How to use Workerman to implement a distributed crawler system

How to use Workerman to implement a distributed crawler system

Introduction:
With the rapid development of the Internet, rapid acquisition of information has become increasingly important for many industries. is becoming more and more important. As an automated data collection tool, crawlers are widely used in visual analysis, academic research, price monitoring and other fields. With the increase in data volume and the diversity of web page structures, traditional stand-alone crawlers can no longer meet the demand. This article will introduce how to use the Workerman framework to implement a distributed crawler system to improve crawling efficiency.

1. Introduction to Workerman
Workerman is a high-performance, highly scalable network communication framework based on PHP. It takes advantage of PHP's asynchronous IO extension to achieve IO multiplexing, thus greatly improving Efficiency of network communication. The core idea of Workerman is a multi-process model, which can achieve process-level load balancing.

2. Architecture design of distributed crawler system
The architecture of distributed crawler system includes master node and slave node. The master node is responsible for scheduling tasks, initiating requests and receiving results returned from slave nodes, and the slave nodes are responsible for the actual crawling tasks. Communication between the master node and slave nodes occurs through TCP connections.

The architecture design is shown in the figure below:

主节点 +---+ | | +---+ 从节点 +---+ | | +---+ 从节点 +---+ | | +---+ 从节点 +---+ | | +---+

3. Implementation of the master node
The implementation of the master node mainly includes task scheduling, task allocation and result processing.

1. Task Scheduling
   The master node receives connection requests from slave nodes by listening to a port. When the slave node is successfully connected, the master node will send a task request to the slave node.

count = 4; // 主节点的进程数 $worker->onConnect = function($con) { echo "New connection "; // 向从节点发送任务请求 $con->send('task'); }; Worker::runAll();

2. Task allocation
   After the master node receives the task request sent from the slave node, it allocates it according to the needs. Flexible scheduling can be performed based on task type, slave node load, etc.

$worker->onMessage = function($con, $data) { $task = allocateTask($data); // 任务分配算法 $con->send($task); };

3. Result processing
   After the master node receives the results returned from the slave node, it can perform further processing, such as storing in the database, parsing, etc.

$worker->onMessage = function($con, $data) { // 处理结果 saveToDatabase($data); };

4. Implementation of slave nodes
The implementation of slave nodes mainly includes receiving tasks, executing tasks, and returning results.

1. Receiving tasks and executing tasks
   The slave node will continuously monitor the requests sent by the master node. When receiving the task, it will perform specific crawling work according to the task type.

count = 4; // 从节点的进程数 $worker->onMessage = function($con, $data) { if ($data === 'task') { $task = getTask(); // 获取任务 $con->send($task); } else { $result = executeTask($data); // 执行任务 $con->send($result); } }; Worker::runAll();

2. Return results
   After the slave node returns the crawling results to the master node, it can continue to receive the next task.

$worker->onMessage = function($con, $data) { // 执行任务并返回结果 $result = executeTask($data); $con->send($result); };

5. Summary
By using the Workerman framework, we can easily implement a distributed crawler system. By allocating tasks to different slave nodes and taking advantage of Workerman's high performance and scalability, we can greatly improve crawling efficiency and stability. I hope this article will help you understand how to use Workerman to implement a distributed crawler system.

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