redis之bitmap

九转成圣

发布于 2024-04-10 16:58:42

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代码可运行

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代码可运行

redis之bitmap

redis在线网址

https://try.redis.io/

二值统计:只有两个数的统计,要么0要么1

bitmap底层也是动态字符串(不需要初始化字符串,就可以往字符串里面存,如果不存在就创建,若果空间不足则扩容)

private void setBit() {
    // 初始化了一个9字节的字符串吗? 没有
    bitmapStatsService.setBit(USER_MONTH_SIGN, 3, true);
    bitmapStatsService.setBit(USER_MONTH_SIGN, 6, true);
    bitmapStatsService.setBit(USER_MONTH_SIGN, 9, true);
    redisTemplate.expire(USER_MONTH_SIGN, 1, TimeUnit.DAYS);
}

bitmap相关API

SETBIT key offset value
summary: Sets or clears the bit at offset in the string value stored at key
since: 2.2.0

GETBIT key offset
summary: Returns the bit value at offset in the string value stored at key
since: 2.2.0

BITCOUNT key [start end]
summary: Count set bits in a string
since: 2.6.0

BITFIELD key [GET type offset] [SET type offset value] [INCRBY type offset increment] [OVERFLOW WRAP|SAT|FAIL]
summary: Perform arbitrary bitfield integer operations on strings
since: 3.2.0

BITOP operation destkey key [key ...]
summary: Perform bitwise operations between strings
since: 2.6.0

BITPOS key bit [start] [end]
summary: Find first bit set or clear in a string
since: 2.8.7

RedisTemplate操作bitmap

@Component
public class BitmapService {
    @Autowired
    private RedisTemplate<String, String> redisTemplate;


    // 设置指定位置的位值
    public void setBit(String key, long offset, boolean value) {
        redisTemplate.opsForValue().setBit(key, offset, value);
    }

    // 获取指定位置的位值
    public Boolean getBit(String key, long offset) {
        return redisTemplate.opsForValue().getBit(key, offset);
    }

    // 统计指定范围内的位值为 true 的个数
    public Long bitCount(String key) {
        return redisTemplate.execute((RedisCallback<Long>) connection -> connection.bitCount(key.getBytes()));
    }

    public Long bitCount(String key, long start, long end) {
        return redisTemplate.execute((RedisCallback<Long>) connection -> connection.bitCount(key.getBytes(), start, end));
    }

    // 首签时间
    public Long bitPos(String key, boolean bit) {
        return redisTemplate.execute((RedisCallback<Long>) connection -> connection.bitPos(key.getBytes(), bit));
    }

    public Long bitPos(String key, boolean bit, Long start, Long end) {
        Range<Long> range = Range.closed(start, end);
        return redisTemplate.execute((RedisCallback<Long>) connection -> connection.bitPos(key.getBytes(), bit, range));
    }

    // 连续签到/累计签到
    public Long bitOp(RedisStringCommands.BitOperation op, String destination, String... keys) {
        byte[][] keyBytes = new byte[keys.length][];
        for (int i = 0; i < keys.length; i++) {
            keyBytes[i] = keys[i].getBytes();
        }
        return redisTemplate.execute((RedisCallback<Long>) connection -> connection.bitOp(op, destination.getBytes(), keyBytes));
    }
}

测试

@Slf4j
@RestController
public class HelloBitMapController {
    @Autowired
    private BitmapService bitmapStatsService;
    @Autowired
    private RedisTemplate<String, String> redisTemplate;
    private static final String USER_MONTH_SIGN = "sign:uid:month:1:202306";
    private static final String weekSignAndKey = "week:sign:and";
    private static final String weekSignOrKey = "week:sign:or";

    @RequestMapping("/helloBitmap")
    public void helloBitmap() {
        setBit();
        getBit();
        bitCount();
        bitPos();
    }

    // 首签 累计签到 连续签到
    private void setBit() {
        bitmapStatsService.setBit(USER_MONTH_SIGN, 3, true);
        bitmapStatsService.setBit(USER_MONTH_SIGN, 6, true);
        bitmapStatsService.setBit(USER_MONTH_SIGN, 9, true);
        redisTemplate.expire(USER_MONTH_SIGN, 1, TimeUnit.DAYS);
    }


    private void getBit() {
        // 可不初始化(string) 不一定非要从0开始,可以用1代表1号
        Boolean bit3 = bitmapStatsService.getBit(USER_MONTH_SIGN, 3);
        log.info("3号签到情况:{}", bit3);
        Boolean bit6 = bitmapStatsService.getBit(USER_MONTH_SIGN, 6);
        log.info("6号签到情况:{}", bit6);
        Boolean bit9 = bitmapStatsService.getBit(USER_MONTH_SIGN, 9);
        log.info("9号签到情况:{}", bit9);
    }

    private void bitCount() {
        Long count = bitmapStatsService.bitCount(USER_MONTH_SIGN);
        log.info("累计签到{}天", count != null ? count : 0L);
    }


    private void bitPos() {
        Long pos = bitmapStatsService.bitPos(USER_MONTH_SIGN, true);
        log.info("首签{}号", pos);
    }

    // 不用bitOp也能实现统计(bitCount,感觉还要简单一些,至于那个更合适有待进一步思考)
    @RequestMapping("/bitOp")
    public void bitOp() {
        // 1号用户7天全签到
        weekSign(1, true);
        // 2号用户周一没有签到
        weekSign(2, true);
        bitmapStatsService.setBit("week:sign:1", 2, false);
        // 3号用户只有周1签到
        bitmapStatsService.setBit("week:sign:1", 3, true);
        // 输出签到结果
        show();
        // 统计结果
        bitOpAnd();
        bitOpOr();
    }

    private void show() {
        int[] userIds = {1, 2, 3};
        List<StringBuilder> list = new ArrayList<>();
        for (String s : getWeekSignKey()) {
            StringBuilder sb = new StringBuilder();
            for (int userId : userIds) {
                Boolean bit = bitmapStatsService.getBit(s, userId);
                sb.append(bit ? "1\t" : "0\t");
            }
            list.add(sb);
        }
        for (StringBuilder sb : list) {
            System.out.println(sb);
        }
        System.out.println("----------------------");
        StringBuilder and = new StringBuilder();
        for (int userId : userIds) {
            Boolean bit = bitmapStatsService.getBit(weekSignAndKey, userId);
            and.append(bit ? "1\t" : "0\t");
        }
        System.out.println(and);
        System.out.println("----------------------");
        StringBuilder or = new StringBuilder();
        for (int userId : userIds) {
            Boolean bit = bitmapStatsService.getBit(weekSignOrKey, userId);
            or.append(bit ? "1\t" : "0\t");
        }
        System.out.println(or);
        for (int userId : userIds) {
            allSign(userId);
            anySign(userId);
        }
    }

    public String[] getWeekSignKey() {
        String[] keys = new String[7];
        // 按天记录 week:sign:1 周一签到情况,week:sign:2 周二签到情况...
        String userSignKey = "week:sign:${week}";
        for (int i = 1; i <= 7; i++) {
            String key = userSignKey.replace("${week}", String.valueOf(i));
            keys[i - 1] = key;
        }
        System.out.println(Arrays.toString(keys));
        return keys;
    }

    public void weekSign(int userId, boolean value) {
        String[] keys = getWeekSignKey();
        for (String key : keys) {
            System.out.println(key);
            bitmapStatsService.setBit(key, userId, value);
            redisTemplate.expire(key, 1, TimeUnit.DAYS);
        }
    }

    private void bitOpAnd() {
        // 周签统计结果
        bitmapStatsService.bitOp(RedisStringCommands.BitOperation.AND, weekSignAndKey, getWeekSignKey());
    }

    private void bitOpOr() {
        // 周签统计结果
        bitmapStatsService.bitOp(RedisStringCommands.BitOperation.OR, weekSignOrKey, getWeekSignKey());
    }

    private void allSign(int userId) {
        Boolean bit = bitmapStatsService.getBit(weekSignAndKey, userId);
        log.info("用户{}是否7天有签到过:{}", userId, bit);
        redisTemplate.expire(weekSignAndKey, 1, TimeUnit.DAYS);
    }

    private void anySign(int userId) {
        Boolean bit = bitmapStatsService.getBit(weekSignOrKey, userId);
        log.info("用户{}是否7天都签到过:{}", userId, bit);
        redisTemplate.expire(weekSignOrKey, 1, TimeUnit.DAYS);
    }
}

redis命令操作bitmap

海量用户登录状态的保存

保存5000万用户的登录状态(大概需要50000000/8/1024/1024≈6M)

setbit login_status 10086 1

判断是否登录

getbit login_status 10086

退出

setbit login_status 10086 0

用户签到以及统计

签到

setbit uid:sign:10086:202306 5 1

统计月签次数

bitcount uid:sign:10086:202306

查看首签时间

bitpos uid:sign:10086:202306 1

连续7天登录用户统计

setbit uid:sign:1 10086 1
setbit uid:sign:2 10086 1
setbit uid:sign:3 10086 1
setbit uid:sign:4 10086 1
setbit uid:sign:5 10086 1
setbit uid:sign:6 10086 1
setbit uid:sign:7 10086 1
# BITOP operation destkey key [key ...]
# opration 可以是 and、OR、NOT、XOR
# 7天连续登录
bitop and uid:sign:r uid:sign:1 uid:sign:2 uid:sign:3...
# 7天内有登录过
bitop or uid:sign:r uid:sign:1 uid:sign:2 uid:sign:3...

优点

节省空间
效率高setbit和getbit的时间复杂度都是O(1)，其他位运算效率也高

缺点

本质上位只有0和1的区别，所以一般只能用于状态记录
对于需要统计的key的数量不大，但key与key之前跨度较大的场景不适用比如要存入(10,8887983,93452134)这三个数据，我们需要建立一个 99999999 长度的 BitMap ，但是实际上只存了3个数据，这时候就有很大的空间浪费，碰到这种问题的话，可以通过引入 Roaring BitMap 来解决。