Distributed task scheduling and distributed unique ID generation method in PHP flash sale system

Distributed task scheduling and distributed unique ID generation methods in the PHP flash sale system

In the PHP flash sale system, distributed task scheduling and distributed unique ID generation are two very critical functions. This article will introduce how to implement these two functions and provide specific code examples.

1. Distributed task scheduling

In the flash sale system, a large number of concurrent operations and scheduled tasks are required. In a stand-alone environment, these operations and tasks will put a lot of pressure on the server. In order to improve the system's concurrent processing capabilities and task scheduling efficiency, we can adopt a distributed task scheduling solution.

The following is a sample code that uses Redis as a message queue to implement distributed task scheduling:

connect('127.0.0.1', 6379); $taskData = [ 'task_id' => uniqid(), // 任务ID 'task_data' => 'some data' // 任务数据 ]; $redis->lPush('task_queue', json_encode($taskData)); // 消费者代码 $redis = new Redis(); $redis->connect('127.0.0.1', 6379); while (true) { $taskDataJson = $redis->rPop('task_queue'); if ($taskDataJson) { $taskData = json_decode($taskDataJson, true); // 执行任务代码 echo "Task ID: {$taskData['task_id']} "; echo "Task Data: {$taskData['task_data']} "; } }

In the above sample code, the producer stores task data in the Redis queue, and the consumer Then the task is taken out from the queue through a loop and executed.

2. Distributed unique ID generation method

In the flash sale system, a unique ID needs to be generated to record orders, users and other information. The traditional self-increasing ID generation method will encounter conflict problems in a distributed environment. To solve this problem, we can use the Snowflake algorithm to generate distributed unique IDs.

The following is a sample code that uses the Snowflake algorithm to achieve distributed unique ID generation:

 31 || $dataCenterId < 0) { throw new InvalidArgumentException("Data Center ID can't be greater than 31 or less than 0"); } if ($workerId > 31 || $workerId < 0) { throw new InvalidArgumentException("Worker ID can't be greater than 31 or less than 0"); } $this->dataCenterId = $dataCenterId; $this->workerId = $workerId; } public function nextId() { $timestamp = $this->getTimestamp(); if ($timestamp < self::EPOCH) { throw new Exception("Clock moved backwards. Refusing to generate ID"); } if ($timestamp === $this->lastTimestamp) { $this->sequence = ($this->sequence + 1) & 4095; // 4095是12位二进制 if ($this->sequence === 0) { $timestamp = $this->tilNextMillis(); } } else { $this->sequence = 0; } $this->lastTimestamp = $timestamp; return (($timestamp - self::EPOCH) << 22) | ($this->dataCenterId << 17) | ($this->workerId << 12) | $this->sequence; } public function tilNextMillis() { $timestamp = $this->getTimestamp(); while ($timestamp <= $this->lastTimestamp) { $timestamp = $this->getTimestamp(); } return $timestamp; } public function getTimestamp() { return floor(microtime(true) * 1000); } } // 测试代码 $snowflake = new Snowflake(1, 1); // 数据中心ID为1，工作节点ID为1 for ($i = 0; $i < 10; $i++) { echo $snowflake->nextId() . PHP_EOL; }

In the above sample code, we use the Snowflake algorithm to generate a unique ID. Among them, the data center ID and working node ID need to be determined based on the actual situation. By calling thenextIdmethod, a unique ID can be generated.

Conclusion

Through distributed task scheduling and distributed unique ID generation methods, we can improve the concurrent processing capabilities and task scheduling efficiency of the flash sale system and ensure the generation of unique IDs. I hope the above introduction will help you understand distributed task scheduling and distributed unique ID generation.

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