Implementing Sign‑in and Statistics with Redis BitMap in Spring Boot

In many projects a sign‑in and statistics feature is needed; using Redis BitMap can store user sign‑in data with minimal memory. The article first introduces the basic Redis BitMap syntax and commands such as SETBIT , GETBIT , BITCOUNT , BITFIELD , BITOP , and BITPOS .

It then shows how to integrate Redis BitMap into a Spring Boot application. The Redis server version used is 6.2, and the following commands are demonstrated with screenshots: creating a key, setting bits, getting bits, using BITFIELD for unsigned queries, and locating the first 0/1 with BITPOS .

Core source code for the sign‑in API is provided:

@PostMapping("sign")
public Result sign() {
    return userService.sign();
}

The service implementation obtains the logged‑in user ID, builds a key based on year and month, determines the day of month, and writes a 1 to the corresponding bit:

public Result sign() {
    Long userId = UserHolder.getUser().getId();
    LocalDateTime now = LocalDateTime.now();
    String keySuffix = now.format(DateTimeFormatter.ofPattern(":yyyyMM"));
    String key = RedisConstants.USER_SIGN_KEY + userId + keySuffix;
    int dayOfMonth = now.getDayOfMonth();
    stringRedisTemplate.opsForValue().setBit(key, dayOfMonth - 1, true);
    return Result.ok();
}

For statistics, the article explains how to calculate continuous sign‑in days by retrieving the month’s BitMap as a decimal number with BITFIELD and iterating bit‑by‑bit using bitwise operations:

public Result signCount() {
    Long userId = UserHolder.getUser().getId();
    LocalDateTime now = LocalDateTime.now();
    String keySuffix = now.format(DateTimeFormatter.ofPattern(":yyyyMM"));
    String key = RedisConstants.USER_SIGN_KEY + userId + keySuffix;
    int dayOfMonth = now.getDayOfMonth();
    List
result = stringRedisTemplate.opsForValue().bitField(
        key,
        BitFieldSubCommands.create()
            .get(BitFieldSubCommands.BitFieldType.unsigned(dayOfMonth)).valueAt(0));
    if (result == null || result.isEmpty() || result.get(0) == null) {
        return Result.ok(0);
    }
    long num = result.get(0);
    int count = 0;
    while (true) {
        if ((num & 1) == 0) {
            break;
        } else {
            count++;
        }
        num >>>= 1;
    }
    return Result.ok(count);
}

The article also discusses using BitMap to mitigate cache‑penetration attacks by hashing large ID spaces into a bitmap, reducing memory compared to storing IDs in a list, and notes the importance of handling false‑positive rates.

Finally, a brief summary emphasizes that Redis BitMap provides a lightweight, high‑performance solution for sign‑in and statistical features in microservices, improving user engagement while keeping memory usage low.