Build a Memory-Efficient Sign-In System with Redis BitMap and Spring Boot

Introduction

Many projects need a sign-in and statistics feature; using Redis BitMap can store daily sign-in flags with minimal memory.

1. Redis BitMap Basics

Key commands

SETBIT – set a bit at a given offset

GETBIT – get the bit value at an offset

BITCOUNT – count bits set to 1

BITFIELD – read or modify arbitrary bit fields

BITFIELD_RO – read bit fields as unsigned integers

BITOP – perform bitwise operations on multiple BitMaps

BITPOS – find first occurrence of 0 or 1

Using a BitMap, each user's daily sign-in can be represented by a single bit; 31 days fit into 2 bytes, dramatically reducing memory compared with a relational table.

2. Spring Boot Integration – Sign-In API

Requirement

Store the current user's sign-in status for the day in Redis.

Key design: sign:{userId}:{yyyyMM}, where each bit corresponds to a day of the month.

Core source code

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

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();
}

3. Sign-In Statistics – Continuous Days

Problem: How to calculate consecutive sign-in days?

Retrieve the month's BitMap as an unsigned integer, then iterate from the current day backward, counting consecutive 1 bits until a 0 is encountered.

Core source code

@GetMapping("/signCount")
public Result signCount() {
    return userService.signCount();
}

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<Long> 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);
}

4. Using BitMap to Mitigate Cache Penetration

Instead of storing a large list of existing IDs, a BitMap can represent the presence of an ID with a single bit calculated by id % bitmapSize. This reduces memory usage but introduces a false‑positive rate due to hash collisions, which must be considered.

Conclusion

Combining Spring Boot with Redis BitMap provides an efficient way to implement sign-in and statistical features, saving memory and enabling quick queries for daily activity and continuous sign-in streaks.