Redis特殊类型数据结构Bitmap、HyperLogLog、GEO的使用及场景分析

> SETBIT sign 5 1
0
> SETBIT sign 3 1
0
> GETBIT sign 0
0
> GETBIT sign 3
1
> BITCOUNT sign 0 5
2
> BITPOS sign 1 0 5
3
> GETBIT sign 3
1
> SETBIT sign1 3 1
0
> SETBIT sign1 4 1
0
> BITOP AND sign2 sign sign1
1
> GETBIT sign2 3
1
> GETBIT sign2 4
0
> GETBIT sign2 5
0
> BITOP OR sign3 sign sign1
1
> GETBIT sign3 4
1

> PFADD chars a b c d e
1
> PFADD chars f g
1
> PFCOUNT chars
7
> PFADD nums 1 2 3
1
> PFCOUNT chars nums
10
> PFMERGE destination chars nums
OK
> PFCOUNT destination
10

> GEOADD location 116.33 39.89 user1 116.34 39.90 user2 116.35 39.88 user3 119.35 41.22 user4
3
> GEOPOS location user1
116.3299986720085144
39.89000061669732844
> GEODIST location user1 user2 km
1.4018
> GEODIST location user1 user4 km
294.9606
> GEORADIUS location 116.33 39.87 3 km
user3
user1
> GEORADIUS location 116.33 39.87 5 km
user3
user1
user2
> GEORADIUSBYMEMBER location user1 3 km
user3
user1
user2
> GEORADIUSBYMEMBER location user1 2 km
user1
user2

package com.eckey.lab.service.util;
import com.alibaba.fastjson.JSON;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.data.redis.connection.RedisConnection;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.data.redis.core.ZSetOperations;
import org.springframework.data.redis.core.types.RedisClientInfo;
import org.springframework.stereotype.Component;
import javax.annotation.Resource;
import java.nio.charset.StandardCharsets;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.TimeUnit;
@Component
public class RedisUtil {
    private static final Logger LOG = LoggerFactory.getLogger(RedisUtil.class);
    @Resource
    private RedisTemplate<String, Object> redisTemplate;
    @Resource(name = "strRedisTemplate")
    private RedisTemplate<String, String> stringRedisTemplate;
	 /**
	     * 创建布隆过滤器
	     *
	     * @param size          位数组大小
	     * @param hashFunctions 哈希函数数量
	     * @param value         元素值
	     */
    private List<Long> getHashPositions(String value, int hashFunctions, int size) {
        List<Long> positions = new ArrayList<>(hashFunctions);
        try {
            MessageDigest md = MessageDigest.getInstance("MD5");
            byte[] bytes = md.digest(value.getBytes(StandardCharsets.UTF_8));
            // 使用同一个MD5值生成多个哈希位置
            for (int i = 0; i < hashFunctions; i++) {
                long hashValue = 0;
                for (int j = i * 4; j < i * 4 + 4; j++) {
                    hashValue <<= 8;
                    int index = j % bytes.length;
                    hashValue |= (bytes[index] & 0xFF);
                }
                positions.add(Math.abs(hashValue % size));
            }
        } catch (NoSuchAlgorithmException e) {
            throw new RuntimeException("MD5 algorithm not found", e);
        }
        return positions;
    }
    public void bloomFilterAdd(String key, String value, int hashFunctions, int size) {
        for (long position : getHashPositions(value, hashFunctions, size)) {
            stringRedisTemplate.opsForValue().setBit(key, position, true);
        }
    }
    public boolean bloomFilterContains(String key, String value, int hashFunctions, int size) {
        for (long position : getHashPositions(value, hashFunctions, size)) {
            if (Boolean.FALSE.equals(stringRedisTemplate.opsForValue().getBit(key, position))) {
                return false;
            }
        }
        return true;
    }
    public void hyperAdd(String key, String value) {
        stringRedisTemplate.opsForHyperLogLog().add(key, value);
    }
    public void hyperAdd(String key, String... values) {
        stringRedisTemplate.opsForHyperLogLog().add(key, values);
    }
    public Long hyperSize(String key) {
        return stringRedisTemplate.opsForHyperLogLog().size(key);
    }
    public void hyperDel(String key) {
        stringRedisTemplate.opsForHyperLogLog().delete(key);
    }
    public Long hyperUnion(String destKey, String srcKey1, String srcKey2) {
        return stringRedisTemplate.opsForHyperLogLog().union(destKey, srcKey1, srcKey2);
    }
    public Long hyperUnion(String destKey, String... srcKeys) {
        return stringRedisTemplate.opsForHyperLogLog().union(destKey, srcKeys);
    }
  public Long geoAdd(String key, double lat, double lon, String member) {
        return stringRedisTemplate.opsForGeo().add(key, new Point(lat, lon), member);
    }
    public List<Point> geoGet(String key, String member) {
        return stringRedisTemplate.opsForGeo().position(key, member);
    }
    public Distance geoDistance(String key, String member1, String member2, Metric metric) {
        return stringRedisTemplate.opsForGeo().distance(key, member1, member2, metric);
    }
    public GeoResults<RedisGeoCommands.GeoLocation<String>> geoRadius(String key, double longitude, double latitude, double radius, RedisGeoCommands.DistanceUnit unit) {
        Point point = new Point(longitude, latitude);
        Circle circle = new Circle(point, new Distance(radius, unit));
        RedisGeoCommands.GeoRadiusCommandArgs args = RedisGeoCommands.GeoRadiusCommandArgs.newGeoRadiusArgs().includeDistance().includeCoordinates().sortAscending();
        return stringRedisTemplate.opsForGeo().radius(key, circle, args);
    }
    public GeoResults<RedisGeoCommands.GeoLocation<String>> geoNearByMember(String key, String member, double radius, RedisGeoCommands.DistanceUnit unit) {
        RedisGeoCommands.GeoRadiusCommandArgs args = RedisGeoCommands.GeoRadiusCommandArgs.newGeoRadiusArgs().includeDistance().includeCoordinates().sortAscending();
        return stringRedisTemplate.opsForGeo().radius(key, member, new Distance(radius, unit), args);
    }
}