Data acquisition method and device based on Actor model and storage medium

Abstract

The invention discloses a data acquisition method and device based on an Actor model and a computer readable storage medium, and is applied to the field of data processing. The method comprises the steps of detecting whether a newly added target task exists in a task cluster or not; under the condition that it is detected that a newly-added target task exists in the task cluster, establishing an Actor model for the target task, wherein the Actor model comprises a plurality of data collectors; dividing the plurality of data collectors into a plurality of stages, and setting the trigger sequences of the plurality of stages; according to the triggering sequence of the multiple stages, sequentially triggering the data collectors of the multiple stages to collect data; and deleting the target task in the task cluster after it is detected that all the data collectors at multiple stages collect the data. According to the application, the plurality of data collectors are Actors, and the execution sequences of different data collectors are set, so that the plurality of data collectors can be dispatched to complete the data collection without a lock.

Description

technical field [0001] The present application relates to the field of data collection, in particular to a data collection method, device and computer-readable storage medium based on an Actor model. Background technique [0002] Data acquisition often falls into a deadlock due to concurrent access to a critical resource by multiple threads or processes. At this time, the critical resource can be locked to establish a mutual exclusion synchronization mechanism between threads or processes to ensure the critical resource. completeness and consistency. There are many mutual exclusion schemes available for stand-alone process synchronization and thread synchronization, such as mutexes, semaphores, and condition variables. However, these mutual exclusion schemes under a single machine cannot be used on multiple machines, because the components of the distributed system run on different machines, making them not in a unified operating environment. [0003] In distributed data c...

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Problems solved by technology

[0004] However, the implementation of distributed locks is more complicated, and the maintenance is more troublesome, requiring more maintenance costs. Therefore, distributed locks are not an ideal solution to the deadlock problem of distributed data collection, and there is still a lack of a more efficient distributed lock. Data collection method

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