Redis BloomFilter實例講解

dependency>
   groupId>com.google.guava/groupId>
   artifactId>guava/artifactId>
   version>30.1.1-jre/version>
/dependency>

import com.google.common.hash.BloomFilter;
import com.google.common.hash.Funnels;
import lombok.extern.slf4j.Slf4j;

/**
 * 布隆過濾器簡單實現(xiàn)
 * @author ludangxin
 * @date 2021/8/16
 */
@Slf4j
public class BloomFilterTest {
   /**
    * 預(yù)計要插入元素個數(shù)
    */
   private static final int SIZE = 1000000;
   /**
    * 誤判率
    */
   private static final double FPP = 0.01;
   /**
    * 布隆過濾器
    */
   private static final BloomFilterInteger> BLOOMFILTER = BloomFilter.create(Funnels.integerFunnel(), SIZE, FPP);

   public static void main(String[] args) {
      //插入數(shù)據(jù)
      for (int i = 0; i  1000000; i++) {
         BLOOMFILTER.put(i);
      }
      int count = 0;
      // 過濾判斷
      for (int i = 1000000; i  3000000; i++) {
         if (BLOOMFILTER.mightContain(i)) {
            count++;
            log.info(i + "誤判了");
         }
      }
      log.info("總共的誤判數(shù):" + count);
   }
}

dependency>
   groupId>org.redisson/groupId>
   artifactId>redisson-spring-boot-starter/artifactId>
   version>3.16.1/version>
/dependency>

import lombok.RequiredArgsConstructor;
import lombok.extern.slf4j.Slf4j;
import org.redisson.api.RBloomFilter;
import org.redisson.api.RedissonClient;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

/**
 * redisson 布隆過濾器實現(xiàn)
 *
 * @author ludangxin
 * @date 2021/8/16
 */
@Slf4j
@RestController
@RequestMapping("bloomFilter")
@RequiredArgsConstructor
public class BloomFilterWithRedisson {
   private final RedissonClient redissonClient;

   /**
    * 預(yù)計要插入元素個數(shù)
    */
   private static final long SIZE = 1000000L;
   /**
    * 誤判率
    */
    private static final double FPP = 0.01;

   /**
    * 自定義布隆過濾器的 key
    */
   private static final String BLOOM_FILTER_KEY = "bloomFilter";

   /**
    * 向布隆過濾器中添加數(shù)據(jù), 模擬向布隆過濾器中添加10億個數(shù)據(jù)
    */
   @GetMapping
   public void filter() {
     // 獲取布隆過濾器
      RBloomFilterInteger> bloomFilter = redissonClient.getBloomFilter(BLOOM_FILTER_KEY);
      // 初始化，容量為100萬， 誤判率為0.01
      bloomFilter.tryInit(SIZE, FPP);
      // 模擬向布隆過濾器中添加100萬個數(shù)據(jù)
      for (int i = 0; i  SIZE; i++) {
          bloomFilter.add(i);
      }
      int count = 0;
      // 過濾判斷
      for (int i = 1000000; i  3000000; i++) {
         if (bloomFilter.contains(i)) {
            count++;
            log.info(i + "誤判了");
         }
      }
      log.info("size:" + bloomFilter.getSize());
      log.info("總共的誤判數(shù):" + count);
   }
}