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

1. Redis BitMap Basic Usage

BitMap Syntax and Commands

The article first compares a traditional MySQL table for storing sign‑in records with the memory‑efficient Redis BitMap approach, highlighting that each sign‑in can be represented by a single bit, reducing storage to a few bytes per user.

SETBIT : Set a bit at a given offset to 0 or 1.

GETBIT : Retrieve the bit value at a given offset.

BITCOUNT : Count the number of bits set to 1.

BITFIELD : Query, modify or increment values in a bit array.

BITFIELD_RO : Read bit array values in decimal.

BITOP : Perform bitwise operations (AND, OR, XOR) on multiple BitMaps.

BITPOS : Find the first occurrence of 0 or 1 within a range.

Implementing the Feature with BitMap

Using Redis 6.2, the article demonstrates the SETBIT, GETBIT, BITFIELD and BITPOS commands through screenshots, showing how to create a key, set a sign‑in bit, query its state, and retrieve bit fields.

2. Spring Boot Integration with Redis for Sign‑in

Requirement

Provide an API that records the current user's daily sign‑in status in Redis using a BitMap.

Design

The year‑month string is used as part of the Redis key, and the day of month determines the bit offset; setting the bit to 1 marks a successful sign‑in.

Core Source Code

UserController

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

UserServiceImpl

public Result sign() {
    // 1. Get logged‑in user
    Long userId = UserHolder.getUser().getId();
    // 2. Current date
    LocalDateTime now = LocalDateTime.now();
    // 3. Build key
    String keySuffix = now.format(DateTimeFormatter.ofPattern(":yyyyMM"));
    String key = RedisConstants.USER_SIGN_KEY + userId + keySuffix;
    // 4. Day of month
    int dayOfMonth = now.getDayOfMonth();
    // 5. Set bit to 1
    stringRedisTemplate.opsForValue().setBit(key, dayOfMonth - 1, true);
    return Result.ok();
}

Testing

ApiFox is used to invoke the sign‑in endpoint, and Redis data is inspected to verify the bit has been set.

3. Sign‑in Statistics

Problem 1: Consecutive Sign‑in Days

The algorithm retrieves the last sign‑in of the current month and walks backwards until the first zero bit is encountered, counting the number of consecutive ones.

Problem 2: Retrieve All Sign‑in Data for the Current Month

BITFIELD key GET u[dayOfMonth] 0

This command returns a decimal number representing the bits for the days up to today; counting the number of 1 bits yields the total sign‑ins.

Problem 3: Iterate Bits Backwards

By repeatedly performing a bitwise AND with 1 and right‑shifting the number, each bit can be examined from the least‑significant side.

Core Source Code for Statistics

UserController

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

UserServiceImpl

public Result signCount() {
    // 1. Get user
    Long userId = UserHolder.getUser().getId();
    // 2. Current date
    LocalDateTime now = LocalDateTime.now();
    // 3. Build key
    String keySuffix = now.format(DateTimeFormatter.ofPattern(":yyyyMM"));
    String key = RedisConstants.USER_SIGN_KEY + userId + keySuffix;
    // 4. Day of month
    int dayOfMonth = now.getDayOfMonth();
    // 5. Get bitmap as decimal
    List
result = stringRedisTemplate.opsForValue().bitField(
        key,
        BitFieldSubCommands.create()
            .get(BitFieldSubCommands.BitFieldType.unsigned(dayOfMonth)).valueAt(0));
    if (result == null || result.isEmpty()) {
        return Result.ok(0);
    }
    Long num = result.get(0);
    if (num == null || num == 0) {
        return Result.ok(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

The article proposes storing hashed IDs in a large BitMap instead of a list, allowing constant‑time existence checks while accepting a configurable false‑positive rate.

Conclusion

Redis BitMap combined with Spring Boot provides a lightweight, memory‑efficient solution for user sign‑in tracking and statistical analysis, and can also be leveraged to address cache‑penetration problems.