Spanner 和 PGAdapter 使用入门

---

目标

本教程将介绍如何使用 Spanner 完成以下步骤： 适用于 PostgreSQL 驱动程序的 PGAdapter 本地代理：

• 创建 Spanner 实例和数据库。
• 写入、读取数据库中的数据和对数据执行 SQL 查询。
• 更新数据库架构。
• 使用读写事务更新数据。
• 向数据库添加二级索引。
• 使用索引来读取数据和对数据执行 SQL 查询。
• 使用只读事务检索数据。

费用

本教程使用 Spanner，它是 Google Cloud如需了解 Spanner 的使用费用，请参阅 定价。

准备工作

完成设置中介绍的步骤，包括创建和设置默认 Google Cloud 项目、启用结算功能、启用 Cloud Spanner API 以及设置 OAuth 2.0 来获取身份验证凭据以使用 Cloud Spanner API。

尤其要确保运行 gcloud auth application-default login，以便使用身份验证凭据设置本地开发环境。

注意：如果您不打算保留在本教程中创建的资源，请考虑创建新的 Google Cloud 项目，而不是选择现有项目。完成本教程后，您可以删除项目，以移除所有 与项目关联的资源

准备本地 PGAdapter 环境

您可以将 PostgreSQL 驱动程序与 PGAdapter 结合使用 才能连接到 Spanner。PGAdapter 是一个 会将 PostgreSQL 网络协议转换为 Spanner gRPC 协议。

提示： 请参阅延迟时间比较 比较 PGAdapter 和常规 Spanner 客户端库。

PGAdapter 需要 Java 或 Docker 才能运行。

1. 如果尚未安装以下任何一项，请在开发机器上安装其中之一：

   • Java 8 JDK（下载）。
   • Docker（下载）。

2. 将示例应用代码库克隆到本地机器：

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

3. 切换到包含 Spanner 示例代码的目录：

   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
   

创建实例

提示： 如果您将 PGAdapter 与 模拟器。PGAdapter 会自动 模拟器。

首次使用 Spanner 时，您必须创建一个实例， 分配 Spanner 数据库使用的资源。创建实例时，请选择一个实例配置（决定数据的存储位置），同时选择要使用的节点数（决定实例中服务资源和存储资源的数量）。

执行以下命令，在该区域中创建 Spanner 实例 us-central1，具有 1 个节点：

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

请注意，此命令将创建一个具有以下特征的实例：

• 实例 ID 为 test-instance
• 显示名为 Test Instance
• 实例配置为 regional-us-central1（单区域配置将数据存储在单个区域中，而多区域配置则将数据分布在多个区域中。如需了解详情，请参阅实例简介。）
• 节点数为 1（node_count 对应于实例中数据库可用的服务资源和存储资源的数量。有关详情，请参阅节点和 处理单元）。

您应该会看到：

Creating instance...done.

浏览示例文件

示例代码库包含一个示例，展示了如何使用 Spanner 与 PGAdapter 结合使用。

请浏览 samples/snippets 文件夹，其中说明了如何使用 Spanner。代码展示了如何创建和使用新数据库。数据 使用 架构和数据模型页面。

启动 PGAdapter

在本地开发机器上启动 PGAdapter，并将其指向 实例

以下命令假定您已执行 gcloud auth application-default login。

Java 应用

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

注意： 如果打开，请将 $HOME/.config/gcloud/替换为 %APPDATA%\gcloud Windows 或运行 gcloud info --format='value(config.paths.global_config_dir)' 找到您当前的 gcloud 配置文件夹。

敬上

模拟器

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

这将使用嵌入式 Spanner 启动 PGAdapter 模拟器。此嵌入式模拟器会自动创建任何 Spanner 而无需手动创建 。

我们建议您在生产环境中运行 PGAdapter，并将其作为 Sidecar 或作为进程内依赖项使用如需详细了解如何部署 PGAdapter 在生产环境中的情况，请参阅 选择运行 PGAdapter 的方法。

创建数据库

通过以下方法在名为 test-instance 的实例中创建名为 example-db 的数据库： 请在命令行中运行以下命令。

提示： 如果您将 PGAdapter 与 模拟器。PGAdapter 会自动 模拟器。

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

您应该会看到：

Creating database...done.

创建表

以下代码会在数据库中创建两个表。

注意 ：后续代码示例使用这两个表。如果您没有执行 此代码，然后使用 Google Cloud 控制台或 gcloud CLI。如需了解详情，请参阅示例架构。

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}]");
    }
}

使用以下命令运行该示例：

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

下一步是将数据写入数据库。

创建连接

您必须先创建与以下服务的连接，然后才能执行读写操作 PGAdapter 结合使用。您与 Spanner 的所有交互都必须 通过 Connection 实现。数据库名称在连接字符串中指定。

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}");
        }
    }
}

使用以下命令运行该示例：

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

使用 DML 写入数据

您可以在读写事务中使用数据操纵语言 (DML) 插入数据。

这些示例展示了如何在 Spanner 上执行 DML 语句 使用 PostgreSQL 驱动程序。

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.");
    }
}

使用以下命令运行该示例：

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

您应该会看到以下响应：

 4 records inserted.

注意 ：提交大小存在限制。请参阅 CRUD 限制 了解详情。

使用 DML 批次写入数据

PGAdapter 支持执行 DML 批次。发送多个 DML 语句减少 并提升应用的性能。

提示 ：您还可以使用 START BATCH DML 命令。

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.");
    }
}

使用以下命令运行该示例：

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

您应该会看到：

3 records inserted.

使用变更写入数据

您还可以使用变更插入数据。

PGAdapter 会将 PostgreSQL COPY 命令转换为 变更。使用 COPY 是在 Spanner 数据库的数据。

COPY 操作默认为原子操作。原子操作 Spanner 受到提交大小限制。 如需了解详情，请参阅 CRUD 限制。

以下示例展示了如何执行非原子 COPY 操作。这样， COPY 操作以超出提交大小限制。

提示： 请参阅 COPY 支持 如需详细了解如何将数据从 PostgreSQL 直接复制到 Spanner。您还可以直接从 MySQL 导入数据 使用 COPY 命令。

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");
    }
}

使用以下命令运行该示例：

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

您应该会看到：

Copied 5 singers
Copied 5 albums

注意 ：提交大小存在限制。请参阅 CRUD 限制 了解详情。

使用 SQL 查询数据

Spanner 支持使用 SQL 接口读取数据， 使用 Google Cloud CLI 或 以编程方式使用 PostgreSQL 驱动程序。

在命令行中

执行以下 SQL 语句，读取 Albums 表中所有列的值：

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

注意 ：有关 GoogleSQL 参考，请参阅 GoogleSQL 中的查询语法 如需查看 PostgreSQL 参考信息，请参阅 PostgreSQL 词汇结构和语法。

结果应为：

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

使用 PostgreSQL 驱动程序

除了在命令行上执行 SQL 语句外，还可以发出 使用 PostgreSQL 驱动程序以编程方式创建相同的 SQL 语句。

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)}");
        }
    }
}

使用以下命令运行该示例：

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

您应该会看到以下结果：

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

使用 SQL 参数进行查询

如果您的应用具有频繁执行的查询，您可以提高其性能 对其进行参数化处理。生成的参数查询可以缓存和重复使用 降低编译开销。如需了解详情，请参阅 使用查询参数加快频繁执行的查询的速度。

以下示例展示了如何在 WHERE 子句中使用形参 包含特定 LastName 值的查询记录。

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"]}");
        }
    }
}

使用以下命令运行该示例：

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

您应该会看到以下结果：

12 Melissa Garcia

更新数据库架构

假设您需要将名为 MarketingBudget 的新列添加到 Albums 表。向现有表添加新列需要更新数据库架构。Spanner 支持对数据库进行架构更新，同时 以便继续处理流量架构更新不需要 数据库离线，且不会锁定整个表或列；您可以继续 在架构更新期间将数据写入数据库。详细了解“支持” 架构更新和架构更改性能， 进行架构更新。

添加列

您可以使用 Google Cloud CLI 或 以编程方式使用 PostgreSQL 驱动程序。

在命令行中

使用以下 ALTER TABLE 命令向表添加新列：

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

您应该会看到：

Schema updating...done.

使用 PostgreSQL 驱动程序

使用 PostgreSQL 驱动程序执行 DDL 语句，以修改 架构：

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");
    }
}

使用以下命令运行该示例：

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

您应该会看到：

Added marketing_budget column

执行 DDL 批次

建议一次性执行多个架构修改。 您可以使用内置的 批量处理功能，具体方法是提交所有 DDL， 语句表示为一个以英文分号分隔的 SQL 字符串，或者使用 START BATCH DDL 和 RUN BATCH 语句。

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");
    }
}

使用以下命令运行该示例：

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

您应该会看到：

Added venues and concerts tables

将数据写入新列

以下代码可将数据写入新列。对于 Albums(1, 1) 键控的行，该代码会将 MarketingBudget 设置为 100000；而对于 Albums(2, 2) 键控的行，该代码会将其设置为 500000。

PGAdapter 会将 PostgreSQL COPY 命令转换为 变更。COPY 命令默认转换为 Insert 变更。 执行 set spanner.copy_upsert=true 以将 COPY 命令转换为 InsertOrUpdate 项变更。这可用于更新现有数据 Spanner。

提示： 如需查看可用于访问 Spanner 功能与 PGAdapter 结合使用，请参阅 PGAdapter 会话管理命令。

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");
    }
}

使用以下命令运行该示例：

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

您应该会看到：

Updated 2 albums

您也可以执行 SQL 查询来获取刚刚写入的值。

以下是执行查询的代码：

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"]}");
        }
    }
}

使用以下命令运行查询：

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

您应该会看到：

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

更新数据

您可以在读写事务中使用 DML 来更新数据。

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");
    }
}

使用以下命令运行该示例：

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

您应该会看到：

Transferred marketing budget from Album 2 to Album 1

交易代码和请求代码

使用事务代码和请求代码 来排查 Spanner 中的事务和查询问题。您可以设置 交易代码以及请求代码与 SPANNER.TRANSACTION_TAG 和 SPANNER.STATEMENT_TAG 会话变量。

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");
    }
}

使用以下命令运行该示例：

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

提示： 如需查看可用于访问 Spanner 功能与 PGAdapter 结合使用，请参阅 PGAdapter 会话管理命令。

使用只读事务检索数据

假设您要在同一时间戳执行多个读取操作。只读事务会遵从一致的事务提交历史记录前缀，因此您的应用始终可获得一致的数据。 将连接设置为只读或使用 SET TRANSACTION READ ONLY SQL 语句来执行只读事务。

提示 ：PGAdapter 支持多个额外的 SQL 语句， 执行特定类型的事务和批次，以及访问 Spanner 特性。如需查看受支持语句的完整列表，请参阅 PGAdapter 会话管理命令

下面演示了如何运行查询并在同一只读事务中执行读取操作：

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();
    }
}

使用以下命令运行该示例：

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

您看到的输出结果应该类似于以下内容：

    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

分区查询和 Data Boost

partitionQuery API 将查询划分为较小的部分或分区，并使用多个 并行提取分区。每个分区都由 分区标记。PartitionQuery API 的延迟时间比标准 Query API，因为它仅适用于批量操作，例如导出或 扫描整个数据库。

数据提升 执行分析查询和数据导出，费用接近于零 对已预配 Spanner 实例上现有工作负载的影响。 Data Boost 仅支持分区查询。

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"]}");
        }
    }
}

使用以下命令运行该示例：

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

如需详细了解如何运行分区查询以及如何搭配使用 Data Boost 和 PGAdapter，请参阅： Data Boost 和分区查询语句

分区 DML

分区数据操纵语言 (DML) 是 适用于以下类型的批量更新和删除操作：

• 定期清理和垃圾回收。
• 使用默认值回填新列。

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");
    }
}

使用以下命令运行该示例：

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

清理

为避免因本教程中使用的资源导致您的 Google Cloud 账号产生额外费用，请删除数据库和您创建的实例。

删除数据库

如果您删除一个实例，则该实例中的所有数据库都会自动删除。 本步骤演示了如何在不删除实例的情况下删除数据库（您仍需为该实例付费）。

在命令行中

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

使用 Google Cloud 控制台

1. 前往 Google Cloud 控制台中的 Spanner 实例页面。

   转到“实例”页面

2. 点击实例。

3. 点击您想删除的数据库。

4. 在数据库详细信息页面中，点击删除。

5. 确认您要删除数据库并点击删除。

删除实例

删除实例会自动删除在该实例中创建的所有数据库。

在命令行中

gcloud spanner instances delete test-instance

使用 Google Cloud 控制台

1. 前往 Google Cloud 控制台中的 Spanner 实例页面。

   转到“实例”页面

2. 点击您的实例。

3. 点击删除。

4. 确认您要删除实例并点击删除。

后续步骤

• 了解如何通过虚拟机实例访问 Spanner。

• 要了解授权和身份验证凭据，请参阅进行身份验证 使用客户端库的 Cloud 服务。

• 详细了解 Spanner 架构设计最佳实践。