Gearman is an open-source job queue manager and distributed task handling system. It is used to distribute tasks (jobs) and execute them in parallel processes. Gearman allows large or complex tasks to be broken down into smaller sub-tasks, which can then be processed in parallel across different servers or processes.
Gearman operates on a simple client-server-worker model:
Client: A client submits a task to the Gearman server, such as uploading and processing a large file or running a script.
Server: The Gearman server receives the task and splits it into individual jobs. It then distributes these jobs to available workers.
Worker: A worker is a process or server that listens for jobs from the Gearman server and processes tasks that it can handle. Once the worker completes a task, it sends the result back to the server, which forwards it to the client.
Distributed Computing: Gearman allows tasks to be distributed across multiple servers, reducing processing time. This is especially useful for large, data-intensive tasks like image processing, data analysis, or web scraping.
Asynchronous Processing: Gearman supports background job execution, meaning a client does not need to wait for a job to complete. The results can be retrieved later.
Load Balancing: By using multiple workers, Gearman can distribute the load of tasks across several machines, offering better scalability and fault tolerance.
Cross-platform and Multi-language: Gearman supports various programming languages like C, Perl, Python, PHP, and more, so developers can work in their preferred language.
Batch Processing: When large datasets need to be processed, Gearman can split the task across multiple workers for parallel processing.
Microservices: Gearman can be used to coordinate different services and distribute tasks across multiple servers.
Background Jobs: Websites can offload tasks like report generation or email sending to the background, allowing them to continue serving user requests.
Overall, Gearman is a useful tool for distributing tasks and improving the efficiency of job processing across multiple systems.
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