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feat(data-align): 实现用户关注、粉丝及笔记发布数的数据对齐功能

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- 新增 LUA 脚本实现布隆过滤器校验日增量数据
- 修改表结构将 t_data_align_note_publish_count_temp 的 note_id 替换为 user_id
-为 CreateTableXxlJob 添加事务管理确保表创建一致性
- 新增 FollowUnfollowMqDTO 和 NoteOperateMqDTO 用于消息传递
- 扩展 InsertRecordMapper 支持插入关注、粉丝和笔记发布计数记录
- 在 RedisKeyConstants 中新增多个布隆过滤器相关常量和构建方法
- 新增两个 RocketMQ 消费者处理用户关注/取关和笔记发布/删除事件
- 更新 HTTP 测试文件中的请求参数以适配最新接口逻辑
This commit is contained in:
Hanserwei
2025-10-23 20:02:36 +08:00
parent 5c4d8862a2
commit 17123657f4
13 changed files with 425 additions and 15 deletions
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10
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/constant/MQConstants.java
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@@ -12,4 +12,14 @@ public interface MQConstants {
*/
String TOPIC_COUNT_NOTE_COLLECT = "CountNoteCollectTopic";
/**
* Topic: 笔记操作（发布、删除）
*/
String TOPIC_NOTE_OPERATE = "NoteOperateTopic";
/**
* Topic: 关注数计数
*/
String TOPIC_COUNT_FOLLOWING = "CountFollowingTopic";
}

45
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/constant/RedisKeyConstants.java
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@@ -12,6 +12,21 @@ public class RedisKeyConstants {
*/
public static final String BLOOM_TODAY_NOTE_COLLECT_LIST_KEY = "bloom:dataAlign:note:collects:";
/**
* 布隆过滤器：日增量变更数据，用户笔记发布，删除 前缀
*/
public static final String BLOOM_TODAY_USER_NOTE_OPERATOR_LIST_KEY = "bloom:dataAlign:user:note:operators:";
/**
* 布隆过滤器：日增量变更数据，用户关注数 前缀
*/
public static final String BLOOM_TODAY_USER_FOLLOW_LIST_KEY = "bloom:dataAlign:user:follows:";
/**
* 布隆过滤器：日增量变更数据，用户粉丝数 前缀
*/
public static final String BLOOM_TODAY_USER_FANS_LIST_KEY = "bloom:dataAlign:user:fans:";
/**
* 构建完整的布隆过滤器：日增量变更数据，用户笔记点赞，取消点赞 KEY
@@ -33,4 +48,34 @@ public class RedisKeyConstants {
return BLOOM_TODAY_NOTE_COLLECT_LIST_KEY + date;
}
/**
* 构建完整的布隆过滤器：日增量变更数据，用户笔记发布，删除 KEY
*
* @param date 日期
* @return 完整的布隆过滤器：日增量变更数据，用户笔记发布，删除 KEY
*/
public static String buildBloomUserNoteOperateListKey(String date) {
return BLOOM_TODAY_USER_NOTE_OPERATOR_LIST_KEY + date;
}
/**
* 构建完整的布隆过滤器：日增量变更数据，用户关注数 KEY
*
* @param date 日期
* @return 完整的布隆过滤器：日增量变更数据，用户关注数 KEY
*/
public static String buildBloomUserFollowListKey(String date) {
return BLOOM_TODAY_USER_FOLLOW_LIST_KEY + date;
}
/**
* 构建完整的布隆过滤器：日增量变更数据，用户粉丝数 KEY
*
* @param date 日期
* @return 完整的布隆过滤器：日增量变更数据，用户粉丝数 KEY
*/
public static String buildBloomUserFansListKey(String date) {
return BLOOM_TODAY_USER_FANS_LIST_KEY + date;
}
}

91
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/consumer/TodayNotePublishIncrementData2DBConsumer.java Normal file
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@@ -0,0 +1,91 @@
package com.hanserwei.hannote.data.align.consumer;
import com.hanserwei.framework.common.utils.JsonUtils;
import com.hanserwei.hannote.data.align.constant.MQConstants;
import com.hanserwei.hannote.data.align.constant.RedisKeyConstants;
import com.hanserwei.hannote.data.align.constant.TableConstants;
import com.hanserwei.hannote.data.align.domain.mapper.InsertRecordMapper;
import com.hanserwei.hannote.data.align.model.vo.NoteOperateMqDTO;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.apache.rocketmq.spring.annotation.RocketMQMessageListener;
import org.apache.rocketmq.spring.core.RocketMQListener;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.core.io.ClassPathResource;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.data.redis.core.script.RedisScript;
import org.springframework.scripting.support.ResourceScriptSource;
import org.springframework.stereotype.Component;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.Collections;
import java.util.Objects;
@Component
@Slf4j
@RocketMQMessageListener(
consumerGroup = "han_note_group_data_align_" + MQConstants.TOPIC_NOTE_OPERATE,
topic = MQConstants.TOPIC_NOTE_OPERATE
)
public class TodayNotePublishIncrementData2DBConsumer implements RocketMQListener<String> {
@Resource
private RedisTemplate<String, Object> redisTemplate;
@Resource
private InsertRecordMapper insertRecordMapper;
/**
* 表总分片数
*/
@Value("${table.shards}")
private int tableShards;
@Override
public void onMessage(String body) {
log.info("## TodayNotePublishIncrementData2DBConsumer 消费到了 MQ: {}", body);
// 1. 布隆过滤器判断该日增量数据是否已经记录
// 消息字符串转换为DTO类
NoteOperateMqDTO noteOperateMqDTO = JsonUtils.parseObject(body, NoteOperateMqDTO.class);
if (Objects.isNull(noteOperateMqDTO)) {
return;
}
// 发布、被删除的作品的作者Id
Long noteCreatorId = noteOperateMqDTO.getCreatorId();
// 今日日期
String date = LocalDate.now()
.format(DateTimeFormatter.ofPattern("yyyyMMdd"));
String bloomKey = RedisKeyConstants.buildBloomUserNoteOperateListKey(date);
// 1. 布隆过滤器判断该日增量数据是否已经记录
DefaultRedisScript<Long> script = new DefaultRedisScript<>();
// Lua 脚本路径
script.setScriptSource(new ResourceScriptSource(new ClassPathResource("/lua/bloom_today_user_note_publish_check.lua")));
// 返回值类型
script.setResultType(Long.class);
// 执行 Lua 脚本，拿到返回结果
Long result = redisTemplate.execute(script, Collections.singletonList(bloomKey), noteCreatorId);
// 若布隆过滤器判断不存在（绝对正确）
if (Objects.equals(result, 0L)) {
// 根据分片总数，取模，分别获取对应的分片序号
long userIdHashKey = noteCreatorId % tableShards;
// 将日增量变更数据，写入日增量表中
// - t_data_align_note_publish_count_temp_日期_分片序号
insertRecordMapper.insert2DataAlignUserNotePublishCountTempTable(TableConstants.buildTableNameSuffix(date, userIdHashKey), noteCreatorId);
// 3. 数据库写入成功后，再添加布隆过滤器中
RedisScript<Long> bloomAddScript = RedisScript.of("return redis.call('BF.ADD', KEYS[1], ARGV[1])", Long.class);
redisTemplate.execute(bloomAddScript, Collections.singletonList(bloomKey), noteCreatorId);
}
}
}

129
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/consumer/TodayUserFollowIncrementData2DBConsumer.java Normal file
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@@ -0,0 +1,129 @@
package com.hanserwei.hannote.data.align.consumer;
import com.hanserwei.framework.common.utils.JsonUtils;
import com.hanserwei.hannote.data.align.constant.MQConstants;
import com.hanserwei.hannote.data.align.constant.RedisKeyConstants;
import com.hanserwei.hannote.data.align.constant.TableConstants;
import com.hanserwei.hannote.data.align.domain.mapper.InsertRecordMapper;
import com.hanserwei.hannote.data.align.model.vo.FollowUnfollowMqDTO;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.apache.rocketmq.spring.annotation.RocketMQMessageListener;
import org.apache.rocketmq.spring.core.RocketMQListener;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.core.io.ClassPathResource;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.script.DefaultRedisScript;
import org.springframework.data.redis.core.script.RedisScript;
import org.springframework.scripting.support.ResourceScriptSource;
import org.springframework.stereotype.Component;
import org.springframework.transaction.annotation.Transactional;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.Collections;
import java.util.Objects;
@Slf4j
@Component
@RocketMQMessageListener(
consumerGroup = "han_note_group_data_align_" + MQConstants.TOPIC_COUNT_FOLLOWING,
topic = MQConstants.TOPIC_COUNT_FOLLOWING
)
public class TodayUserFollowIncrementData2DBConsumer implements RocketMQListener<String> {
@Resource
private RedisTemplate<String, Object> redisTemplate;
@Resource
private InsertRecordMapper insertRecordMapper;
/**
* 表总分片数
*/
@Value("${table.shards}")
private int tableShards;
@Override
@Transactional(rollbackFor = Exception.class)
public void onMessage(String body) {
log.info("## TodayUserFollowIncrementData2DBConsumer 消费到了 MQ: {}", body);
// 字符串转换为DTO对象
FollowUnfollowMqDTO followUnfollowMqDTO = JsonUtils.parseObject(body, FollowUnfollowMqDTO.class);
if (Objects.isNull(followUnfollowMqDTO)) {
return;
}
// 关注/取关操作
// 源用户 ID
Long userId = followUnfollowMqDTO.getUserId();
// 目标用户 ID
Long targetUserId = followUnfollowMqDTO.getTargetUserId();
// 今日日期
String date = LocalDate.now()
.format(DateTimeFormatter.ofPattern("yyyyMMdd")); // 转字符串
// ------------------------- 源用户的关注数变更记录 -------------------------
// 布隆过滤器判断该日增量数据是否已经记录
String userBloomKey = RedisKeyConstants.buildBloomUserFollowListKey(date);
// 1. 布隆过滤器判断该日增量数据是否已经记录
DefaultRedisScript<Long> script = new DefaultRedisScript<>();
// Lua 脚本路径
script.setScriptSource(new ResourceScriptSource(new ClassPathResource("/lua/bloom_today_user_follow_check.lua")));
// 返回值类型
script.setResultType(Long.class);
// 执行 Lua 脚本，拿到返回结果
Long result = redisTemplate.execute(script, Collections.singletonList(userBloomKey), userId);
// Lua 脚本：添加到布隆过滤器
RedisScript<Long> bloomAddScript = RedisScript.of("return redis.call('BF.ADD', KEYS[1], ARGV[1])", Long.class);
// 若布隆过滤器判断不存在（绝对正确）
if (Objects.equals(result, 0L)) {
// 根据分片总数，取模，分别获取对应的分片序号
long userIdHashKey = userId % tableShards;
try {
// 将日增量变更数据，写入表 t_data_align_following_count_temp_日期_分片序号
insertRecordMapper.insert2DataAlignUserFollowingCountTempTable(
TableConstants.buildTableNameSuffix(date, userIdHashKey), userId);
} catch (Exception e) {
log.error("", e);
throw new RuntimeException(e);
}
// 数据库写入成功后，再添加布隆过滤器中
redisTemplate.execute(bloomAddScript, Collections.singletonList(userBloomKey), userId);
}
// ------------------------- 目标用户的粉丝数变更记录 -------------------------
// 目标用户 ID 对应的 Bloom Key
String targetUserBloomKey = RedisKeyConstants.buildBloomUserFansListKey(date);
// 布隆过滤器判断该日增量数据是否已经记录
result = redisTemplate.execute(script, Collections.singletonList(targetUserBloomKey), targetUserId);
// 若布隆过滤器判断不存在（绝对正确）
if (Objects.equals(result, 0L)) {
// 若无，才会落库，减轻数据库压力
// 根据分片总数，取模，分别获取对应的分片序号
long targetUserIdHashKey = targetUserId % tableShards;
try {
// 将日增量变更数据，写入表 t_data_align_fans_count_temp_日期_分片序号
insertRecordMapper.insert2DataAlignUserFansCountTempTable(
TableConstants.buildTableNameSuffix(date, targetUserIdHashKey), targetUserId);
} catch (Exception e) {
log.error("", e);
throw new RuntimeException(e);
}
// 数据库写入成功后，再添加布隆过滤器中
redisTemplate.execute(bloomAddScript, Collections.singletonList(targetUserBloomKey), targetUserId);
}
}
}

15
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/domain/mapper/InsertRecordMapper.java
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@@ -26,4 +26,19 @@ public interface InsertRecordMapper {
* 用户获得的收藏数：计数变更
*/
void insert2DataAlignUserCollectCountTempTable(@Param("tableNameSuffix") String tableNameSuffix, @Param("userId") Long userId);
/**
* 用户已发布笔记数：计数变更
*/
void insert2DataAlignUserNotePublishCountTempTable(@Param("tableNameSuffix") String tableNameSuffix, @Param("userId") Long userId);
/**
* 用户关注数：计数变更
*/
void insert2DataAlignUserFollowingCountTempTable(@Param("tableNameSuffix") String tableNameSuffix, @Param("userId") Long userId);
/**
* 用户粉丝数：计数变更
*/
void insert2DataAlignUserFansCountTempTable(@Param("tableNameSuffix") String tableNameSuffix, @Param("userId") Long userId);
}

33
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/job/CreateTableXxlJob.java
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@@ -5,13 +5,16 @@ import com.hanserwei.hannote.data.align.domain.mapper.CreateTableMapper;
import com.xxl.job.core.context.XxlJobHelper;
import com.xxl.job.core.handler.annotation.XxlJob;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.cloud.context.config.annotation.RefreshScope;
import org.springframework.stereotype.Component;
import org.springframework.transaction.support.TransactionTemplate;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
@Slf4j
@Component
@RefreshScope
@SuppressWarnings("unused")
@@ -26,6 +29,9 @@ public class CreateTableXxlJob {
@Value("${table.shards}")
private int tableShards;
@Resource
private TransactionTemplate transactionTemplate;
/**
* 1、简单任务示例（Bean模式）
*/
@@ -41,15 +47,24 @@ public class CreateTableXxlJob {
// 表名后缀
String tableNameSuffix = TableConstants.buildTableNameSuffix(date, hashKey);
// 创建表
// 创建表
createTableMapper.createDataAlignFollowingCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignFansCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignNoteCollectCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignUserCollectCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignUserLikeCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignNoteLikeCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignNotePublishCountTempTable(tableNameSuffix);
transactionTemplate.execute(status -> {
try {
// 创建表
createTableMapper.createDataAlignFollowingCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignFansCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignNoteCollectCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignUserCollectCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignUserLikeCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignNoteLikeCountTempTable(tableNameSuffix);
createTableMapper.createDataAlignNotePublishCountTempTable(tableNameSuffix);
return true;
} catch (Exception e) {
status.setRollbackOnly();
log.error("创建表失败", e);
}
return false;
});
}
}
XxlJobHelper.log("## 创建日增量数据表成功，表名后缀: {}...", date);

29
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/model/vo/FollowUnfollowMqDTO.java Normal file
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@@ -0,0 +1,29 @@
package com.hanserwei.hannote.data.align.model.vo;
import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@AllArgsConstructor
@NoArgsConstructor
@Builder
public class FollowUnfollowMqDTO {
/**
* 原用户
*/
private Long userId;
/**
* 目标用户
*/
private Long targetUserId;
/**
* 1:关注 0:取关
*/
private Integer type;
}

29
han-note-data-align/src/main/java/com/hanserwei/hannote/data/align/model/vo/NoteOperateMqDTO.java Normal file
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@@ -0,0 +1,29 @@
package com.hanserwei.hannote.data.align.model.vo;
import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@AllArgsConstructor
@NoArgsConstructor
@Builder
public class NoteOperateMqDTO {
/**
* 笔记发布者 ID
*/
private Long creatorId;
/**
* 笔记 ID
*/
private Long noteId;
/**
* 操作类型： 0 - 笔记删除； 1：笔记发布；
*/
private Integer type;
}

16
han-note-data-align/src/main/resources/lua/bloom_today_user_follow_check.lua Normal file
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@@ -0,0 +1,16 @@
-- LUA 脚本：日增量用户关注、取关变更数据布隆过滤器
local key = KEYS[1] -- 操作的 Redis Key
local userId = ARGV[1] -- Redis Value
-- 使用 EXISTS 命令检查布隆过滤器是否存在
local exists = redis.call('EXISTS', key)
if exists == 0 then
-- 创建布隆过滤器
redis.call('BF.ADD', key, '')
-- 设置过期时间，一天后过期
redis.call("EXPIRE", key, 20 * 60 * 60)
end
-- 校验该变更数据是否已经存在(1 表示已存在，0 表示不存在)
return redis.call('BF.EXISTS', key, userId)

16
han-note-data-align/src/main/resources/lua/bloom_today_user_note_publish_check.lua Normal file
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@@ -0,0 +1,16 @@
-- LUA 脚本：日增量笔记发布、删除变更数据布隆过滤器
local key = KEYS[1] -- 操作的 Redis Key
local userId = ARGV[1] -- Redis Value
-- 使用 EXISTS 命令检查布隆过滤器是否存在
local exists = redis.call('EXISTS', key)
if exists == 0 then
-- 创建布隆过滤器
redis.call('BF.ADD', key, '')
-- 设置过期时间，一天后过期
redis.call("EXPIRE", key, 20 * 60 * 60)
end
-- 校验该变更数据是否已经存在(1 表示已存在，0 表示不存在)
return redis.call('BF.EXISTS', key, userId)

4
han-note-data-align/src/main/resources/mapperxml/CreateTableMapper.xml
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@@ -76,9 +76,9 @@
CREATE TABLE IF NOT EXISTS `t_data_align_note_publish_count_temp_${tableNameSuffix}`
(
`id` bigint unsigned NOT NULL AUTO_INCREMENT COMMENT '主键ID',
`note_id` bigint unsigned NOT NULL COMMENT '笔记ID',
`user_id` bigint unsigned NOT NULL COMMENT '用户ID',
PRIMARY KEY (`id`) USING BTREE,
UNIQUE KEY `uk_note_id` (`note_id`)
UNIQUE KEY `uk_user_id` (`user_id`)
) ENGINE = InnoDB
DEFAULT CHARSET = utf8mb4
COLLATE = utf8mb4_unicode_ci COMMENT ='数据对齐日增量表：用户发布笔记数';

15
han-note-data-align/src/main/resources/mapperxml/InsertRecordMapper.xml
View File

@@ -20,4 +20,19 @@
insert into `t_data_align_user_collect_count_temp_${tableNameSuffix}` (user_id)
values (#{userId})
</insert>
<insert id="insert2DataAlignUserNotePublishCountTempTable" parameterType="map">
insert into `t_data_align_note_publish_count_temp_${tableNameSuffix}` (user_id)
values (#{userId})
</insert>
<insert id="insert2DataAlignUserFollowingCountTempTable" parameterType="map">
insert into `t_data_align_following_count_temp_${tableNameSuffix}` (user_id)
values (#{userId})
</insert>
<insert id="insert2DataAlignUserFansCountTempTable" parameterType="map">
insert into `t_data_align_fans_count_temp_${tableNameSuffix}` (user_id)
values (#{userId})
</insert>
</mapper>