Implementing Redis Distributed Lock with Jedis and Simulating High‑Concurrency Order抢单

The article introduces Redis distributed locks, a common interview topic, and uses a simulated order‑抢单 scenario to illustrate the implementation.

Dependency

<dependency>
    <groupId>redis.clients</groupId>
    <artifactId>jedis</artifactId>
</dependency>

Lock creation with setNX

Jedis' set method is called with the NX option (set only if the key does not exist) and PX for a millisecond expiration, ensuring that only one client can acquire the lock at a time.

public boolean setnx(String key, String val) {
    Jedis jedis = null;
    try {
        jedis = jedisPool.getResource();
        if (jedis == null) return false;
        return jedis.set(key, val, "NX", "PX", 1000 * 60).equalsIgnoreCase("ok");
    } catch (Exception ex) {
        // handle exception
    } finally {
        if (jedis != null) jedis.close();
    }
    return false;
}

The method returns true only when the lock is successfully set; otherwise it returns false.

Lock deletion

A Lua script is used to delete the lock atomically only when the stored value matches the requester’s value.

public int delnx(String key, String val) {
    Jedis jedis = null;
    try {
        jedis = jedisPool.getResource();
        if (jedis == null) return 0;
        StringBuilder sb = new StringBuilder();
        sb.append("if redis.call('get','").append(key).append("')=='").append(val).append("' then ")
          .append("return redis.call('del','").append(key).append("') else return 0 end");
        return Integer.valueOf(jedis.eval(sb.toString()).toString());
    } catch (Exception ex) {
        // handle exception
    } finally {
        if (jedis != null) jedis.close();
    }
    return 0;
}

The delete API simply forwards the request to the above method.

Simulating 100,000 concurrent users

Using Java parallel streams, 100,000 virtual users are created, a product inventory of 10 is initialized, and each user repeatedly attempts to acquire the lock within a 30‑second timeout. When a lock is obtained, the user sleeps for one second to mimic order processing, decrements the inventory, and finally releases the lock.

private String qiang(String b) {
    long startTime = System.currentTimeMillis();
    while ((startTime + timeout) >= System.currentTimeMillis()) {
        if (nKuCuen <= 0) break;
        if (jedisCom.setnx(shangpingKey, b)) {
            try {
                if (nKuCuen <= 0) break;
                TimeUnit.SECONDS.sleep(1);
                nKuCuen -= 1;
                return b + "抢单成功，所剩库存：" + nKuCuen;
            } finally {
                jedisCom.delnx(shangpingKey, b);
            }
        }
    }
    return "";
}

The key points of the implementation are:

parallelStream() simulates many users competing for the same product.

The loop (startTime + timeout) >= System.currentTimeMillis() lets a failed user keep trying within the timeout.

Inventory is checked before and after acquiring the lock. jedisCom.setnx(shangpingKey, b) obtains the lock.

After a successful order, the lock is released with jedisCom.delnx(shangpingKey, b).

Log screenshots show that only one request succeeds per lock acquisition and that the lock expires automatically, fulfilling the distributed‑lock requirements.

Finally, the API returns the list of users who successfully placed an order.

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