


How to implement the level-by-level invitation and timeout mechanism of PHP?
Detailed explanation of PHP implementation of level-by-level administrator invitation and timeout mechanism
Many application scenarios require an administrator to implement a step-by-step approval process. For example, user requests require multiple administrators to review in turn until someone approves them. This article will introduce in detail how to use PHP to combine message queues and timing tasks to implement this function. Especially after a request is initiated for the user, the system invites administrators A, B, C, etc. If the previous administrator does not respond within 5 minutes, the next administrator will be invited.
The core idea is to use message queues to manage task scheduling and delayed execution to ensure that the process is reliable and orderly. After the user initiates the request, the system immediately sends an invitation to administrator A and adds a delay task executed in 5 minutes to the message queue.
After 5 minutes, the message queue triggers the delay task. The task first checks whether the invitation has been accepted. If accepted, delete the task and the process ends; if not accepted, send an invitation to Administrator B and add a new 5-minute delay task, looping until all administrators are invited or someone accepts the invitation.
Message queues such as Redis or RabbitMQ can implement this function and operate with the corresponding PHP client library. The database needs to record the invitation status and timestamp of each administrator in order to track the process. At the same time, error handling and exception situations need to be considered, such as message queue processing failure or network interruption. The flow chart is as follows:
<code>发送邀请-> 加入延时队列-> 5分钟后-> 队列任务执行-> (已接受-> 结束) 或(未接受-> 邀请下一位管理员-> 加入延时队列)</code>
The above is the detailed content of How to implement the level-by-level invitation and timeout mechanism of PHP?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

This article discusses how to improve Hadoop data processing efficiency on Debian systems. Optimization strategies cover hardware upgrades, operating system parameter adjustments, Hadoop configuration modifications, and the use of efficient algorithms and tools. 1. Hardware resource strengthening ensures that all nodes have consistent hardware configurations, especially paying attention to CPU, memory and network equipment performance. Choosing high-performance hardware components is essential to improve overall processing speed. 2. Operating system tunes file descriptors and network connections: Modify the /etc/security/limits.conf file to increase the upper limit of file descriptors and network connections allowed to be opened at the same time by the system. JVM parameter adjustment: Adjust in hadoop-env.sh file

On CentOS systems, you can limit the execution time of Lua scripts by modifying Redis configuration files or using Redis commands to prevent malicious scripts from consuming too much resources. Method 1: Modify the Redis configuration file and locate the Redis configuration file: The Redis configuration file is usually located in /etc/redis/redis.conf. Edit configuration file: Open the configuration file using a text editor (such as vi or nano): sudovi/etc/redis/redis.conf Set the Lua script execution time limit: Add or modify the following lines in the configuration file to set the maximum execution time of the Lua script (unit: milliseconds)

Building a Hadoop Distributed File System (HDFS) on a CentOS system requires multiple steps. This article provides a brief configuration guide. 1. Prepare to install JDK in the early stage: Install JavaDevelopmentKit (JDK) on all nodes, and the version must be compatible with Hadoop. The installation package can be downloaded from the Oracle official website. Environment variable configuration: Edit /etc/profile file, set Java and Hadoop environment variables, so that the system can find the installation path of JDK and Hadoop. 2. Security configuration: SSH password-free login to generate SSH key: Use the ssh-keygen command on each node

The Hadoop task execution process mainly includes the following steps: Submit the job: the user uses the command line tools or API provided by Hadoop on the client machine to build the task execution environment and submit the task to YARN (Hadoop's resource manager). Resource application: After YARN receives the task submission request, it will apply for resources from the nodes in the cluster based on the resources required by the task (such as memory, CPU, etc.). Task Start: Once the resource allocation is completed, YARN will send the task's startup command to the corresponding node. On the node, NodeMana

This article describes how to use TigerVNC to share files on Debian systems. You need to install the TigerVNC server first and then configure it. 1. Install the TigerVNC server and open the terminal. Update the software package list: sudoaptupdate to install TigerVNC server: sudoaptinstalltigervnc-standalone-servertigervnc-common 2. Configure TigerVNC server to set VNC server password: vncpasswd Start VNC server: vncserver:1-localhostno

The Installation, Configuration and Optimization Guide for HDFS File System under CentOS System This article will guide you how to install, configure and optimize Hadoop Distributed File System (HDFS) on CentOS System. HDFS installation and configuration Java environment installation: First, make sure that the appropriate Java environment is installed. Edit /etc/profile file, add the following, and replace /usr/lib/java-1.8.0/jdk1.8.0_144 with your actual Java installation path: exportJAVA_HOME=/usr/lib/java-1.8.0/jdk1.8.0_144exportPATH=$J

When configuring Hadoop Distributed File System (HDFS) on CentOS, the following key configuration files need to be modified: core-site.xml: fs.defaultFS: Specifies the default file system address of HDFS, such as hdfs://localhost:9000. hadoop.tmp.dir: Specifies the storage directory for Hadoop temporary files. hadoop.proxyuser.root.hosts and hadoop.proxyuser.ro
