-db

Python

python read_only_transaction.py example-db

C#

dotnet run readonlytransaction example-db

Deberías ver un resultado similar a este:

    1 1 Total Junk
    1 2 Go, Go, Go
    2 1 Green
    2 2 Forever Hold Your Peace
    2 3 Terrified
    2 2 Forever Hold Your Peace
    1 2 Go, Go, Go
    2 1 Green
    2 3 Terrified
    1 1 Total Junk

Consultas particionadas y Data Boost

El partitionQuery La API divide una consulta en partes más pequeñas, o particiones, y usa varias para recuperar las particiones en paralelo. Cada partición se identifica con un token de partición. La API de PartitionQuery tiene una latencia más alta que la estándar Query API, ya que solo está diseñada para operaciones masivas como exportar o analizar toda la base de datos.

Data Boost te permite ejecutar consultas de estadísticas y exportaciones de datos con un impacto casi nulo en las cargas de trabajo existentes de la instancia de Spanner aprovisionada. Data Boost solo admite consultas particionadas.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# 'set spanner.data_boost_enabled=true' enables Data Boost for
# all partitioned queries on this connection.

# 'run partitioned query' is a shortcut for partitioning the query
# that follows and executing each of the partitions that is returned
# by Spanner.

psql -c "set spanner.data_boost_enabled=true" \
     -c "run partitioned query
         select singer_id, first_name, last_name
         from singers"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;

class DataBoost {
  static void dataBoost(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // This enables Data Boost for all partitioned queries on this connection.
      connection.createStatement().execute("set spanner.data_boost_enabled=true");

      // Run a partitioned query. This query will use Data Boost.
      try (ResultSet resultSet =
          connection
              .createStatement()
              .executeQuery(
                  "run partitioned query "
                      + "select singer_id, first_name, last_name "
                      + "from singers")) {
        while (resultSet.next()) {
          System.out.printf(
              "%d %s %s\n",
              resultSet.getLong("singer_id"),
              resultSet.getString("first_name"),
              resultSet.getString("last_name"));
        }
      }
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func DataBoost(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// This enables Data Boost for all partitioned queries on this connection.
	_, _ = conn.Exec(ctx, "set spanner.data_boost_enabled=true")

	// Run a partitioned query. This query will use Data Boost.
	rows, err := conn.Query(ctx, "run partitioned query select singer_id, first_name, last_name from singers")
	defer rows.Close()
	if err != nil {
		return err
	}
	for rows.Next() {
		var singerId int64
		var firstName, lastName string
		err = rows.Scan(&singerId, &firstName, &lastName)
		if err != nil {
			return err
		}
		fmt.Printf("%v %v %v\n", singerId, firstName, lastName)
	}

	return nil
}

Node.js

import { Client } from 'pg';

async function dataBoost(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // This enables Data Boost for all partitioned queries on this connection.
  await connection.query("set spanner.data_boost_enabled=true");

  // Run a partitioned query. This query will use Data Boost.
  const singers = await connection.query(
      "run partitioned query "
      + "select singer_id, first_name, last_name "
      + "from singers");
  for (const row of singers.rows) {
    console.log(`${row["singer_id"]} ${row["first_name"]} ${row["last_name"]}`);
  }

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def data_boost(host: string, port: int, database: string):
    with (psycopg.connect("host={host} port={port} dbname={database} "
                          "sslmode=disable".format(host=host,
                                                   port=port,
                                                   database=database)) as conn):
        # Set autocommit=True so each query uses a separate transaction.
        conn.autocommit = True

        with conn.cursor() as cur:
            # This enables Data Boost for all partitioned queries on this
            # connection.
            cur.execute("set spanner.data_boost_enabled=true")

            # Run a partitioned query. This query will use Data Boost.
            cur.execute("run partitioned query "
                        "select singer_id, first_name, last_name "
                        "from singers")
            for singer in cur:
                print(singer)

C#

using Npgsql;

namespace dotnet_snippets;

public static class DataBoostSample
{
    public static void DataBoost(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        using var cmd = connection.CreateCommand();
        // This enables Data Boost for all partitioned queries on this connection.
        cmd.CommandText = "set spanner.data_boost_enabled=true";
        cmd.ExecuteNonQuery();


        // Run a partitioned query. This query will use Data Boost.
        cmd.CommandText = "run partitioned query "
                          + "select singer_id, first_name, last_name "
                          + "from singers";
        using var reader = cmd.ExecuteReader();
        while (reader.Read())
        {
            Console.WriteLine($"{reader["singer_id"]} {reader["first_name"]} {reader["last_name"]}");
        }
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./data_boost.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar databoost example-db

Go

go run sample_runner.go databoost example-db

Node.js

npm start databoost example-db

Python

python data_boost.py example-db

C#

dotnet run databoost example-db

Para obtener más información sobre cómo ejecutar consultas particionadas y usar Data Boost con PGAdapter, consulta Data Boost y sentencias de consulta particionadas.

DML particionado

El lenguaje de manipulación de datos particionado (DML) es diseñados para los siguientes tipos de actualizaciones y eliminaciones masivas:

• Recolección de elementos no usados y limpieza periódicos.
• El restablecimiento de columnas nuevas con valores predeterminados.

psql

#!/bin/bash

export PGHOST="${PGHOST:-localhost}"
export PGPORT="${PGPORT:-5432}"
export PGDATABASE="${PGDATABASE:-example-db}"

# Change the DML mode that is used by this connection to Partitioned
# DML. Partitioned DML is designed for bulk updates and deletes.
# See https://cloud.google.com/spanner/docs/dml-partitioned for more
# information.
psql -c "set spanner.autocommit_dml_mode='partitioned_non_atomic'" \
     -c "update albums
         set marketing_budget=0
         where marketing_budget is null"

echo "Updated albums using Partitioned DML"

Java

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.SQLException;

class PartitionedDml {

  static void partitionedDml(String host, int port, String database) throws SQLException {
    String connectionUrl = String.format("jdbc:postgresql://%s:%d/%s", host, port, database);
    try (Connection connection = DriverManager.getConnection(connectionUrl)) {
      // Enable Partitioned DML on this connection.
      connection
          .createStatement()
          .execute("set spanner.autocommit_dml_mode='partitioned_non_atomic'");
      // Back-fill a default value for the MarketingBudget column.
      long lowerBoundUpdateCount =
          connection
              .createStatement()
              .executeUpdate("update albums set marketing_budget=0 where marketing_budget is null");
      System.out.printf("Updated at least %d albums\n", lowerBoundUpdateCount);
    }
  }
}

Go

import (
	"context"
	"fmt"

	"github.com/jackc/pgx/v5"
)

func PartitionedDML(host string, port int, database string) error {
	ctx := context.Background()
	connString := fmt.Sprintf(
		"postgres://uid:pwd@%s:%d/%s?sslmode=disable",
		host, port, database)
	conn, err := pgx.Connect(ctx, connString)
	if err != nil {
		return err
	}
	defer conn.Close(ctx)

	// Enable Partitioned DML on this connection.
	if _, err := conn.Exec(ctx, "set spanner.autocommit_dml_mode='partitioned_non_atomic'"); err != nil {
		return err
	}
	// Back-fill a default value for the MarketingBudget column.
	tag, err := conn.Exec(ctx, "update albums set marketing_budget=0 where marketing_budget is null")
	if err != nil {
		return err
	}
	fmt.Printf("Updated at least %v albums\n", tag.RowsAffected())

	return nil
}

Node.js

import { Client } from 'pg';

async function partitionedDml(host: string, port: number, database: string): Promise<void> {
  const connection = new Client({
    host: host,
    port: port,
    database: database,
  });
  await connection.connect();

  // Enable Partitioned DML on this connection.
  await connection.query("set spanner.autocommit_dml_mode='partitioned_non_atomic'");

  // Back-fill a default value for the MarketingBudget column.
  const lowerBoundUpdateCount = await connection.query(
      "update albums " +
      "set marketing_budget=0 " +
      "where marketing_budget is null");
  console.log(`Updated at least ${lowerBoundUpdateCount.rowCount} albums`);

  // Close the connection.
  await connection.end();
}

Python

import string
import psycopg


def execute_partitioned_dml(host: string, port: int, database: string):
    with psycopg.connect("host={host} port={port} dbname={database} "
                         "sslmode=disable".format(host=host,
                                                  port=port,
                                                  database=database)) as conn:
        conn.autocommit = True
        with conn.cursor() as cur:
            # Change the DML mode that is used by this connection to Partitioned
            # DML. Partitioned DML is designed for bulk updates and deletes.
            # See https://cloud.google.com/spanner/docs/dml-partitioned for more
            # information.
            cur.execute(
                "set spanner.autocommit_dml_mode='partitioned_non_atomic'")

            # The following statement will use Partitioned DML.
            cur.execute("update albums "
                        "set marketing_budget=0 "
                        "where marketing_budget is null")
            print("Updated at least %d albums" % cur.rowcount)

C#

using Npgsql;

namespace dotnet_snippets;

public static class PartitionedDmlSample
{
    public static void PartitionedDml(string host, int port, string database)
    {
        var connectionString = $"Host={host};Port={port};Database={database};SSL Mode=Disable";
        using var connection = new NpgsqlConnection(connectionString);
        connection.Open();

        // Enable Partitioned DML on this connection.
        using var cmd = connection.CreateCommand();
        cmd.CommandText = "set spanner.autocommit_dml_mode='partitioned_non_atomic'";
        cmd.ExecuteNonQuery();

        // Back-fill a default value for the MarketingBudget column.
        cmd.CommandText = "update albums set marketing_budget=0 where marketing_budget is null";
        var lowerBoundUpdateCount = cmd.ExecuteNonQuery();

        Console.WriteLine($"Updated at least {lowerBoundUpdateCount} albums");
    }
}

Ejecuta la muestra con el siguiente comando:

psql

PGDATABASE=example-db ./partitioned_dml.sh

Java

java -jar target/pgadapter-snippets/pgadapter-samples.jar partitioneddml example-db

Go

go run sample_runner.go partitioneddml example-db

Node.js

npm start partitioneddml example-db

Python

python partitioned_dml.py example-db

C#

dotnet run datpartitioneddmlboost example-db

Limpieza

Para evitar que se apliquen cargos adicionales a tu cuenta de Google Cloud por los recursos que se usaron en este instructivo, descarta la base de datos y borra la instancia que creaste.

Borra la base de datos

Si borras una instancia, se borrarán de forma automática todas las bases de datos que contiene. En este paso, se muestra cómo borrar una base de datos sin borrar una instancia (ten en cuenta que se seguirán generando cargos por la instancia).

En la línea de comandos

gcloud spanner databases delete example-db --instance=test-instance

Usa la consola de Google Cloud

1. Ve a la página Instancias de Spanner en la consola de Google Cloud.

   Ir a la página Instancias

2. Haz clic en la instancia.

3. Haz clic en la base de datos que deseas borrar.

4. En la página Detalles de la base de datos, haz clic en Borrar.

5. Confirma que deseas borrar la base de datos y haz clic en Borrar.

Borra la instancia

Si borras una instancia, se descartarán de forma automática todas las bases de datos creadas en ella.

En la línea de comandos

gcloud spanner instances delete test-instance

Usa la consola de Google Cloud

1. Ve a la página Instancias de Spanner en la consola de Google Cloud.

   Ir a la página Instancias

2. Haz clic en tu instancia.

3. Haz clic en Borrar.

4. Confirma que deseas borrar la instancia y haz clic en Borrar.

¿Qué sigue?

• Obtén información para acceder a Spanner con una instancia de máquina virtual.

• Obtén más información sobre las credenciales de autorización y autenticación en Autentícate en servicios de Cloud con bibliotecas cliente.

• Obtén más información sobre las prácticas recomendadas para el diseño de esquemas de Spanner.