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redis使用场景和java测试案例

redis数据结构和使用场景

strings
lists
sets
sort sets
hashes

strings

token
session
validateCode
分布锁
lists
最近联系人
sets
优惠卷
激活码
用户标签
sort sets
排行榜
hashes
购物车
bitmaps
用户签到
在线状态
hyperloglog
ip去重复统计
geo
附近的人
摇一摇
两位距离

主要使用场景对应的java源码

/**
   * 代金卷例子.
   * set结构保证了value的唯一性.
   */
  @Test
  public void setCoupon() {
    final String COUPON_KEY = "coupon";

    for (int i = 0; i < 100; i++) {
      redisTemplate.opsForSet().add(COUPON_KEY, String.format("abc%s", i));
      redisTemplate.opsForSet().add(COUPON_KEY, String.format("abc%s", i));
    }
    Assert.assertEquals(Long.valueOf(100), redisTemplate.opsForSet().size(COUPON_KEY));
    redisTemplate.opsForSet().pop(COUPON_KEY);
    Assert.assertEquals(Long.valueOf(99), redisTemplate.opsForSet().size(COUPON_KEY));

  }

  /**
   * 用户消费top10.
   * sortList结构做实时排名.
   */
  @Test
  public void sortListTop() {
    final String CONSUMPTION_KEY = "consumption";

    redisTemplate.opsForZSet().add(CONSUMPTION_KEY, "person1", 1);
    redisTemplate.opsForZSet().add(CONSUMPTION_KEY, "person2", 2);
    redisTemplate.opsForZSet().add(CONSUMPTION_KEY, "person3", 1);

    for (Object o : redisTemplate.opsForZSet().rangeByScore(CONSUMPTION_KEY, 1, 1)) {
      System.out.println(o);
    }

  }

  @Test
  public void distributeLock2() {

    new Thread(() -> {
      for (int i = 0; i < 5; i++) {
        queue2();
      }
    }).start();
  }

  /**
   * 地理位置测试.
   */
  @Test
  public void geoTest() {
    BoundGeoOperations boundGeoOperations = redisTemplate.boundGeoOps("CHINA:CITY");
    Point nanjing = new Point(118.803805, 32.060168);
    boundGeoOperations.add(nanjing, "南京市");
    Point beijing = new Point(116.397039, 39.9077);
    boundGeoOperations.add(beijing, "北京市");
    Point shanghai = new Point(120.52, 30.40);
    boundGeoOperations.add(shanghai, "上海市");
    //geodist：获取两个地理位置的距离
    Distance distance = boundGeoOperations.distance("南京市", "北京市", Metrics.KILOMETERS);
    System.out.println("南京市到北京市之间的距离是：" + distance.getValue() + "km");

    Distance distance2 = boundGeoOperations.distance("南京市", "上海市", Metrics.KILOMETERS);
    System.out.println("南京市到上海市之间的距离是：" + distance2.getValue() + "km");

    //geohash：获取某个地理位置的geohash值
    List<String> list = boundGeoOperations.hash("南京市");
    System.out.println("南京市的geoHash = " + list.get(0));

    //geopos：获取某个地理位置的坐标
    List<Point> pointList = boundGeoOperations.position("南京市");
    System.out.println("南京市的经纬度为 = " + pointList.get(0));

    //georadius：根据给定地理位置坐标获取指定范围内的地理位置集合
    //查询南京市1000KM范围内的城市
    Circle within = new Circle(nanjing, 1000000);
    //设置geo查询参数
    RedisGeoCommands.GeoRadiusCommandArgs geoRadiusArgs = RedisGeoCommands.GeoRadiusCommandArgs.newGeoRadiusArgs();
    //查询返回结果包括距离和坐标
    geoRadiusArgs = geoRadiusArgs.includeCoordinates().includeDistance();
    //按查询出的坐标距离中心坐标的距离进行排序
    geoRadiusArgs.sortAscending();
    //限制查询返回的数量
    geoRadiusArgs.limit(2);
    GeoResults<RedisGeoCommands.GeoLocation<String>> geoResults = boundGeoOperations.radius(within, geoRadiusArgs);
    List<GeoResult<RedisGeoCommands.GeoLocation<String>>> geoResultList = geoResults.getContent();
    for (GeoResult geoResult : geoResultList) {
      System.out.println("geoRadius  " + geoResult.getContent());
    }

    //georadiusbymember：根据给定地理位置获取指定范围内的地理位置集合
    geoRadiusArgs.limit(1);
    geoResults = boundGeoOperations.radius("南京市", new Distance(1000000), geoRadiusArgs);
    geoResultList = geoResults.getContent();
    for (GeoResult geoResult : geoResultList) {
      System.out.println("geoRadiusByMember  " + geoResult.getContent());
    }
    //删除位置信息,此命令不是geo提供的，是使用zrem命令删除的
   boundGeoOperations.remove("南京市");
  }

  /**
   * 查看用户在线状态情况 1在线，0离线.
   */
  @Test
  public void bitmapTest() {
    final String onlineKey = "online:";
    for (int i = 0; i < 100; i++) {
      redisTemplate.opsForValue().setBit(onlineKey, i, i % 2 == 0);
    }
    for (int i = 0; i < 10; i++) {

      System.out.println(i + "=" + redisTemplate.opsForValue().getBit(onlineKey, i));
    }
    System.out.println("online:" + redisConfig.bitCount(onlineKey));
  }

  /**
   * 统一数组里数据唯一性.
   * IP地址去重复.
   */
  @Test
  public void hyperLogLogTest() {
    final String loglogKey = "loglog:";

    String[] arr = new String[100];
    for (int i = 0; i < 100; i++) {
      arr[i] = "A" + new Random().nextInt(10) + 1;
    }
    redisTemplate.opsForHyperLogLog().add(loglogKey, arr);
    System.out.println("loglog:" + redisTemplate.opsForHyperLogLog().size(loglogKey));
  }

原文 http://www.cnblogs.com/lori/p/10457011.html

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