HashMap和布隆过滤器命中性能测试

package datafilter;

import com.google.common.base.Stopwatch;

import com.google.common.hash.BloomFilter;

import com.google.common.hash.Funnels;

import java.util.*;

import static java.util.concurrent.TimeUnit.MILLISECONDS;

import static java.util.concurrent.TimeUnit.NANOSECONDS;

public class WarnIp {

	public static String getRandomIp() {

		// 需要排除监控的ip范围

		int[][] range = { { 607649792, 608174079 }, // 36.56.0.0-36.63.255.255

				{ 1038614528, 1039007743 }, // 61.232.0.0-61.237.255.255

				{ 1783627776, 1784676351 }, // 106.80.0.0-106.95.255.255

				{ 2035023872, 2035154943 }, // 121.76.0.0-121.77.255.255

				{ 2078801920, 2079064063 }, // 123.232.0.0-123.235.255.255

				{ -1950089216, -1948778497 }, // 139.196.0.0-139.215.255.255

				{ -1425539072, -1425014785 }, // 171.8.0.0-171.15.255.255

				{ -1236271104, -1235419137 }, // 182.80.0.0-182.92.255.255

				{ -770113536, -768606209 }, // 210.25.0.0-210.47.255.255

				{ -569376768, -564133889 }, // 222.16.0.0-222.95.255.255

		};

		Random rdint = new Random();

		int index = rdint.nextInt(10);

		String ip = num2ip(range[index][0] + new Random().nextInt(range[index][1] - range[index][0]));

		return ip;

	}

	/*

	 * 将十进制转换成IP地址

	 */

	public static String num2ip(int ip) {

		int[] b = new int[4];

		String x = "";

		b[0] = (int) ((ip >> 24) & 0xff);

		b[1] = (int) ((ip >> 16) & 0xff);

		b[2] = (int) ((ip >> 8) & 0xff);

		b[3] = (int) (ip & 0xff);

		x = Integer.toString(b[0]) + "." + Integer.toString(b[1]) + "." + Integer.toString(b[2]) + "." + Integer.toString(b[3]);

		return x;

	}

	private static Map<String, Integer> map = new HashMap<>();

	private static BloomFilter<String> bloomFilter = BloomFilter.create(Funnels.unencodedCharsFunnel(), 1000000);

	private static List<String> list = new ArrayList<>();

	static {

		int count = 100000000;

		for (int id = 0; id < count; id++) {

			String randomIp = getRandomIp();

			int randomPort = (int)(Math.random() * 65536);

			String key = randomIp + ":" + randomPort;

			if(!map.containsKey(key)) {

				System.out.println("key: " + key);

				map.put(key, id);

				list.add(key);

				bloomFilter.put(key);

			}

			if(map.size() >= 1000000) {

				break;

			}

		}

	}

	static Stopwatch stopwatch = Stopwatch.createUnstarted();

	public static void main(String[] args) {

		System.out.println("map.size: " + map.size());

		Scanner scanner = new Scanner(System.in); //String param = "222.17.204.104:8001";

		while(scanner.hasNextLine()) {

			String param = scanner.nextLine();

			System.out.println("Input: " + param);

			if("exit".equalsIgnoreCase(param)) {

				break;

			}

			stopwatch.start();

//			if (map.containsKey(param)) { //map判断

//			if(list.contains(param)) {

			if (bloomFilter.mightContain(param)) { //布隆过滤器判断（默认3%误差率）

				System.out.println("list集合存在该数据=============数据: " + param);

			}

			//计时结束

			stopwatch.stop();

			System.out.println("list集合测试，判断该元素集合中是否存在用时: " + stopwatch.elapsed(MILLISECONDS));

			System.out.println("list集合测试，判断该元素集合中是否存在用时: " + stopwatch.elapsed(NANOSECONDS));

			stopwatch.reset();

		}

		scanner.close();

	}

}

结论：100w数据，key都是字符串（ip:port），map测试时，key存在大概耗时0.01-0.1ms，不存在时大概0.005ms左右，list耗时20-40ms，布隆过滤器0.01-0.2ms左右。除此之外需要考虑占用内存，按255.255.255.255:65535来考虑，用list存储100w条21字节*1000000约20M，布隆过滤器占用更小。

巴特西

HashMap和布隆过滤器命中性能测试

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