sharding-jdbc sub-banco de dados horizontal subtabela combate real


  • Conceito de subtabela de sub-biblioteca de dados e cenários de aplicação Subtabela de
    sub-biblioteca detalhada trouxe alguns problemas
    sharding-jdbc ambiente de sub-tabela de sub-biblioteca horizontal e vertical para construir
    subtabela de sub-biblioteca de nível de sharding-jdbc real
    sharding-jdbc sub-biblioteca subtabela combate vertical

  • Subtabela de sub-banco de dados
    horizontal Objetivo 1. Subtabela horizontal, aliviar o problema de desempenho de uma grande quantidade de dados em uma única tabela
    2. Sub-banco de dados horizontal, aliviar o problema de desempenho de altas solicitações simultâneas para um único banco de dados

  • Realização da tabela de pontuação de nível

    实现方案:将一张表的数据,根据某种算法,分摊到多表中
    public class springJdbcTest {
          
          
        public static void main(String[] args) throws SQLException {
          
          
    
            //获取数据源
            DataSource dataSource = getDataSource();
    
            //获取jdbctemplate
            JdbcTemplate jdbcTemplate = getJdbcTemplate(dataSource);
    
    
            //执行语句
            for(int i=1;i<=10;i++) {
          
          
                jdbcTemplate.update("insert into t_user(user_name,user_age,user_type) values (?,?,?)",i,i,i);
            }
    
        }
    
    	//创建JdbcTemplate
        public static JdbcTemplate getJdbcTemplate( DataSource dataSource){
          
          
            JdbcTemplate jdbcTemplate = new JdbcTemplate();
            jdbcTemplate.setDataSource(dataSource);
            return jdbcTemplate;
        }
    
    	//创建数据源,这个数据源是sharding-jdbc级别的数据源
        public static DataSource getDataSource() throws SQLException {
          
          
            // 配置真实数据源
            Map<String, DataSource> dataSourceMap = new HashMap<>();
    
            // 配置第 1 个数据源
            DruidDataSource dataSource1 = new DruidDataSource();
            dataSource1.setDriverClassName("com.mysql.jdbc.Driver");
            dataSource1.setUrl("jdbc:mysql://localhost:3306/ds0?characterEncoding=utf-8&useSSL=false");
            dataSource1.setUsername("root");
            dataSource1.setPassword("123456");
            dataSourceMap.put("ds0", dataSource1);
    
            // 配置表规则bean
            ShardingRuleConfiguration shardingRuleConfiguration=new ShardingRuleConfiguration();
    
            //配置逻辑表和实际表分布情况,$是一个变量,取值范围是[1,2],表都在一个数据源ds0
            TableRuleConfiguration tableRuleConfiguration = new TableRuleConfiguration("t_user","ds0.t_user_$->{1..2}");
    
            //实际表生成主键策略,分表用数据库自增会重复,必须用第三方生成的id
            KeyGeneratorConfiguration keyGeneratorConfiguration = new KeyGeneratorConfiguration("snowflake","user_id");
    
            //配置选择表的路由配置,当user_id是偶数数据存t_user_1中
            //配置选择表的路由配置,当user_id是奇数数据存t_user_2中
            ShardingStrategyConfiguration shardingStrategyConfiguration = new InlineShardingStrategyConfiguration("user_id","t_user_$->{user_id%2+1}");
            //配置选择库的路由配置,因为是分表,所以库是固定的
            ShardingStrategyConfiguration shardingStrategyConfiguration1 = new InlineShardingStrategyConfiguration("user_id","ds0");
    
            shardingRuleConfiguration.setTableRuleConfigs(Arrays.asList(tableRuleConfiguration));
            shardingRuleConfiguration.setDefaultKeyGeneratorConfig(keyGeneratorConfiguration);
            shardingRuleConfiguration.setDefaultTableShardingStrategyConfig(shardingStrategyConfiguration);
            shardingRuleConfiguration.setDefaultDatabaseShardingStrategyConfig(shardingStrategyConfiguration1);
    
            return ShardingDataSourceFactory.createDataSource(dataSourceMap, shardingRuleConfiguration, new Properties());
        }
    }
    
  • Efeito da tabela de pontuação de nível
    Insira a descrição da imagem aqui
    Insira a descrição da imagem aqui

  • Realização de sub-biblioteca horizontal

    public class springJdbcTest {
          
          
        public static void main(String[] args) throws SQLException {
          
          
    
            //获取数据源
            DataSource dataSource = getDataSource();
    
            //获取jdbctemplate
            JdbcTemplate jdbcTemplate = getJdbcTemplate(dataSource);
    
    
            //执行语句
            for(int i=1;i<=10;i++) {
          
          
                jdbcTemplate.update("insert into t_user(user_name,user_age,user_type) values (?,?,?)",i,i,i);
            }
    
        }
    
    
        public static JdbcTemplate getJdbcTemplate( DataSource dataSource){
          
          
            JdbcTemplate jdbcTemplate = new JdbcTemplate();
            jdbcTemplate.setDataSource(dataSource);
            return jdbcTemplate;
        }
    
        public static DataSource getDataSource() throws SQLException {
          
          
            // 配置真实数据源
            Map<String, DataSource> dataSourceMap = new HashMap<>();
    
            // 配置第 1 个数据源
            DruidDataSource dataSource1 = new DruidDataSource();
            dataSource1.setDriverClassName("com.mysql.jdbc.Driver");
            dataSource1.setUrl("jdbc:mysql://localhost:3306/ds0");
            dataSource1.setUsername("root");
            dataSource1.setPassword("123456");
            dataSourceMap.put("ds0", dataSource1);
    
            // 配置第 2 个数据源
            DruidDataSource dataSource2 = new DruidDataSource();
            dataSource2.setDriverClassName("com.mysql.jdbc.Driver");
            dataSource2.setUrl("jdbc:mysql://localhost:3307/ds0");
            dataSource2.setUsername("root");
            dataSource2.setPassword("123456");
            dataSourceMap.put("ds1", dataSource2);
    
            // 配置表规则bean
            ShardingRuleConfiguration shardingRuleConfiguration=new ShardingRuleConfiguration();
    
            //配置逻辑表和实际表分布情况,两个t_user表分布在不同的数据库中
            TableRuleConfiguration tableRuleConfiguration = new TableRuleConfiguration("t_user","ds$->{0..1}.t_user");
    
            //实际表生成主键策略,分表用数据库自增会重复,必须用第三方生成的id
            KeyGeneratorConfiguration keyGeneratorConfiguration = new KeyGeneratorConfiguration("snowflake","user_id");
    
            //配置选择表的路由配置,这里我们分库了,表名称一样了
            ShardingStrategyConfiguration shardingStrategyConfiguration = new InlineShardingStrategyConfiguration("user_id","t_user");
    
    		//配置选择库的路由配置,当user_id是奇数,数据存在ds0数据库中
    		//配置选择库的路由配置,当user_id是偶数,数据存在ds1数据库中
            ShardingStrategyConfiguration shardingStrategyConfiguration1 = new InlineShardingStrategyConfiguration("user_id","ds$->{user_id%2}");
    
            shardingRuleConfiguration.setTableRuleConfigs(Arrays.asList(tableRuleConfiguration));
            shardingRuleConfiguration.setDefaultKeyGeneratorConfig(keyGeneratorConfiguration);
            shardingRuleConfiguration.setDefaultTableShardingStrategyConfig(shardingStrategyConfiguration);
            shardingRuleConfiguration.setDefaultDatabaseShardingStrategyConfig(shardingStrategyConfiguration1);
    
            return ShardingDataSourceFactory.createDataSource(dataSourceMap, shardingRuleConfiguration, new Properties());
        }
    }
    
    
  • Efeito de sub-biblioteca horizontal
    Insira a descrição da imagem aqui
    Insira a descrição da imagem aqui

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Origin blog.csdn.net/weixin_38312719/article/details/109138914
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