redis 数据结构和使用场景

1. strings
2. lists
3. sets
4. sort sets
5. 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 &lt; 100; i++) {
  arr[i] = "A" + new Random().nextInt(10) + 1;
}
redisTemplate.opsForHyperLogLog().add(loglogKey, arr);
System.out.println("loglog:" + redisTemplate.opsForHyperLogLog().size(loglogKey));

}