引言
排行榜是现代应用程序中常见的功能,无论是游戏积分榜、销售排行还是用户活跃度统计,都需要高效的排序和查询机制。Redis的有序集合(Sorted Set)数据结构为实现排行榜提供了完美的解决方案,它能够自动维护元素的排序,并支持高效的范围查询和排名操作。
Redis Sorted Set简介
Redis的有序集合(Sorted Set)是一种特殊的数据结构,它具有以下特点:
-
唯一性:集合中的每个元素都是唯一的
-
有序性:每个元素都关联一个分数(score),Redis根据分数自动排序
-
高效性:插入、删除、查找操作的时间复杂度都是O(log N)
-
范围查询:支持按分数范围或排名范围查询元素
环境准备
Maven依赖
首先,在项目的pom.xml中添加必要的依赖:
<dependencies>
<!-- Jedis Redis客户端 -->
<dependency>
<groupId>redis.clients</groupId>
<artifactId>jedis</artifactId>
<version>4.3.1</version>
</dependency>
<!-- Spring Boot Redis Starter (可选) -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
<version>2.7.0</version>
</dependency>
<!-- JSON处理 -->
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>2.14.2</version>
</dependency>
</dependencies>
Redis配置
创建Redis连接配置类:
@Configuration
public class RedisConfig {
@Bean
public JedisConnectionFactory jedisConnectionFactory() {
JedisConnectionFactory factory = new JedisConnectionFactory();
factory.setHostName("localhost");
factory.setPort(6379);
factory.setDatabase(0);
return factory;
}
@Bean
public RedisTemplate<String, Object> redisTemplate() {
RedisTemplate<String, Object> template = new RedisTemplate<>();
template.setConnectionFactory(jedisConnectionFactory());
template.setDefaultSerializer(new GenericJackson2JsonRedisSerializer());
template.setKeySerializer(new StringRedisSerializer());
template.setHashKeySerializer(new StringRedisSerializer());
return template;
}
}
核心实现
1. 排行榜服务类
@Service
public class LeaderboardService {
@Autowired
private RedisTemplate<String, Object> redisTemplate;
private static final String LEADERBOARD_KEY = "game:leaderboard";
/**
* 更新用户分数
* @param userId 用户ID
* @param score 分数
*/
public void updateScore(String userId, double score) {
redisTemplate.opsForZSet().add(LEADERBOARD_KEY, userId, score);
}
/**
* 增加用户分数
* @param userId 用户ID
* @param increment 增加的分数
* @return 更新后的总分数
*/
public Double incrementScore(String userId, double increment) {
return redisTemplate.opsForZSet().incrementScore(LEADERBOARD_KEY, userId, increment);
}
/**
* 获取用户当前分数
* @param userId 用户ID
* @return 用户分数
*/
public Double getUserScore(String userId) {
return redisTemplate.opsForZSet().score(LEADERBOARD_KEY, userId);
}
/**
* 获取用户排名(从1开始)
* @param userId 用户ID
* @return 用户排名,如果用户不存在返回null
*/
public Long getUserRank(String userId) {
Long rank = redisTemplate.opsForZSet().reverseRank(LEADERBOARD_KEY, userId);
return rank != null ? rank + 1 : null;
}
/**
* 获取前N名排行榜
* @param topN 获取前几名
* @return 排行榜列表
*/
public List<LeaderboardEntry> getTopN(int topN) {
Set<ZSetOperations.TypedTuple<Object>> tuples =
redisTemplate.opsForZSet().reverseRangeWithScores(LEADERBOARD_KEY, 0, topN - 1);
List<LeaderboardEntry> leaderboard = new ArrayList<>();
int rank = 1;
for (ZSetOperations.TypedTuple<Object> tuple : tuples) {
LeaderboardEntry entry = new LeaderboardEntry();
entry.setUserId((String) tuple.getValue());
entry.setScore(tuple.getScore());
entry.setRank(rank++);
leaderboard.add(entry);
}
return leaderboard;
}
/**
* 获取指定排名范围的排行榜
* @param startRank 起始排名(从1开始)
* @param endRank 结束排名(包含)
* @return 排行榜列表
*/
public List<LeaderboardEntry> getRangeByRank(int startRank, int endRank) {
Set<ZSetOperations.TypedTuple<Object>> tuples =
redisTemplate.opsForZSet().reverseRangeWithScores(
LEADERBOARD_KEY, startRank - 1, endRank - 1);
List<LeaderboardEntry> leaderboard = new ArrayList<>();
int rank = startRank;
for (ZSetOperations.TypedTuple<Object> tuple : tuples) {
LeaderboardEntry entry = new LeaderboardEntry();
entry.setUserId((String) tuple.getValue());
entry.setScore(tuple.getScore());
entry.setRank(rank++);
leaderboard.add(entry);
}
return leaderboard;
}
/**
* 获取指定分数范围的用户
* @param minScore 最小分数
* @param maxScore 最大分数
* @return 用户列表
*/
public List<LeaderboardEntry> getRangeByScore(double minScore, double maxScore) {
Set<ZSetOperations.TypedTuple<Object>> tuples =
redisTemplate.opsForZSet().reverseRangeByScoreWithScores(
LEADERBOARD_KEY, minScore, maxScore);
List<LeaderboardEntry> result = new ArrayList<>();
for (ZSetOperations.TypedTuple<Object> tuple : tuples) {
LeaderboardEntry entry = new LeaderboardEntry();
entry.setUserId((String) tuple.getValue());
entry.setScore(tuple.getScore());
// 获取具体排名
Long rank = redisTemplate.opsForZSet().reverseRank(LEADERBOARD_KEY, tuple.getValue());
entry.setRank(rank != null ? rank.intValue() + 1 : 0);
result.add(entry);
}
return result;
}
/**
* 获取排行榜总人数
* @return 总人数
*/
public Long getTotalCount() {
return redisTemplate.opsForZSet().zCard(LEADERBOARD_KEY);
}
/**
* 删除用户
* @param userId 用户ID
* @return 是否删除成功
*/
public Boolean removeUser(String userId) {
Long removed = redisTemplate.opsForZSet().remove(LEADERBOARD_KEY, userId);
return removed != null && removed > 0;
}
}
2. 排行榜条目实体类
public class LeaderboardEntry {
private String userId;
private Double score;
private Integer rank;
// 构造函数
public LeaderboardEntry() {}
public LeaderboardEntry(String userId, Double score, Integer rank) {
this.userId = userId;
this.score = score;
this.rank = rank;
}
// Getter和Setter方法
public String getUserId() { return userId; }
public void setUserId(String userId) { this.userId = userId; }
public Double getScore() { return score; }
public void setScore(Double score) { this.score = score; }
public Integer getRank() { return rank; }
public void setRank(Integer rank) { this.rank = rank; }
@Override
public String toString() {
return String.format("LeaderboardEntry{userId='%s', score=%.2f, rank=%d}",
userId, score, rank);
}
}
3. REST API控制器
@RestController
@RequestMapping("/api/leaderboard")
public class LeaderboardController {
@Autowired
private LeaderboardService leaderboardService;
/**
* 更新用户分数
*/
@PostMapping("/score")
public ResponseEntity<String> updateScore(@RequestBody ScoreUpdateRequest request) {
leaderboardService.updateScore(request.getUserId(), request.getScore());
return ResponseEntity.ok("Score updated successfully");
}
/**
* 增加用户分数
*/
@PostMapping("/increment")
public ResponseEntity<Double> incrementScore(@RequestBody ScoreIncrementRequest request) {
Double newScore = leaderboardService.incrementScore(request.getUserId(), request.getIncrement());
return ResponseEntity.ok(newScore);
}
/**
* 获取用户排名和分数
*/
@GetMapping("/user/{userId}")
public ResponseEntity<UserRankInfo> getUserInfo(@PathVariable String userId) {
Double score = leaderboardService.getUserScore(userId);
Long rank = leaderboardService.getUserRank(userId);
if (score == null) {
return ResponseEntity.notFound().build();
}
UserRankInfo info = new UserRankInfo(userId, score, rank);
return ResponseEntity.ok(info);
}
/**
* 获取前N名排行榜
*/
@GetMapping("/top/{n}")
public ResponseEntity<List<LeaderboardEntry>> getTopN(@PathVariable int n) {
List<LeaderboardEntry> leaderboard = leaderboardService.getTopN(n);
return ResponseEntity.ok(leaderboard);
}
/**
* 获取指定排名范围的排行榜
*/
@GetMapping("/range")
public ResponseEntity<List<LeaderboardEntry>> getRangeByRank(
@RequestParam int startRank,
@RequestParam int endRank) {
List<LeaderboardEntry> leaderboard = leaderboardService.getRangeByRank(startRank, endRank);
return ResponseEntity.ok(leaderboard);
}
/**
* 获取排行榜统计信息
*/
@GetMapping("/stats")
public ResponseEntity<LeaderboardStats> getStats() {
Long totalCount = leaderboardService.getTotalCount();
List<LeaderboardEntry> topUsers = leaderboardService.getTopN(1);
LeaderboardStats stats = new LeaderboardStats();
stats.setTotalUsers(totalCount);
if (!topUsers.isEmpty()) {
stats.setTopUser(topUsers.get(0));
}
return ResponseEntity.ok(stats);
}
}
高级功能
1. 多个排行榜管理
@Service
public class MultiLeaderboardService {
@Autowired
private RedisTemplate<String, Object> redisTemplate;
private static final String LEADERBOARD_PREFIX = "leaderboard:";
/**
* 获取排行榜键名
*/
private String getLeaderboardKey(String leaderboardType) {
return LEADERBOARD_PREFIX + leaderboardType;
}
/**
* 更新指定排行榜中用户分数
*/
public void updateScore(String leaderboardType, String userId, double score) {
String key = getLeaderboardKey(leaderboardType);
redisTemplate.opsForZSet().add(key, userId, score);
}
/**
* 获取用户在多个排行榜中的排名
*/
public Map<String, UserRankInfo> getUserRanksInMultipleBoards(String userId, List<String> leaderboardTypes) {
Map<String, UserRankInfo> results = new HashMap<>();
for (String type : leaderboardTypes) {
String key = getLeaderboardKey(type);
Double score = redisTemplate.opsForZSet().score(key, userId);
Long rank = redisTemplate.opsForZSet().reverseRank(key, userId);
if (score != null && rank != null) {
results.put(type, new UserRankInfo(userId, score, rank + 1));
}
}
return results;
}
}
2. 时间窗口排行榜
@Service
public class TimeWindowLeaderboardService {
@Autowired
private RedisTemplate<String, Object> redisTemplate;
/**
* 获取日排行榜键名
*/
private String getDailyLeaderboardKey() {
String today = LocalDate.now().format(DateTimeFormatter.ofPattern("yyyy-MM-dd"));
return "leaderboard:daily:" + today;
}
/**
* 获取周排行榜键名
*/
private String getWeeklyLeaderboardKey() {
LocalDate now = LocalDate.now();
int weekOfYear = now.get(WeekFields.ISO.weekOfYear());
return String.format("leaderboard:weekly:%d-%02d", now.getYear(), weekOfYear);
}
/**
* 更新日排行榜和总排行榜
*/
public void updateDailyScore(String userId, double score) {
String dailyKey = getDailyLeaderboardKey();
String totalKey = "leaderboard:total";
// 使用Redis事务确保一致性
redisTemplate.execute(new SessionCallback<Object>() {
@Override
public Object execute(RedisOperations operations) throws DataAccessException {
operations.multi();
operations.opsForZSet().add(dailyKey, userId, score);
operations.opsForZSet().incrementScore(totalKey, userId, score);
return operations.exec();
}
});
// 设置日排行榜过期时间(7天)
redisTemplate.expire(dailyKey, 7, TimeUnit.DAYS);
}
}
3. 排行榜缓存优化
@Service
public class CachedLeaderboardService {
@Autowired
private RedisTemplate<String, Object> redisTemplate;
private static final String CACHE_KEY_PREFIX = "cache:leaderboard:";
private static final int CACHE_EXPIRE_SECONDS = 300; // 5分钟缓存
/**
* 获取缓存的前N名排行榜
*/
@Cacheable(value = "leaderboard", key = "'top:' + #topN")
public List<LeaderboardEntry> getCachedTopN(int topN) {
String cacheKey = CACHE_KEY_PREFIX + "top:" + topN;
// 尝试从缓存获取
List<LeaderboardEntry> cached = (List<LeaderboardEntry>)
redisTemplate.opsForValue().get(cacheKey);
if (cached != null) {
return cached;
}
// 缓存未命中,从排行榜获取
List<LeaderboardEntry> leaderboard = getTopN(topN);
// 存入缓存
redisTemplate.opsForValue().set(cacheKey, leaderboard,
CACHE_EXPIRE_SECONDS, TimeUnit.SECONDS);
return leaderboard;
}
/**
* 清除相关缓存
*/
public void clearLeaderboardCache() {
Set<String> keys = redisTemplate.keys(CACHE_KEY_PREFIX + "*");
if (keys != null && !keys.isEmpty()) {
redisTemplate.delete(keys);
}
}
}
性能优化建议
1. 批量操作
对于大量的分数更新操作,建议使用批量处理:
public void batchUpdateScores(Map<String, Double> userScores) {
redisTemplate.executePipelined(new SessionCallback<Object>() {
@Override
public Object execute(RedisOperations operations) throws DataAccessException {
ZSetOperations<String, Object> zSetOps = operations.opsForZSet();
userScores.forEach((userId, score) -> {
zSetOps.add(LEADERBOARD_KEY, userId, score);
});
return null;
}
});
}
2. 连接池配置
优化Redis连接池配置以提升性能:
@Configuration
public class RedisPoolConfig {
@Bean
public JedisConnectionFactory jedisConnectionFactory() {
JedisPoolConfig poolConfig = new JedisPoolConfig();
poolConfig.setMaxTotal(50);
poolConfig.setMaxIdle(20);
poolConfig.setMinIdle(10);
poolConfig.setTestOnBorrow(true);
poolConfig.setTestOnReturn(true);
JedisConnectionFactory factory = new JedisConnectionFactory(poolConfig);
factory.setHostName("localhost");
factory.setPort(6379);
factory.setTimeout(3000);
return factory;
}
}
测试示例
@SpringBootTest
public class LeaderboardServiceTest {
@Autowired
private LeaderboardService leaderboardService;
@Test
public void testLeaderboard() {
// 添加测试数据
leaderboardService.updateScore("user1", 1000);
leaderboardService.updateScore("user2", 1500);
leaderboardService.updateScore("user3", 800);
leaderboardService.updateScore("user4", 1200);
// 测试获取前3名
List<LeaderboardEntry> top3 = leaderboardService.getTopN(3);
assertEquals(3, top3.size());
assertEquals("user2", top3.get(0).getUserId());
assertEquals(1500.0, top3.get(0).getScore(), 0.01);
// 测试用户排名
Long rank = leaderboardService.getUserRank("user2");
assertEquals(Long.valueOf(1), rank);
// 测试分数增加
Double newScore = leaderboardService.incrementScore("user1", 600);
assertEquals(1600.0, newScore, 0.01);
// 验证排名变化
Long newRank = leaderboardService.getUserRank("user1");
assertEquals(Long.valueOf(1), newRank);
}
}
总结
使用Redis实现排行榜功能具有以下优势:
-
高性能:Redis的内存数据库特性保证了快速的读写操作
-
自动排序:Sorted Set自动维护元素排序,无需额外的排序操作
-
丰富的操作:支持范围查询、排名查询、分数更新等多种操作
-
扩展性强:可以轻松实现多种类型的排行榜和时间窗口排行榜
通过合理的缓存策略和批量操作优化,Redis排行榜系统可以轻松应对高并发场景,为用户提供实时、准确的排名服务。在实际项目中,还可以根据具体需求添加更多功能,如排行榜历史记录、用户分组排行等。