在现代应用开发中,签到打卡功能广泛应用于企业考勤管理、在线教育、社区运营等多个领域。
它不仅是一种记录用户行为的方式,也是提升用户粘性和活跃度的重要手段。
本文将介绍5种签到打卡的实现方案。
一、基于关系型数据库的传统签到系统
1.1 基本原理
最直接的签到系统实现方式是利用关系型数据库(如MySQL、PostgreSQL)记录每次签到行为。
这种方案设计简单,易于理解和实现,适合大多数中小型应用场景。
1.2 数据模型设计
sql
-- 用户表
CREATE TABLE users (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
username VARCHAR(50) NOT NULL UNIQUE,
password VARCHAR(100) NOT NULL,
email VARCHAR(100) UNIQUE,
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- 签到记录表
CREATE TABLE check_ins (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
user_id BIGINT NOT NULL,
check_in_time TIMESTAMP NOT NULL,
check_in_date DATE NOT NULL,
check_in_type VARCHAR(20) NOT NULL, -- 'DAILY', 'COURSE', 'MEETING' 等
location VARCHAR(255),
device_info VARCHAR(255),
remark VARCHAR(255),
FOREIGN KEY (user_id) REFERENCES users(id),
UNIQUE KEY unique_user_date (user_id, check_in_date, check_in_type)
);
-- 签到统计表
CREATE TABLE check_in_stats (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
user_id BIGINT NOT NULL,
total_days INT DEFAULT 0,
continuous_days INT DEFAULT 0,
last_check_in_date DATE,
FOREIGN KEY (user_id) REFERENCES users(id),
UNIQUE KEY unique_user (user_id)
);
1.3 核心代码实现
实体类设计
kotlin
@Data
@TableName("check_ins")
public class CheckIn {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
@TableField("user_id")
private Long userId;
@TableField("check_in_time")
private LocalDateTime checkInTime;
@TableField("check_in_date")
private LocalDate checkInDate;
@TableField("check_in_type")
private String checkInType;
private String location;
@TableField("device_info")
private String deviceInfo;
private String remark;
}
@Data
@TableName("check_in_stats")
public class CheckInStats {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
@TableField("user_id")
private Long userId;
@TableField("total_days")
private Integer totalDays = 0;
@TableField("continuous_days")
private Integer continuousDays = 0;
@TableField("last_check_in_date")
private LocalDate lastCheckInDate;
}
@Data
@TableName("users")
public class User {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
private String username;
private String password;
private String email;
@TableField("created_at")
private LocalDateTime createdAt;
}
Mapper层
less
@Mapper
public interface CheckInMapper extends BaseMapper<CheckIn> {
@Select("SELECT COUNT(*) FROM check_ins WHERE user_id = #{userId} AND check_in_type = #{type}")
int countByUserIdAndType(@Param("userId") Long userId, @Param("type") String type);
@Select("SELECT * FROM check_ins WHERE user_id = #{userId} AND check_in_date BETWEEN #{startDate} AND #{endDate} ORDER BY check_in_date ASC")
List<CheckIn> findByUserIdAndDateBetween(
@Param("userId") Long userId,
@Param("startDate") LocalDate startDate,
@Param("endDate") LocalDate endDate);
@Select("SELECT COUNT(*) FROM check_ins WHERE user_id = #{userId} AND check_in_date = #{date} AND check_in_type = #{type}")
int existsByUserIdAndDateAndType(
@Param("userId") Long userId,
@Param("date") LocalDate date,
@Param("type") String type);
}
@Mapper
public interface CheckInStatsMapper extends BaseMapper<CheckInStats> {
@Select("SELECT * FROM check_in_stats WHERE user_id = #{userId}")
CheckInStats findByUserId(@Param("userId") Long userId);
}
@Mapper
public interface UserMapper extends BaseMapper<User> {
@Select("SELECT * FROM users WHERE username = #{username}")
User findByUsername(@Param("username") String username);
}
Service层
scss
@Service
@Transactional
public class CheckInService {
@Autowired
private CheckInMapper checkInMapper;
@Autowired
private CheckInStatsMapper checkInStatsMapper;
@Autowired
private UserMapper userMapper;
/**
* 用户签到
*/
public CheckIn checkIn(Long userId, String type, String location, String deviceInfo, String remark) {
// 检查用户是否存在
User user = userMapper.selectById(userId);
if (user == null) {
throw new RuntimeException("User not found");
}
LocalDate today = LocalDate.now();
// 检查今天是否已经签到
if (checkInMapper.existsByUserIdAndDateAndType(userId, today, type) > 0) {
throw new RuntimeException("Already checked in today");
}
// 创建签到记录
CheckIn checkIn = new CheckIn();
checkIn.setUserId(userId);
checkIn.setCheckInTime(LocalDateTime.now());
checkIn.setCheckInDate(today);
checkIn.setCheckInType(type);
checkIn.setLocation(location);
checkIn.setDeviceInfo(deviceInfo);
checkIn.setRemark(remark);
checkInMapper.insert(checkIn);
// 更新签到统计
updateCheckInStats(userId, today);
return checkIn;
}
/**
* 更新签到统计信息
*/
private void updateCheckInStats(Long userId, LocalDate today) {
CheckInStats stats = checkInStatsMapper.findByUserId(userId);
if (stats == null) {
stats = new CheckInStats();
stats.setUserId(userId);
stats.setTotalDays(1);
stats.setContinuousDays(1);
stats.setLastCheckInDate(today);
checkInStatsMapper.insert(stats);
} else {
// 更新总签到天数
stats.setTotalDays(stats.getTotalDays() + 1);
// 更新连续签到天数
if (stats.getLastCheckInDate() != null) {
if (today.minusDays(1).equals(stats.getLastCheckInDate())) {
// 连续签到
stats.setContinuousDays(stats.getContinuousDays() + 1);
} else if (today.equals(stats.getLastCheckInDate())) {
// 当天重复签到,不计算连续天数
} else {
// 中断连续签到
stats.setContinuousDays(1);
}
}
stats.setLastCheckInDate(today);
checkInStatsMapper.updateById(stats);
}
}
/**
* 获取用户签到统计
*/
public CheckInStats getCheckInStats(Long userId) {
CheckInStats stats = checkInStatsMapper.findByUserId(userId);
if (stats == null) {
throw new RuntimeException("Check-in stats not found");
}
return stats;
}
/**
* 获取用户指定日期范围内的签到记录
*/
public List<CheckIn> getCheckInHistory(Long userId, LocalDate startDate, LocalDate endDate) {
return checkInMapper.findByUserIdAndDateBetween(userId, startDate, endDate);
}
}
Controller层
less
@RestController
@RequestMapping("/api/check-ins")
public class CheckInController {
@Autowired
private CheckInService checkInService;
@PostMapping
public ResponseEntity<CheckIn> checkIn(@RequestBody CheckInRequest request) {
CheckIn checkIn = checkInService.checkIn(
request.getUserId(),
request.getType(),
request.getLocation(),
request.getDeviceInfo(),
request.getRemark()
);
return ResponseEntity.ok(checkIn);
}
@GetMapping("/stats/{userId}")
public ResponseEntity<CheckInStats> getStats(@PathVariable Long userId) {
CheckInStats stats = checkInService.getCheckInStats(userId);
return ResponseEntity.ok(stats);
}
@GetMapping("/history/{userId}")
public ResponseEntity<List<CheckIn>> getHistory(
@PathVariable Long userId,
@RequestParam @DateTimeFormat(iso = DateTimeFormat.ISO.DATE) LocalDate startDate,
@RequestParam @DateTimeFormat(iso = DateTimeFormat.ISO.DATE) LocalDate endDate) {
List<CheckIn> history = checkInService.getCheckInHistory(userId, startDate, endDate);
return ResponseEntity.ok(history);
}
}
@Data
public class CheckInRequest {
private Long userId;
private String type;
private String location;
private String deviceInfo;
private String remark;
}
1.4 优缺点分析
优点:
- 设计简单直观,易于理解和实现
- 支持丰富的数据查询和统计功能
- 事务支持,确保数据一致性
- 易于与现有系统集成
缺点:
- 数据量大时查询性能可能下降
- 连续签到统计等复杂查询逻辑实现相对繁琐
- 不适合高并发场景
- 数据库负载较高
1.5 适用场景
- 中小型企业的员工考勤系统
- 课程签到系统
- 会议签到管理
- 用户量不大的社区签到功能
二、基于Redis的高性能签到系统
2.1 基本原理
利用Redis的高性能和丰富的数据结构,可以构建一个响应迅速的签到系统。尤其是对于高并发场景和需要实时统计的应用,Redis提供了显著的性能优势。
2.2 系统设计
Redis中我们可以使用以下几种数据结构来实现签到系统:
- String: 记录用户最后签到时间和连续签到天数
- Hash: 存储用户当天的签到详情
- Sorted Set: 按签到时间排序的用户列表,便于排行榜等功能
- Set: 记录每天签到的用户集合
2.3 核心代码实现
Redis配置
arduino
@Configuration
public class RedisConfig {
@Bean
public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) {
RedisTemplate<String, Object> template = new RedisTemplate<>();
template.setConnectionFactory(factory);
// 使用Jackson2JsonRedisSerializer序列化和反序列化redis的value值
Jackson2JsonRedisSerializer<Object> serializer = new Jackson2JsonRedisSerializer<>(Object.class);
ObjectMapper mapper = new ObjectMapper();
mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
mapper.activateDefaultTyping(LaissezFaireSubTypeValidator.instance,
ObjectMapper.DefaultTyping.NON_FINAL, JsonTypeInfo.As.PROPERTY);
serializer.setObjectMapper(mapper);
template.setValueSerializer(serializer);
template.setKeySerializer(new StringRedisSerializer());
template.setHashKeySerializer(new StringRedisSerializer());
template.setHashValueSerializer(serializer);
template.afterPropertiesSet();
return template;
}
}
签到服务实现
ini
@Service
public class RedisCheckInService {
private static final String USER_CHECKIN_KEY = "checkin:user:";
private static final String DAILY_CHECKIN_KEY = "checkin:daily:";
private static final String CHECKIN_RANK_KEY = "checkin:rank:";
private static final String USER_STATS_KEY = "checkin:stats:";
@Autowired
private RedisTemplate<String, Object> redisTemplate;
@Autowired
private StringRedisTemplate stringRedisTemplate;
/**
* 用户签到
*/
public boolean checkIn(Long userId, String location) {
String today = LocalDate.now().format(DateTimeFormatter.ISO_DATE);
String userKey = USER_CHECKIN_KEY + userId;
String dailyKey = DAILY_CHECKIN_KEY + today;
// 判断用户今天是否已经签到
Boolean isMember = redisTemplate.opsForSet().isMember(dailyKey, userId);
if (isMember != null && isMember) {
return false; // 已经签到过了
}
// 记录用户签到
redisTemplate.opsForSet().add(dailyKey, userId);
// 设置过期时间(35天后过期,以便统计连续签到)
redisTemplate.expire(dailyKey, 35, TimeUnit.DAYS);
// 记录用户签到详情
Map<String, String> checkInInfo = new HashMap<>();
checkInInfo.put("time", LocalDateTime.now().toString());
checkInInfo.put("location", location);
redisTemplate.opsForHash().putAll(userKey + ":" + today, checkInInfo);
// 更新签到排行榜
redisTemplate.opsForZSet().incrementScore(CHECKIN_RANK_KEY + today, userId, 1);
// 更新用户签到统计
updateUserCheckInStats(userId);
return true;
}
/**
* 更新用户签到统计
*/
private void updateUserCheckInStats(Long userId) {
String userStatsKey = USER_STATS_KEY + userId;
// 获取当前日期
LocalDate today = LocalDate.now();
String todayStr = today.format(DateTimeFormatter.ISO_DATE);
// 获取用户最后签到日期
String lastCheckInDate = (String) redisTemplate.opsForHash().get(userStatsKey, "lastCheckInDate");
// 更新总签到天数
redisTemplate.opsForHash().increment(userStatsKey, "totalDays", 1);
// 更新连续签到天数
if (lastCheckInDate != null) {
LocalDate lastDate = LocalDate.parse(lastCheckInDate, DateTimeFormatter.ISO_DATE);
if (today.minusDays(1).equals(lastDate)) {
// 连续签到
redisTemplate.opsForHash().increment(userStatsKey, "continuousDays", 1);
} else if (today.equals(lastDate)) {
// 当天重复签到,不增加连续天数
} else {
// 中断连续签到
redisTemplate.opsForHash().put(userStatsKey, "continuousDays", 1);
}
} else {
// 第一次签到
redisTemplate.opsForHash().put(userStatsKey, "continuousDays", 1);
}
// 更新最后签到日期
redisTemplate.opsForHash().put(userStatsKey, "lastCheckInDate", todayStr);
}
/**
* 获取用户签到统计信息
*/
public Map<Object, Object> getUserCheckInStats(Long userId) {
String userStatsKey = USER_STATS_KEY + userId;
return redisTemplate.opsForHash().entries(userStatsKey);
}
/**
* 获取用户是否已签到
*/
public boolean isUserCheckedInToday(Long userId) {
String today = LocalDate.now().format(DateTimeFormatter.ISO_DATE);
String dailyKey = DAILY_CHECKIN_KEY + today;
Boolean isMember = redisTemplate.opsForSet().isMember(dailyKey, userId);
return isMember != null && isMember;
}
/**
* 获取今日签到用户数
*/
public long getTodayCheckInCount() {
String today = LocalDate.now().format(DateTimeFormatter.ISO_DATE);
String dailyKey = DAILY_CHECKIN_KEY + today;
Long size = redisTemplate.opsForSet().size(dailyKey);
return size != null ? size : 0;
}
/**
* 获取签到排行榜
*/
public Set<ZSetOperations.TypedTuple<Object>> getCheckInRank(int limit) {
String today = LocalDate.now().format(DateTimeFormatter.ISO_DATE);
String rankKey = CHECKIN_RANK_KEY + today;
return redisTemplate.opsForZSet().reverseRangeWithScores(rankKey, 0, limit - 1);
}
/**
* 检查用户在指定日期是否签到
*/
public boolean checkUserSignedInDate(Long userId, LocalDate date) {
String dateStr = date.format(DateTimeFormatter.ISO_DATE);
String dailyKey = DAILY_CHECKIN_KEY + dateStr;
Boolean isMember = redisTemplate.opsForSet().isMember(dailyKey, userId);
return isMember != null && isMember;
}
/**
* 获取用户指定月份的签到情况
*/
public List<String> getMonthlyCheckInStatus(Long userId, int year, int month) {
List<String> result = new ArrayList<>();
YearMonth yearMonth = YearMonth.of(year, month);
// 获取指定月份的第一天和最后一天
LocalDate firstDay = yearMonth.atDay(1);
LocalDate lastDay = yearMonth.atEndOfMonth();
// 逐一检查每一天是否签到
LocalDate currentDate = firstDay;
while (!currentDate.isAfter(lastDay)) {
if (checkUserSignedInDate(userId, currentDate)) {
result.add(currentDate.format(DateTimeFormatter.ISO_DATE));
}
currentDate = currentDate.plusDays(1);
}
return result;
}
}
控制器实现
less
@RestController
@RequestMapping("/api/redis-check-in")
public class RedisCheckInController {
@Autowired
private RedisCheckInService checkInService;
@PostMapping
public ResponseEntity<?> checkIn(@RequestBody RedisCheckInRequest request) {
boolean success = checkInService.checkIn(request.getUserId(), request.getLocation());
if (success) {
return ResponseEntity.ok(Map.of("message", "Check-in successful"));
} else {
return ResponseEntity.badRequest().body(Map.of("message", "Already checked in today"));
}
}
@GetMapping("/stats/{userId}")
public ResponseEntity<Map<Object, Object>> getUserStats(@PathVariable Long userId) {
Map<Object, Object> stats = checkInService.getUserCheckInStats(userId);
return ResponseEntity.ok(stats);
}
@GetMapping("/status/{userId}")
public ResponseEntity<Map<String, Object>> getCheckInStatus(@PathVariable Long userId) {
boolean checkedIn = checkInService.isUserCheckedInToday(userId);
long todayCount = checkInService.getTodayCheckInCount();
Map<String, Object> response = new HashMap<>();
response.put("checkedIn", checkedIn);
response.put("todayCount", todayCount);
return ResponseEntity.ok(response);
}
@GetMapping("/rank")
public ResponseEntity<Set<ZSetOperations.TypedTuple<Object>>> getCheckInRank(
@RequestParam(defaultValue = "10") int limit) {
Set<ZSetOperations.TypedTuple<Object>> rank = checkInService.getCheckInRank(limit);
return ResponseEntity.ok(rank);
}
@GetMapping("/monthly/{userId}")
public ResponseEntity<List<String>> getMonthlyStatus(
@PathVariable Long userId,
@RequestParam int year,
@RequestParam int month) {
List<String> checkInDays = checkInService.getMonthlyCheckInStatus(userId, year, month);
return ResponseEntity.ok(checkInDays);
}
}
@Data
public class RedisCheckInRequest {
private Long userId;
private String location;
}
2.4 优缺点分析
优点:
- 极高的性能,支持高并发场景
- 丰富的数据结构支持多种签到功能(排行榜、签到日历等)
- 内存数据库,响应速度快
- 适合实时统计和分析
缺点:
- 数据持久性不如关系型数据库
- 复杂查询能力有限
- 内存成本较高
2.5 适用场景
- 大型社区或应用的签到功能
- 实时性要求高的签到系统
- 高并发场景下的打卡功能
- 需要签到排行榜、签到日历等交互功能的应用
三、基于位图(Bitmap)的连续签到统计系统
3.1 基本原理
Redis的Bitmap是一种非常节省空间的数据结构,它可以用来记录签到状态,每个bit位代表一天的签到状态(0表示未签到,1表示已签到)。利用Bitmap可以高效地实现连续签到统计、月度签到日历等功能,同时极大地节省内存使用。
3.2 系统设计
主要使用Redis的Bitmap操作来记录和统计用户签到情况:
- 每个用户每个月的签到记录使用一个Bitmap
- Bitmap的每一位代表当月的一天(1-31)
- 通过位操作可以高效地统计签到天数、连续签到等信息
3.3 核心代码实现
ini
@Service
public class BitmapCheckInService {
@Autowired
private StringRedisTemplate redisTemplate;
/**
* 用户签到
*/
public boolean checkIn(Long userId) {
LocalDate today = LocalDate.now();
int day = today.getDayOfMonth(); // 获取当月的第几天
String key = buildSignKey(userId, today);
// 检查今天是否已经签到
Boolean isSigned = redisTemplate.opsForValue().getBit(key, day - 1);
if (isSigned != null && isSigned) {
return false; // 已经签到
}
// 设置签到标记
redisTemplate.opsForValue().setBit(key, day - 1, true);
// 设置过期时间(确保数据不会永久保存)
redisTemplate.expire(key, 100, TimeUnit.DAYS);
// 更新连续签到记录
updateContinuousSignDays(userId);
return true;
}
/**
* 更新连续签到天数
*/
private void updateContinuousSignDays(Long userId) {
LocalDate today = LocalDate.now();
String continuousKey = "user:sign:continuous:" + userId;
// 判断昨天是否签到
boolean yesterdayChecked = isSignedIn(userId, today.minusDays(1));
if (yesterdayChecked) {
// 昨天签到了,连续签到天数+1
redisTemplate.opsForValue().increment(continuousKey);
} else {
// 昨天没签到,重置连续签到天数为1
redisTemplate.opsForValue().set(continuousKey, "1");
}
}
/**
* 判断用户指定日期是否签到
*/
public boolean isSignedIn(Long userId, LocalDate date) {
int day = date.getDayOfMonth();
String key = buildSignKey(userId, date);
Boolean isSigned = redisTemplate.opsForValue().getBit(key, day - 1);
return isSigned != null && isSigned;
}
/**
* 获取用户连续签到天数
*/
public int getContinuousSignDays(Long userId) {
String continuousKey = "user:sign:continuous:" + userId;
String value = redisTemplate.opsForValue().get(continuousKey);
return value != null ? Integer.parseInt(value) : 0;
}
/**
* 获取用户当月签到次数
*/
public long getMonthSignCount(Long userId, LocalDate date) {
String key = buildSignKey(userId, date);
int dayOfMonth = date.lengthOfMonth(); // 当月总天数
return redisTemplate.execute((RedisCallback<Long>) con -> {
return con.bitCount(key.getBytes());
});
}
/**
* 获取用户当月签到情况
*/
public List<Integer> getMonthSignData(Long userId, LocalDate date) {
List<Integer> result = new ArrayList<>();
String key = buildSignKey(userId, date);
int dayOfMonth = date.lengthOfMonth(); // 当月总天数
for (int i = 0; i < dayOfMonth; i++) {
Boolean isSigned = redisTemplate.opsForValue().getBit(key, i);
result.add(isSigned != null && isSigned ? 1 : 0);
}
return result;
}
/**
* 获取用户当月首次签到时间
*/
public int getFirstSignDay(Long userId, LocalDate date) {
String key = buildSignKey(userId, date);
int dayOfMonth = date.lengthOfMonth(); // 当月总天数
for (int i = 0; i < dayOfMonth; i++) {
Boolean isSigned = redisTemplate.opsForValue().getBit(key, i);
if (isSigned != null && isSigned) {
return i + 1; // 返回第一次签到的日期
}
}
return -1; // 本月没有签到记录
}
/**
* 构建签到Key
*/
private String buildSignKey(Long userId, LocalDate date) {
return String.format("user:sign:%d:%d%02d", userId, date.getYear(), date.getMonthValue());
}
}
控制器实现
less
@RestController
@RequestMapping("/api/bitmap-check-in")
public class BitmapCheckInController {
@Autowired
private BitmapCheckInService checkInService;
@PostMapping("/{userId}")
public ResponseEntity<?> checkIn(@PathVariable Long userId) {
boolean success = checkInService.checkIn(userId);
if (success) {
Map<String, Object> response = new HashMap<>();
response.put("success", true);
response.put("continuousDays", checkInService.getContinuousSignDays(userId));
return ResponseEntity.ok(response);
} else {
return ResponseEntity.badRequest().body(Map.of("message", "Already checked in today"));
}
}
@GetMapping("/{userId}/status")
public ResponseEntity<?> checkInStatus(
@PathVariable Long userId,
@RequestParam(required = false)
@DateTimeFormat(iso = DateTimeFormat.ISO.DATE) LocalDate date) {
if (date == null) {
date = LocalDate.now();
}
Map<String, Object> response = new HashMap<>();
response.put("signedToday", checkInService.isSignedIn(userId, date));
response.put("continuousDays", checkInService.getContinuousSignDays(userId));
response.put("monthSignCount", checkInService.getMonthSignCount(userId, date));
response.put("monthSignData", checkInService.getMonthSignData(userId, date));
return ResponseEntity.ok(response);
}
@GetMapping("/{userId}/first-sign-day")
public ResponseEntity<Integer> getFirstSignDay(
@PathVariable Long userId,
@RequestParam(required = false)
@DateTimeFormat(iso = DateTimeFormat.ISO.DATE) LocalDate date) {
if (date == null) {
date = LocalDate.now();
}
int firstDay = checkInService.getFirstSignDay(userId, date);
return ResponseEntity.ok(firstDay);
}
}
3.4 优缺点分析
优点:
- 极其节省存储空间,一个月的签到记录仅需要4字节
- 位操作性能高,适合大规模用户
- 统计操作(如计算签到天数)非常高效
- 适合实现签到日历和连续签到统计
缺点:
- 不能存储签到的详细信息(如签到时间、地点等)
- 仅适合简单的签到/未签到二元状态记录
- 复杂的签到业务逻辑实现较困难
- 历史数据查询相对复杂
3.5 适用场景
- 需要节省存储空间的大规模用户签到系统
- 社区/电商平台的每日签到奖励功能
- 需要高效计算连续签到天数的应用
- 移动应用的签到日历功能
四、基于地理位置的签到打卡系统
4.1 基本原理
地理位置签到系统利用用户的GPS定位信息,验证用户是否在指定区域内进行签到,常用于企业考勤、学校上课点名、实地活动签到等场景。
该方案结合了关系型数据库存储签到记录和Redis的GEO功能进行位置验证。
4.2 数据模型设计
sql
-- 签到位置表
CREATE TABLE check_in_locations (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
name VARCHAR(100) NOT NULL,
latitude DOUBLE NOT NULL,
longitude DOUBLE NOT NULL,
radius DOUBLE NOT NULL, -- 有效半径(米)
address VARCHAR(255),
location_type VARCHAR(50),
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
-- 地理位置签到记录表
CREATE TABLE geo_check_ins (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
user_id BIGINT NOT NULL,
location_id BIGINT NOT NULL,
check_in_time TIMESTAMP NOT NULL,
latitude DOUBLE NOT NULL,
longitude DOUBLE NOT NULL,
accuracy DOUBLE, -- 定位精度(米)
is_valid BOOLEAN DEFAULT TRUE, -- 是否有效签到
device_info VARCHAR(255),
FOREIGN KEY (user_id) REFERENCES users(id),
FOREIGN KEY (location_id) REFERENCES check_in_locations(id)
);
4.3 核心代码实现
实体类设计
kotlin
@Data
@TableName("check_in_locations")
public class CheckInLocation {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
private String name;
private Double latitude;
private Double longitude;
private Double radius; // 单位:米
private String address;
@TableField("location_type")
private String locationType;
@TableField("created_at")
private LocalDateTime createdAt;
}
@Data
@TableName("geo_check_ins")
public class GeoCheckIn {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
@TableField("user_id")
private Long userId;
@TableField("location_id")
private Long locationId;
@TableField("check_in_time")
private LocalDateTime checkInTime;
private Double latitude;
private Double longitude;
private Double accuracy;
@TableField("is_valid")
private Boolean isValid = true;
@TableField("device_info")
private String deviceInfo;
}
Mapper层
less
@Mapper
public interface CheckInLocationMapper extends BaseMapper<CheckInLocation> {
@Select("SELECT * FROM check_in_locations WHERE location_type = #{locationType}")
List<CheckInLocation> findByLocationType(@Param("locationType") String locationType);
}
@Mapper
public interface GeoCheckInMapper extends BaseMapper<GeoCheckIn> {
@Select("SELECT * FROM geo_check_ins WHERE user_id = #{userId} AND check_in_time BETWEEN #{startTime} AND #{endTime}")
List<GeoCheckIn> findByUserIdAndCheckInTimeBetween(
@Param("userId") Long userId,
@Param("startTime") LocalDateTime startTime,
@Param("endTime") LocalDateTime endTime);
@Select("SELECT * FROM geo_check_ins WHERE user_id = #{userId} AND location_id = #{locationId} " +
"AND DATE(check_in_time) = DATE(#{date})")
GeoCheckIn findByUserIdAndLocationIdAndDate(
@Param("userId") Long userId,
@Param("locationId") Long locationId,
@Param("date") LocalDateTime date);
}
Service层
java
@Service
@Transactional
public class GeoCheckInService {
@Autowired
private CheckInLocationMapper locationMapper;
@Autowired
private GeoCheckInMapper geoCheckInMapper;
@Autowired
private UserMapper userMapper;
@Autowired
private StringRedisTemplate redisTemplate;
private static final String GEO_KEY = "geo:locations";
@PostConstruct
public void init() {
// 将所有签到位置加载到Redis GEO中
List<CheckInLocation> locations = locationMapper.selectList(null);
if (!locations.isEmpty()) {
Map<String, Point> locationPoints = new HashMap<>();
for (CheckInLocation location : locations) {
locationPoints.put(location.getId().toString(),
new Point(location.getLongitude(), location.getLatitude()));
}
redisTemplate.opsForGeo().add(GEO_KEY, locationPoints);
}
}
/**
* 添加新的签到地点
*/
public CheckInLocation addCheckInLocation(CheckInLocation location) {
location.setCreatedAt(LocalDateTime.now());
locationMapper.insert(location);
// 添加到Redis GEO
redisTemplate.opsForGeo().add(GEO_KEY,
new Point(location.getLongitude(), location.getLatitude()),
location.getId().toString());
return location;
}
/**
* 用户地理位置签到
*/
public GeoCheckIn checkIn(Long userId, Long locationId, Double latitude,
Double longitude, Double accuracy, String deviceInfo) {
// 验证用户和位置是否存在
User user = userMapper.selectById(userId);
if (user == null) {
throw new RuntimeException("User not found");
}
CheckInLocation location = locationMapper.selectById(locationId);
if (location == null) {
throw new RuntimeException("Check-in location not found");
}
// 检查今天是否已经在该位置签到
LocalDateTime now = LocalDateTime.now();
GeoCheckIn existingCheckIn = geoCheckInMapper
.findByUserIdAndLocationIdAndDate(userId, locationId, now);
if (existingCheckIn != null) {
throw new RuntimeException("Already checked in at this location today");
}
// 验证用户是否在签到范围内
boolean isWithinRange = isWithinCheckInRange(
latitude, longitude, location.getLatitude(), location.getLongitude(), location.getRadius());
// 创建签到记录
GeoCheckIn checkIn = new GeoCheckIn();
checkIn.setUserId(userId);
checkIn.setLocationId(locationId);
checkIn.setCheckInTime(now);
checkIn.setLatitude(latitude);
checkIn.setLongitude(longitude);
checkIn.setAccuracy(accuracy);
checkIn.setIsValid(isWithinRange);
checkIn.setDeviceInfo(deviceInfo);
geoCheckInMapper.insert(checkIn);
return checkIn;
}
/**
* 检查用户是否在签到范围内
*/
private boolean isWithinCheckInRange(Double userLat, Double userLng,
Double locationLat, Double locationLng, Double radius) {
// 使用Redis GEO计算距离
Distance distance = redisTemplate.opsForGeo().distance(
GEO_KEY,
locationLat + "," + locationLng,
userLat + "," + userLng,
Metrics.METERS
);
return distance != null && distance.getValue() <= radius;
}
/**
* 查找附近的签到地点
*/
public List<GeoResult<RedisGeoCommands.GeoLocation<String>>> findNearbyLocations(
Double latitude, Double longitude, Double radius) {
Circle circle = new Circle(new Point(longitude, latitude), new Distance(radius, Metrics.METERS));
RedisGeoCommands.GeoRadiusCommandArgs args = RedisGeoCommands.GeoRadiusCommandArgs
.newGeoRadiusArgs().includeDistance().sortAscending();
GeoResults<RedisGeoCommands.GeoLocation<String>> results = redisTemplate.opsForGeo()
.radius(GEO_KEY, circle, args);
return results != null ? results.getContent() : Collections.emptyList();
}
/**
* 获取用户签到历史
*/
public List<GeoCheckIn> getUserCheckInHistory(Long userId, LocalDate startDate, LocalDate endDate) {
LocalDateTime startDateTime = startDate.atStartOfDay();
LocalDateTime endDateTime = endDate.atTime(23, 59, 59);
return geoCheckInMapper.findByUserIdAndCheckInTimeBetween(
userId, startDateTime, endDateTime);
}
}
Controller层
less
@RestController
@RequestMapping("/api/geo-check-in")
public class GeoCheckInController {
@Autowired
private GeoCheckInService geoCheckInService;
@PostMapping("/locations")
public ResponseEntity<CheckInLocation> addLocation(@RequestBody CheckInLocation location) {
CheckInLocation savedLocation = geoCheckInService.addCheckInLocation(location);
return ResponseEntity.ok(savedLocation);
}
@PostMapping
public ResponseEntity<?> checkIn(@RequestBody GeoCheckInRequest request) {
try {
GeoCheckIn checkIn = geoCheckInService.checkIn(
request.getUserId(),
request.getLocationId(),
request.getLatitude(),
request.getLongitude(),
request.getAccuracy(),
request.getDeviceInfo()
);
Map<String, Object> response = new HashMap<>();
response.put("id", checkIn.getId());
response.put("checkInTime", checkIn.getCheckInTime());
response.put("isValid", checkIn.getIsValid());
if (!checkIn.getIsValid()) {
response.put("message", "You are not within the valid check-in range");
}
return ResponseEntity.ok(response);
} catch (RuntimeException e) {
return ResponseEntity.badRequest().body(Map.of("message", e.getMessage()));
}
}
@GetMapping("/nearby")
public ResponseEntity<?> findNearbyLocations(
@RequestParam Double latitude,
@RequestParam Double longitude,
@RequestParam(defaultValue = "500") Double radius) {
List<GeoResult<RedisGeoCommands.GeoLocation<String>>> locations =
geoCheckInService.findNearbyLocations(latitude, longitude, radius);
return ResponseEntity.ok(locations);
}
@GetMapping("/history/{userId}")
public ResponseEntity<List<GeoCheckIn>> getUserHistory(
@PathVariable Long userId,
@RequestParam @DateTimeFormat(iso = DateTimeFormat.ISO.DATE) LocalDate startDate,
@RequestParam @DateTimeFormat(iso = DateTimeFormat.ISO.DATE) LocalDate endDate) {
List<GeoCheckIn> history = geoCheckInService.getUserCheckInHistory(userId, startDate, endDate);
return ResponseEntity.ok(history);
}
}
@Data
public class GeoCheckInRequest {
private Long userId;
private Long locationId;
private Double latitude;
private Double longitude;
private Double accuracy;
private String deviceInfo;
}
4.4 优缺点分析
优点:
- 利用地理位置验证提高签到真实性
- 支持多地点签到和附近地点查找
- 结合了关系型数据库和Redis的优势
- 适合需要物理位置验证的场景
缺点:
- 依赖用户设备的GPS定位精度
- 可能受到GPS欺骗工具的影响
- 室内定位精度可能不足
- 系统复杂度较高
4.5 适用场景
- 企业员工考勤系统
- 外勤人员签到打卡
- 学校课堂点名
- 实地活动签到验证
- 外卖/快递配送签收系统
五、基于二维码的签到打卡系统
5.1 基本原理
二维码签到系统通过动态生成带有时间戳和签名的二维码,用户通过扫描二维码完成签到。
这种方式适合会议、课程、活动等场景,可有效防止代签,同时简化签到流程。
5.2 数据模型设计
sql
-- 签到活动表
CREATE TABLE check_in_events (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
title VARCHAR(100) NOT NULL,
description VARCHAR(500),
start_time TIMESTAMP NOT NULL,
end_time TIMESTAMP NOT NULL,
location VARCHAR(255),
organizer_id BIGINT,
qr_code_refresh_interval INT DEFAULT 60, -- 二维码刷新间隔(秒)
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
FOREIGN KEY (organizer_id) REFERENCES users(id)
);
-- 二维码签到记录表
CREATE TABLE qr_check_ins (
id BIGINT PRIMARY KEY AUTO_INCREMENT,
event_id BIGINT NOT NULL,
user_id BIGINT NOT NULL,
check_in_time TIMESTAMP NOT NULL,
qr_code_token VARCHAR(100) NOT NULL,
ip_address VARCHAR(50),
device_info VARCHAR(255),
FOREIGN KEY (event_id) REFERENCES check_in_events(id),
FOREIGN KEY (user_id) REFERENCES users(id),
UNIQUE KEY unique_event_user (event_id, user_id)
);
5.3 核心代码实现
实体类设计
kotlin
@Data
@TableName("check_in_events")
public class CheckInEvent {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
private String title;
private String description;
@TableField("start_time")
private LocalDateTime startTime;
@TableField("end_time")
private LocalDateTime endTime;
private String location;
@TableField("organizer_id")
private Long organizerId;
@TableField("qr_code_refresh_interval")
private Integer qrCodeRefreshInterval = 60; // 默认60秒
@TableField("created_at")
private LocalDateTime createdAt;
@TableField(exist = false)
private String currentQrCode;
}
@Data
@TableName("qr_check_ins")
public class QrCheckIn {
@TableId(value = "id", type = IdType.AUTO)
private Long id;
@TableField("event_id")
private Long eventId;
@TableField("user_id")
private Long userId;
@TableField("check_in_time")
private LocalDateTime checkInTime;
@TableField("qr_code_token")
private String qrCodeToken;
@TableField("ip_address")
private String ipAddress;
@TableField("device_info")
private String deviceInfo;
}
Mapper层
less
@Mapper
public interface CheckInEventMapper extends BaseMapper<CheckInEvent> {
}
@Mapper
public interface QrCheckInMapper extends BaseMapper<QrCheckIn> {
@Select("SELECT * FROM qr_check_ins WHERE event_id = #{eventId} ORDER BY check_in_time DESC")
List<QrCheckIn> findByEventIdOrderByCheckInTimeDesc(@Param("eventId") Long eventId);
@Select("SELECT * FROM qr_check_ins WHERE user_id = #{userId} ORDER BY check_in_time DESC")
List<QrCheckIn> findByUserIdOrderByCheckInTimeDesc(@Param("userId") Long userId);
@Select("SELECT COUNT(*) FROM qr_check_ins WHERE event_id = #{eventId}")
long countByEventId(@Param("eventId") Long eventId);
@Select("SELECT COUNT(*) FROM qr_check_ins WHERE event_id = #{eventId} AND user_id = #{userId}")
int existsByEventIdAndUserId(@Param("eventId") Long eventId, @Param("userId") Long userId);
}
QR码服务和校验
ini
@Service
public class QrCodeService {
@Value("${qrcode.secret:defaultSecretKey}")
private String secretKey;
@Autowired
private StringRedisTemplate redisTemplate;
/**
* 生成带签名的二维码内容
*/
public String generateQrCodeContent(Long eventId) {
long timestamp = System.currentTimeMillis();
String content = eventId + ":" + timestamp;
String signature = generateSignature(content);
// 创建完整的二维码内容
String qrCodeContent = content + ":" + signature;
// 保存到Redis,设置过期时间
String redisKey = "qrcode:event:" + eventId + ":" + timestamp;
redisTemplate.opsForValue().set(redisKey, qrCodeContent, 5, TimeUnit.MINUTES);
return qrCodeContent;
}
/**
* 验证二维码内容
*/
public boolean validateQrCode(String qrCodeContent) {
String[] parts = qrCodeContent.split(":");
if (parts.length != 3) {
return false;
}
String eventId = parts[0];
String timestamp = parts[1];
String providedSignature = parts[2];
// 验证签名
String content = eventId + ":" + timestamp;
String expectedSignature = generateSignature(content);
if (!expectedSignature.equals(providedSignature)) {
return false;
}
// 验证二维码是否在Redis中存在(防止重复使用)
String redisKey = "qrcode:event:" + eventId + ":" + timestamp;
Boolean exists = redisTemplate.hasKey(redisKey);
return exists != null && exists;
}
/**
* 生成二维码图片
*/
public byte[] generateQrCodeImage(String content, int width, int height) throws Exception {
QRCodeWriter qrCodeWriter = new QRCodeWriter();
BitMatrix bitMatrix = qrCodeWriter.encode(content, BarcodeFormat.QR_CODE, width, height);
ByteArrayOutputStream pngOutputStream = new ByteArrayOutputStream();
MatrixToImageWriter.writeToStream(bitMatrix, "PNG", pngOutputStream);
return pngOutputStream.toByteArray();
}
/**
* 生成内容签名
*/
private String generateSignature(String content) {
try {
Mac sha256_HMAC = Mac.getInstance("HmacSHA256");
SecretKeySpec secret_key = new SecretKeySpec(secretKey.getBytes(), "HmacSHA256");
sha256_HMAC.init(secret_key);
byte[] hash = sha256_HMAC.doFinal(content.getBytes());
return Base64.getEncoder().encodeToString(hash);
} catch (Exception e) {
throw new RuntimeException("Failed to generate signature", e);
}
}
}
服务层实现
scss
@Service
@Transactional
public class QrCheckInService {
@Autowired
private CheckInEventMapper eventMapper;
@Autowired
private QrCheckInMapper qrCheckInMapper;
@Autowired
private UserMapper userMapper;
@Autowired
private QrCodeService qrCodeService;
/**
* 创建签到活动
*/
public CheckInEvent createEvent(CheckInEvent event) {
event.setCreatedAt(LocalDateTime.now());
eventMapper.insert(event);
return event;
}
/**
* 获取活动信息,包括当前二维码
*/
public CheckInEvent getEventWithQrCode(Long eventId) {
CheckInEvent event = eventMapper.selectById(eventId);
if (event == null) {
throw new RuntimeException("Event not found");
}
// 检查活动是否在有效期内
LocalDateTime now = LocalDateTime.now();
if (now.isBefore(event.getStartTime()) || now.isAfter(event.getEndTime())) {
throw new RuntimeException("Event is not active");
}
// 生成当前二维码
String qrCodeContent = qrCodeService.generateQrCodeContent(eventId);
event.setCurrentQrCode(qrCodeContent);
return event;
}
/**
* 用户通过二维码签到
*/
public QrCheckIn checkIn(String qrCodeContent, Long userId, String ipAddress, String deviceInfo) {
// 验证二维码
if (!qrCodeService.validateQrCode(qrCodeContent)) {
throw new RuntimeException("Invalid QR code");
}
// 解析二维码内容
String[] parts = qrCodeContent.split(":");
Long eventId = Long.parseLong(parts[0]);
// 验证活动和用户
CheckInEvent event = eventMapper.selectById(eventId);
if (event == null) {
throw new RuntimeException("Event not found");
}
User user = userMapper.selectById(userId);
if (user == null) {
throw new RuntimeException("User not found");
}
// 检查活动是否在有效期内
LocalDateTime now = LocalDateTime.now();
if (now.isBefore(event.getStartTime()) || now.isAfter(event.getEndTime())) {
throw new RuntimeException("Event is not active");
}
// 检查用户是否已经签到
if (qrCheckInMapper.existsByEventIdAndUserId(eventId, userId) > 0) {
throw new RuntimeException("User already checked in for this event");
}
// 创建签到记录
QrCheckIn checkIn = new QrCheckIn();
checkIn.setEventId(eventId);
checkIn.setUserId(userId);
checkIn.setCheckInTime(now);
checkIn.setQrCodeToken(qrCodeContent);
checkIn.setIpAddress(ipAddress);
checkIn.setDeviceInfo(deviceInfo);
qrCheckInMapper.insert(checkIn);
return checkIn;
}
/**
* 获取活动签到列表
*/
public List<QrCheckIn> getEventCheckIns(Long eventId) {
return qrCheckInMapper.findByEventIdOrderByCheckInTimeDesc(eventId);
}
/**
* 获取用户签到历史
*/
public List<QrCheckIn> getUserCheckIns(Long userId) {
return qrCheckInMapper.findByUserIdOrderByCheckInTimeDesc(userId);
}
/**
* 获取活动签到统计
*/
public Map<String, Object> getEventStatistics(Long eventId) {
CheckInEvent event = eventMapper.selectById(eventId);
if (event == null) {
throw new RuntimeException("Event not found");
}
long totalCheckIns = qrCheckInMapper.countByEventId(eventId);
Map<String, Object> statistics = new HashMap<>();
statistics.put("eventId", eventId);
statistics.put("title", event.getTitle());
statistics.put("startTime", event.getStartTime());
statistics.put("endTime", event.getEndTime());
statistics.put("totalCheckIns", totalCheckIns);
return statistics;
}
}
控制器实现
less
@RestController
@RequestMapping("/api/qr-check-in")
public class QrCheckInController {
@Autowired
private QrCheckInService checkInService;
@Autowired
private QrCodeService qrCodeService;
@PostMapping("/events")
public ResponseEntity<CheckInEvent> createEvent(@RequestBody CheckInEvent event) {
CheckInEvent createdEvent = checkInService.createEvent(event);
return ResponseEntity.ok(createdEvent);
}
@GetMapping("/events/{eventId}")
public ResponseEntity<CheckInEvent> getEvent(@PathVariable Long eventId) {
CheckInEvent event = checkInService.getEventWithQrCode(eventId);
return ResponseEntity.ok(event);
}
@GetMapping("/events/{eventId}/qrcode")
public ResponseEntity<?> getEventQrCode(
@PathVariable Long eventId,
@RequestParam(defaultValue = "300") int width,
@RequestParam(defaultValue = "300") int height) {
try {
CheckInEvent event = checkInService.getEventWithQrCode(eventId);
byte[] qrCodeImage = qrCodeService.generateQrCodeImage(
event.getCurrentQrCode(), width, height);
return ResponseEntity.ok()
.contentType(MediaType.IMAGE_PNG)
.body(qrCodeImage);
} catch (Exception e) {
return ResponseEntity.badRequest().body(Map.of("message", e.getMessage()));
}
}
@PostMapping("/check-in")
public ResponseEntity<?> checkIn(@RequestBody QrCheckInRequest request,
HttpServletRequest httpRequest) {
try {
String ipAddress = httpRequest.getRemoteAddr();
QrCheckIn checkIn = checkInService.checkIn(
request.getQrCodeContent(),
request.getUserId(),
ipAddress,
request.getDeviceInfo()
);
return ResponseEntity.ok(checkIn);
} catch (RuntimeException e) {
return ResponseEntity.badRequest().body(Map.of("message", e.getMessage()));
}
}
@GetMapping("/events/{eventId}/check-ins")
public ResponseEntity<List<QrCheckIn>> getEventCheckIns(@PathVariable Long eventId) {
List<QrCheckIn> checkIns = checkInService.getEventCheckIns(eventId);
return ResponseEntity.ok(checkIns);
}
@GetMapping("/users/{userId}/check-ins")
public ResponseEntity<List<QrCheckIn>> getUserCheckIns(@PathVariable Long userId) {
List<QrCheckIn> checkIns = checkInService.getUserCheckIns(userId);
return ResponseEntity.ok(checkIns);
}
@GetMapping("/events/{eventId}/statistics")
public ResponseEntity<Map<String, Object>> getEventStatistics(@PathVariable Long eventId) {
Map<String, Object> statistics = checkInService.getEventStatistics(eventId);
return ResponseEntity.ok(statistics);
}
}
@Data
public class QrCheckInRequest {
private String qrCodeContent;
private Long userId;
private String deviceInfo;
}
5.4 优缺点分析
优点:
- 签到过程简单快捷,用户体验好
- 适合集中式签到场景(会议、课程等)
缺点:
- 需要组织者提前设置签到活动
- 需要现场展示二维码(投影、打印等)
- 可能出现二维码被拍照传播的风险
5.5 适用场景
- 会议、研讨会签到
- 课堂点名
- 活动入场签到
- 培训签到
- 需要现场确认的签到场景
六、各方案对比与选择指南
6.1 功能对比
功能特性 | 关系型数据库 | Redis | Bitmap | 地理位置 | 二维码 |
---|---|---|---|---|---|
实现复杂度 | 低 | 中 | 中 | 高 | 中 |
系统性能 | 中 | 高 | 极高 | 中 | 高 |
存储效率 | 中 | 高 | 极高 | 中 | 中 |
用户体验 | 中 | 高 | 高 | 中 | 高 |
开发成本 | 低 | 中 | 中 | 高 | 中 |
维护成本 | 低 | 中 | 低 | 高 | 中 |
6.2 适用场景对比
方案 | 最佳适用场景 | 不适合场景 |
---|---|---|
关系型数据库 | 中小型企业考勤、简单签到系统 | 高并发、大规模用户场景 |
Redis | 高并发社区签到、连续签到奖励 | 需要复杂查询和报表统计 |
Bitmap | 大规模用户的每日签到、连续签到统计 | 需要详细签到信息记录 |
地理位置 | 外勤人员打卡、实地活动签到 | 室内或GPS信号弱的环境 |
二维码 | 会议、课程、活动签到 | 远程办公、分散式签到 |
七、总结
在实际应用中,可以根据具体需求、用户规模、安全要求和预算等因素选择最合适的方案,也可以将多种方案结合使用,构建更加完善的签到打卡系统。