分库分表与自定义分表规则

总体介绍

  • Oinone的分库分表方案是基于Sharding-JDBC的整合方案,要先具备一些Sharding-JDBC的知识。[Sharding-JDBC]https://shardingsphere.apache.org/document/current/cn/overview/

  • 做分库分表前,大家要有一个明确注意的点就是分表字段(也叫均衡字段)的选择,它是非常重要的,与业务场景非常相关。在明确了分库分表字段以后,甚至在功能上都要做一些妥协。比如分库分表字段在查询管理中做为查询条件是必须带上的,不然效率只会更低。

  • 分表字段不允许更新,所以代码里更新策略设置类永不更新,并在设置了在页面修改的时候为readonly

配置分表策略

  1. 配置ShardingModel模型走分库分表的数据源pamirsSharding
  2. 为pamirsSharding配置数据源以及sharding规则
    a. pamirs.sharding.define用于oinone的数据库表创建用
    b. pamirs.sharding.rule用于分表规则配置
  3. 为pamirsSharding配置数据源以及sharding规则

    1)指定模型对应数据源

pamirs:
  framework:
    system:
      system-ds-key: base
      system-models:
        - base.WorkerNode
    data:
      default-ds-key: pamirs
      ds-map:
        base: base
      modelDsMap:
        "[demo.ShardingModel]": pamirsSharding  #配置模型对应的库

2)分库分表规则配置

pamirs: 
  sharding:
    define:
      data-sources:
        ds: pamirs
        pamirsSharding: pamirs #申明pamirsSharding库对应的pamirs数据源
      models:
        "[trigger.PamirsSchedule]":
          tables: 0..13
        "[demo.ShardingModel]":
          tables: 0..7
          table-separator: _
    rule:
      pamirsSharding: #配置pamirsSharding库的分库分表规则
        actual-ds:
          - pamirs  #申明pamirsSharding库对应的pamirs数据源
        sharding-rules:
          # Configure sharding rule ,以下配置跟sharding-jdbc配置一致
          - tables:
              demo_core_sharding_model: #demo_core_sharding_model表规则配置
                actualDataNodes: pamirs.demo_core_sharding_model_${0..7}
                tableStrategy:
                  standard:
                    shardingColumn: user_id
                    shardingAlgorithmName: table_inline
            shardingAlgorithms:
              table_inline:
                type: INLINE
                props:
                  algorithm-expression: demo_core_sharding_model_${(Long.valueOf(user_id) % 8)}
        props:
          sql.show: true

自定义规则

  • 默认规则即通用的分库分表策略,如按照数据量、哈希等方式进行分库分表;通常默认规则是可以的。
  • 但在一些复杂的业务场景下,使用默认规则可能无法满足需求,需要根据实际情况进行自定义。例如,某些业务可能有特定的数据分布模式或者查询特点,需要定制化的分库分表规则来优化数据访问性能或者满足业务需求。在这种情况下,使用自定义规则可以更好地适应业务的需求。

自定义分表规则示例

示例1:按月份分表(DATE_MONTH )

package pro.shushi.pamirs.demo.core.sharding;

import cn.hutool.core.date.DateUtil;
import com.google.common.collect.Range;
import org.apache.shardingsphere.sharding.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.RangeShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.StandardShardingAlgorithm;
import org.springframework.stereotype.Component;
import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j;

import java.util.*;

/**
 * @author wangxian
 * @version 1.0
 * @description
 */
@Component
@Slf4j
public class DateMonthShardingAlgorithm implements StandardShardingAlgorithm<Date> {

    private Properties props;

    @Override
    public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<Date> preciseShardingValue) {
        Date date = preciseShardingValue.getValue();
        String suffix = "_" + (DateUtil.month(date) + 1);
        for (String tableName : availableTargetNames) {
            if (tableName.endsWith(suffix)) {
                return tableName;
            }
        }
        throw new IllegalArgumentException("未找到匹配的数据表");
    }

    @Override
    public Collection<String> doSharding(Collection<String> availableTargetNames, RangeShardingValue<Date> rangeShardingValue) {
        List<String> list = new ArrayList<>();
        log.info(rangeShardingValue.toString());
        Range<Date> valueRange = rangeShardingValue.getValueRange();
        Date lowerDate = valueRange.lowerEndpoint();
        Date upperDate = valueRange.upperEndpoint();
        Integer begin = DateUtil.month(lowerDate) + 1;
        Integer end = DateUtil.month(upperDate) + 1;
        TreeSet<String> suffixList = ShardingUtils.getSuffixListForRange(begin, end);
        for (String tableName : availableTargetNames) {
            if (containTableName(suffixList, tableName)) {
                list.add(tableName);
            }
        }
        return list;
    }

    private boolean containTableName(Set<String> suffixList, String tableName) {
        boolean flag = false;
        for (String s : suffixList) {
            if (tableName.endsWith(s)) {
                flag = true;
                break;
            }
        }
        return flag;
    }

    @Override
    public void init() {

    }

    @Override
    public String getType() {
        return "DATE_MONTH";
    }

    @Override
    public Properties getProps() {
        return this.props;
    }

    @Override
    public void setProps(Properties properties) {
        this.props = props;
    }
}

示例2:按特定字段截取去取模分表

package pro.shushi.pamirs.demo.core.sharding;

import org.apache.shardingsphere.sharding.api.sharding.standard.PreciseShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.RangeShardingValue;
import org.apache.shardingsphere.sharding.api.sharding.standard.StandardShardingAlgorithm;
import org.springframework.stereotype.Component;
import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j;

import java.util.Collection;
import java.util.Properties;

/**
 * @author wangxian
 * @version 1.0
 * @description
 */
@Component
@Slf4j
public class AppUserCodeShardingAlgorithm implements StandardShardingAlgorithm<String> {

    private Properties props;

    @Override
    public String doSharding(Collection<String> availableTargetNames, PreciseShardingValue<String> preciseShardingValue) {
        String appUserCode = preciseShardingValue.getValue();
        String suffix = "_" + Long.parseLong(appUserCode.substring(1)) % 21;
        for (String tableName : availableTargetNames) {
            if (tableName.endsWith(suffix)) {
                return tableName;
            }
        }
        throw new IllegalArgumentException("未找到匹配的数据表");
    }

    @Override
    public Collection<String> doSharding(final Collection<String> availableTargetNames, final RangeShardingValue<String> shardingValue) {
        return availableTargetNames;
    }

    @Override
    public String getType() {
        return "APP_USER_CODE_TYPE";
    }

    @Override
    public Properties getProps() {
        return this.props;
    }

    @Override
    public void setProps(Properties properties) {
        this.props = props;
    }

    @Override
    public void init() {

    }
}

使用自定义分表策略

1)指定模型对应数据源

pamirs:
  framework:
    system:
      system-ds-key: base
      system-models:
        - base.WorkerNode
    data:
      default-ds-key: pamirs_biz
      ds-map:
        base: base
        demo_core: pamirs
      modelDsMap:
        "[demo.record.MsgRecode]": pamirsSharding

2)分库分表规则配置

pamirs:
  sharding:
    define:
      data-sources:
        ds: pamirs
        pamirsSharding: pamirs
      models:
        "[trigger.PamirsSchedule]":
          tables: 0..13
        "[demo.record.MsgRecode]":
          tables: 0..20
          table-separator: _
    rule:
      pamirsSharding:
        actual-ds:
          - pamirs
        sharding-rules:
          - tables:
              demo_core_record_msg_recode:
                actualDataNodes: pamirs.demo_core_record_msg_recode_${0..20}
                tableStrategy:
                  standard:
                    shardingColumn: app_user_code
                    shardingAlgorithmName: app_user_code_table_algorithm
            shardingAlgorithms:
              app_user_code_table_algorithm:
                type: APP_USER_CODE_TYPE
                props:
                  strategy: STANDARD
                  algorithmClassName:
                    pro.shushi.pamirs.demo.core.sharding.AppUserCodeShardingAlgorithm

配置自定义规则SPI

分库分表规则SPI

在resources/META-INF/services 配置 org.apache.shardingsphere.sharding.spi.ShardingAlgorithm

pro.shushi.pamirs.demo.core.sharding.AppUserCodeShardingAlgorithm
pro.shushi.pamirs.demo.core.sharding.DateMonthShardingAlgorithm

Oinone社区 作者:望闲原创文章,如若转载,请注明出处:https://doc.oinone.top/backend/7155.html

访问Oinone官网:https://www.oinone.top获取数式Oinone低代码应用平台体验

(0)
望闲的头像望闲数式管理员
上一篇 2024年5月9日 pm3:56
下一篇 2024年5月13日 pm7:06

相关推荐

  • 函数之触发与定时配置和示例

    异步任务总体介绍 函数的触发和定时在很多场景中会用到,也是一个oinone的基础能力。比如我们的流程产品中在定义流程触发时就会让用户选择模型触发还是时间触发,就是用到了函数的触发与定时能力。 触发任务TriggerTaskAction 触发任务的创建,使用sql-record模块监听mysql的binlog事件,通过rocketmq发送变更数据消息,收到MQ消息后,创建TriggerAutoTask。 触发任务的执行,使用TBSchedule拉取触发任务后,执行相应函数。 项目中引入依赖 1、项目的API工程引入依赖pamirs-core-trigger模块 <dependency> <groupId>pro.shushi.pamirs.core</groupId> <artifactId>pamirs-trigger-api</artifactId> </dependency> 2、DemoModule在模块依赖定义中增加@Module(dependencies={TriggerModule.MODULE_MODULE}) @Component @Module( name = DemoModule.MODULE_NAME, displayName = "oinoneDemo工程", version = "1.0.0", dependencies = {ModuleConstants.MODULE_BASE, CommonModule.MODULE_MODULE, UserModule.MODULE_MODULE, TriggerModule.MODULE_MODULE} ) @Module.module(DemoModule.MODULE_MODULE) @Module.Advanced(selfBuilt = true, application = true) @UxHomepage(PetShopProxy.MODEL_MODEL) public class DemoModule implements PamirsModule { ……其他代码 } 3、项目的boot工程引入依赖 <dependency> <groupId>pro.shushi.pamirs.core</groupId> <artifactId>pamirs-trigger-core</artifactId> </dependency> <dependency> <groupId>pro.shushi.pamirs.core</groupId> <artifactId>pamirs-trigger-bridge-tbschedule</artifactId> </dependency> <dependency> <groupId>pro.shushi.pamirs.core</groupId> <artifactId>pamirs-sql-record-core</artifactId> </dependency> yml文件修改(applcation-xxx.yml) a. 修改pamris.event.enabled和pamris.event.schedule.enabled为trueb. pamirs_boot_modules增加启动模块:trigger、sql_record pamirs: record: sql: #改成自己路径 store: /opt/pamirs/logs … event: enabled: true schedule: enabled: true rocket-mq: namesrv-addr: 127.0.0.1:9876 boot: init: true sync: true modules: – base -…… – trigger – sql_record -…… 新建触发任务 新建PetTalentTrigger类,当PetTalent模型的数据记录被新建时触发系统做一些事情 package pro.shushi.pamirs.demo.core.trigger; import pro.shushi.pamirs.demo.api.model.PetTalent; import pro.shushi.pamirs.meta.annotation.Fun; import pro.shushi.pamirs.meta.annotation.Function; import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j; import pro.shushi.pamirs.trigger.annotation.Trigger; import pro.shushi.pamirs.trigger.enmu.TriggerConditionEnum; @Fun(PetTalent.MODEL_MODEL) @Slf4j public class PetTalentTrigger { @Function @Trigger(displayName = “PetTalent创建时触发”,name = “PetTalent#Trigger#onCreate”,condition = TriggerConditionEnum.ON_CREATE) public PetTalent onCreate(PetTalent data){ log.info(data.getName() + “,被创建”); //可以增加逻辑 return data; } } 定时任务 定时任务是一种非常常见的模式,这里就不介绍概念了,直接进入示例环节 新建PetTalentAutoTask实现ScheduleAction getInterfaceName()需要跟taskAction.setExecuteNamespace定义保持一致,都是函数的命名空间 taskAction.setExecuteFun("execute");跟执行函数名“execute”一致 TaskType需配置为CYCLE_SCHEDULE_NO_TRANSACTION_TASK,把定时任务的schedule线程分开,要不然有一个时间长的任务会导致普通异步或触发任务全部延时。 package pro.shushi.pamirs.demo.core.task; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.stereotype.Component; import pro.shushi.pamirs.core.common.enmu.TimeUnitEnum; import pro.shushi.pamirs.demo.api.model.PetTalent; import pro.shushi.pamirs.meta.annotation.Fun; import pro.shushi.pamirs.meta.annotation.Function; import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j; import pro.shushi.pamirs.meta.domain.fun.FunctionDefinition; import pro.shushi.pamirs.middleware.schedule.api.ScheduleAction; import pro.shushi.pamirs.middleware.schedule.common.Result; import pro.shushi.pamirs.middleware.schedule.domain.ScheduleItem; import pro.shushi.pamirs.middleware.schedule.eunmeration.TaskType; import pro.shushi.pamirs.trigger.enmu.TriggerTimeAnchorEnum; import pro.shushi.pamirs.trigger.model.ScheduleTaskAction; import pro.shushi.pamirs.trigger.service.ScheduleTaskActionService; @Slf4j @Component @Fun(PetTalent.MODEL_MODEL) public class PetTalentAutoTask implements…

    2024年5月25日
    1.5K00
  • 自定义数据权限拦截处理

    业务场景 公司给员工对哪些模块有访问权限,这个时候就需要在员工访问模块表的时候做数据过滤, 解决方案 我们可以通过平台提供的数据过滤占位符解决这个问题,新建一条数据行权限,过滤语句条件是占位符,再编写占位符的解析逻辑 1.初始化权限基础数据 package pro.shushi.pamirs.demo.core.init; import com.google.common.collect.Lists; import org.springframework.core.annotation.Order; import org.springframework.stereotype.Component; import pro.shushi.pamirs.auth.api.constants.AuthConstants; import pro.shushi.pamirs.auth.api.enmu.AuthGroupTypeEnum; import pro.shushi.pamirs.auth.api.enmu.PermissionDataSourceEnum; import pro.shushi.pamirs.auth.api.enmu.PermissionTypeEnum; import pro.shushi.pamirs.auth.api.model.AuthGroup; import pro.shushi.pamirs.auth.api.model.AuthRole; import pro.shushi.pamirs.auth.api.model.ResourcePermission; import pro.shushi.pamirs.boot.base.model.UeModule; import pro.shushi.pamirs.boot.common.api.command.AppLifecycleCommand; import pro.shushi.pamirs.boot.common.api.init.InstallDataInit; import pro.shushi.pamirs.boot.common.api.init.UpgradeDataInit; import pro.shushi.pamirs.demo.api.DemoModule; import pro.shushi.pamirs.demo.core.placeholder.EmployeeModulePlaceholder; import pro.shushi.pamirs.framework.common.utils.ObjectUtils; import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j; import pro.shushi.pamirs.meta.domain.module.ModuleDefinition; import java.util.Collections; import java.util.List; @Slf4j @Component @Order(0) public class DemoModuleBizInit implements InstallDataInit, UpgradeDataInit { @Override public List<String> modules() { return Collections.singletonList(DemoModule.MODULE_MODULE); } @Override public int priority() { return 0; } @Override public boolean init(AppLifecycleCommand command, String version) { this.initAuth(); return true; } @Override public boolean upgrade(AppLifecycleCommand command, String version, String existVersion) { this.initAuth(); return true; } private void initAuth() { AuthGroup authGroup = new AuthGroup(); authGroup.setName("测试权限组") .setDisplayName("测试权限组") .setType(AuthGroupTypeEnum.RUNTIME) .setActive(true); authGroup.createOrUpdate(); AuthRole authRole = new AuthRole(); authRole.setCode("TEST_ROLE_1") .setName("测试角色") .setRoleTypeCode(AuthConstants.ROLE_SYSTEM_TYPE_CODE) .setPermissionDataSource(PermissionDataSourceEnum.CUSTOM) .setActive(true); authRole.createOrUpdate(); authRole.setGroups(Lists.newArrayList(authGroup)); authRole.fieldSave(AuthRole::getGroups); ResourcePermission authPermission = new ResourcePermission(); authPermission.setName("测试模块权限过滤") .setDomainExp(EmployeeModulePlaceholder.PLACEHOLDER) .setModel(ModuleDefinition.MODEL_MODEL) .setPermRead(true) .setPermRun(true) .setPermissionType(PermissionTypeEnum.ROW) .setPermissionDataSource(PermissionDataSourceEnum.CUSTOM) .setCanShow(true) .setActive(true); ResourcePermission authPermission2 = ObjectUtils.clone(authPermission); authPermission2.setName("测试ue模块权限过滤").setModel(UeModule.MODEL_MODEL); authGroup.setPermissions(Lists.newArrayList(authPermission, authPermission2)); authGroup.fieldSave(AuthGroup::getPermissions); } } 这里演示的module表比较特殊,需要同时设置ModuleDefinition和UeModule这2个模型做数据过滤 2.编写占位符拦截替换逻辑 package pro.shushi.pamirs.demo.core.placeholder; import org.springframework.stereotype.Component; import pro.shushi.pamirs.user.api.AbstractPlaceHolderParser; @Component public class EmployeeModulePlaceholder extends AbstractPlaceHolderParser { public static final String PLACEHOLDER = "${employeeModulePlaceholder}"; protected String value() { // TODO…

    2023年11月24日
    1.1K00
  • Oinone请求路由源码分析

    通过源码分析,从页面发起请求,如果通过graphQL传输到具体action的链路,并且在这之间做了哪些隐式处理分析源码版本5.1.x 请求流程大致如下: 拦截所有指定的请求 组装成graphQL请求信息 调用graphQL执行 通过hook拦截先执行 RsqlDecodeHook:rsql解密 UserHook: 获取用户信息, 通过cookies获取用户ID,再查表获取用户信息,放到本地Local线程里 RoleHook: 角色Hook FunctionPermissionHook: 函数权限Hook ,跳过权限拦截的实现放在这一层,对应的配置 pamirs: auth: fun-filter: – namespace: user.PamirsUserTransient fun: login #登录 – namespace: top.PetShop fun: action DataPermissionHook: 数据权限hook PlaceHolderHook:占位符转化替换hook RsqlParseHook: 解释Rsql hook SingletonModelUpdateHookBefore 执行post具体内容 通过hook拦截后执行 QueryPageHook4TreeAfter: 树形Parent查询优化 FieldPermissionHook: 字段权限Hook UserQueryPageHookAfter UserQueryOneHookAfter 封装执行结果信息返回 时序图 核心源码解析 拦截所有指定的请求 /pamirs/模块名RequestController @RequestMapping( value = "/pamirs/{moduleName:^[a-zA-Z][a-zA-Z0-9_]+[a-zA-Z0-9]$}", method = RequestMethod.POST ) public String pamirsPost(@PathVariable("moduleName") String moduleName, @RequestBody PamirsClientRequestParam gql, HttpServletRequest request, HttpServletResponse response) { } DefaultRequestExecutor 构建graph请求信息,并调用graph请求 () -> execute(GraphQL::execute, param), param private <T> T execute(BiFunction<GraphQL, ExecutionInput, T> executor, PamirsRequestParam param) { // 获取GraphQL请求信息,包含grapsh schema GraphQL graphQL = buildGraphQL(param); … ExecutionInput executionInput = ExecutionInput.newExecutionInput() .query(param.getQuery()) .variables(param.getVariables().getVariables()) .dataLoaderRegistry(Spider.getDefaultExtension(DataLoaderRegistryApi.class).dataLoader()) .build(); … // 调用 GraphQL的方法execute 执行 T result = executor.apply(graphQL, executionInput); … return result; } QueryAndMutationBinder 绑定graphQL读取写入操作 public static DataFetcher<?> dataFetcher(Function function, ModelConfig modelConfig) { if (isAsync()) { if (FunctionTypeEnum.QUERY.in(function.getType())) { return AsyncDataFetcher.async(dataFetchingEnvironment -> dataFetcherAction(function, modelConfig, dataFetchingEnvironment), ExecutorServiceApi.getExecutorService()); } else { return dataFetchingEnvironment -> dataFetcherAction(function, modelConfig, dataFetchingEnvironment); } } else { return dataFetchingEnvironment -> dataFetcherAction(function, modelConfig, dataFetchingEnvironment); } } private static Object dataFetcherAction(Function function, ModelConfig modelConfig, DataFetchingEnvironment environment) { try { SessionExtendUtils.tagMainRequest(); // 使用共享的请求和响应对象 return Spider.getDefaultExtension(ActionBinderApi.class) .action(modelConfig,…

    2024年8月21日
    5.7K02
  • 模型字段之序列化方式

    本文核心是带大家全面了解oinone的序列方式,包括支持的序列化类型、注意点、如果新增客户化序列化方式以及字段默认值的反序列化。 字段序列化方式说明 序列化方式 说明 备注 JSON JSON序列化 主要用于模型相关类型字段的序列化,是@Field.serialize默认选项 DOT 点拼接集合元素 COMMA 逗号拼接集合元素 BIT 按位与,2次幂数求和 非@Field.serialize可选项列表,用于二进制枚举序列化不需要配置,由oinone自动推断 字段序列化方式举例 1、给模型PetItemDetail 增加两个字段:petItemDetails类型为List 和 tags类型为List,并设置为不同的序列化方式,petItemDetails为JSON(缺省就是JSON,可不配),tags为COMMA。2、同时设置 @Field.Advanced(columnDefinition = "varchar(1024)"),防止序列化后存储过长。 @Model.model(PetItem.MODEL_MODEL) @Model(displayName = "宠物商品",summary="宠物商品",labelFields = {"itemName"}) public class PetItem extends AbstractDemoCodeModel{ public static final String MODEL_MODEL="demo.PetItem"; @Field(displayName = "品种") @Field.many2one @Field.Relation(relationFields = {"typeId"},referenceFields = {"id"}) private PetType type; @Field(displayName = "品种类型",invisible = true) private Long typeId; @Field(displayName = "详情", serialize = Field.serialize.JSON, store = NullableBoolEnum.TRUE) @Field.Advanced(columnDefinition = "varchar(1024)") private List<PetItemDetail> petItemDetails; @Field(displayName = "商品标签",serialize = Field.serialize.COMMA,store = NullableBoolEnum.TRUE,multi = true) @Field.Advanced(columnDefinition = "varchar(1024)") private List<String> tags; } 字段序列化注意点 必须使用Field#store属性将字段存储设置为NullableBoolEnum.TRUE。 使用Field#serialize属性指定序列化方式,默认为JSON。 如把PetItemDetail设置为存储模型,须在PetItem的petItemDetails字段上使用Field.Relation#store属性将关联关系存储设置为false。不然会同时存储petItemDetails字段和对应的PetItemDetail表记录 注册自己的序列化器 注册自己的序列化器(实现pro.shushi.pamirs.meta.api.core.orm.serialize.Serializer接口), 如oinone的DOT的序列化方式,用type()方法返回值做匹配,serialize和deserialize分别对应序列化和反序列化方法。 package pro.shushi.pamirs.framework.compute.serialize; import org.apache.commons.lang3.StringUtils; import org.springframework.stereotype.Component; import pro.shushi.pamirs.meta.annotation.fun.extern.Slf4j; import pro.shushi.pamirs.meta.api.core.orm.serialize.Serializer; import pro.shushi.pamirs.meta.common.constants.CharacterConstants; import pro.shushi.pamirs.meta.enmu.SerializeEnum; import pro.shushi.pamirs.meta.util.TypeUtils; import java.util.ArrayList; import java.util.Collections; import java.util.List; /** * 点表达式序列生成处理器实现 * @author shushi@shushi.pro * @version 1.0.0 */ @SuppressWarnings("rawtypes") @Slf4j @Component public class DotSerializeProcessor implements Serializer<Object, String> { @Override public String serialize(String ltype, Object value) { if (null == value) { return null; } if (List.class.isAssignableFrom(value.getClass())) { return StringUtils.join((List) value, CharacterConstants.SEPARATOR_DOT); } else { return StringUtils.join(Collections.singletonList(value), CharacterConstants.SEPARATOR_DOT); } } @SuppressWarnings("unchecked") @Override public Object deserialize(String ltype, String ltypeT, String value,…

    2024年5月24日
    1.8K00
  • 【HighGo】后端部署使用HighGo数据库

    HighGo数据库配置 驱动配置 jdbc仓库 https://mvnrepository.com/artifact/com.highgo/HgdbJdbc Maven配置(6.0.1版本可用) <highgo.version>6.0.1.jre8</highgo.version> <dependency> <groupId>com.highgo</groupId> <artifactId>HgdbJdbc</artifactId> <version>${highgo.version}</version> </dependency> JDBC连接配置 pamirs: datasource: base: type: com.alibaba.druid.pool.DruidDataSource driverClassName: com.highgo.jdbc.Driver url: jdbc:highgo://127.0.0.1:5866/oio_base?currentSchema=base,utl_file username: xxxxxx password: xxxxxx initialSize: 5 maxActive: 200 minIdle: 5 maxWait: 60000 timeBetweenEvictionRunsMillis: 60000 testWhileIdle: true testOnBorrow: false testOnReturn: false poolPreparedStatements: true asyncInit: true 连接url配置 官方文档 https://www.highgo.com/document/zh-cn/application/jdbc.html url格式 jdbc:highgo://ip:端口号/数据库名?currentSchema=schema1,schema2 在jdbc连接配置时,${database}和${schema}必须完整配置,不可缺省。 jdbc指定schema时可以在currentSchema后指定多个schema,中间用,分隔,第一个schema为业务库表存放的主schema。 highgo数据库6.0版本里每个数据库默认会带一个utl_file的schema,该模式与文件访问功能有关,需要带在jdbc的schema中,但不能放在第一个。 其他连接参数如需配置,可自行查阅相关资料进行调优。 方言配置 pamirs方言配置 pamirs: dialect: ds: base: type: HighGoDB version: 6 major-version: 6.0.1 biz_data: type: HighGoDB version: 6 major-version: 6.0.1 数据库版本 type version majorVersion 6.0.x HighGo 6 6.0.1 PS:由于方言开发环境为6.0.1版本,其他类似版本(6.0.x)原则上不会出现太大差异,如出现其他版本无法正常支持的,可在文档下方留言。 schedule方言配置 pamirs: event: enabled: true schedule: enabled: true dialect: type: HighGoDB version: 6 major-version: 6.0.1 其他配置 逻辑删除的值配置 pamirs: mapper: global: table-info: logic-delete-value: (EXTRACT(epoch FROM CURRENT_TIMESTAMP) * 1000000 + EXTRACT(MICROSECONDS FROM CURRENT_TIMESTAMP))::bigint Highgo数据库用户初始化及授权 — init oio_base user (user name can be modified by oneself) CREATE USER oio_base WITH PASSWORD 'Test@12345678'; — if using automatic database and schema creation, this is very important. ALTER USER oio_base CREATEDB; SELECT * FROM pg_roles; — if using highgo database, this authorization is required. GRANT CREATE ON DATABASE highgo TO oio_base;

    2025年7月10日
    42900

Leave a Reply

登录后才能评论