Method and device for multi-thread processing data

Abstract

The invention provides a method and device for multi-thread processing data, which are used to realize that multiple threads process a large amount of data at the same time, rationally utilize thread resources, reduce thread resource consumption, and improve the efficiency of system processing data. The method of the present invention includes: for the data group currently processed by multithreading, when any data processing is completed, select a data from the unprocessed data and add it to the data group; wherein, one thread processes one data ; Estimate the total amount of resources consumed by processing the data in the data group at the end of the first processing of any data in the data group, and start processing the data in the group if the total amount of resources meets the preset condition.

Description

technical field [0001] The invention relates to the communication field, in particular to a method and device for multi-thread processing data. Background technique [0002] Based on the global information system (Global Information System, GIS) Call Detail Log-Measurement Report (Call Detail Log-Measurement Report, CDL-MR) mass intelligent analysis system, it can CDL-MR data analysis can detect hidden problems in the network in a timely manner, quickly avoid potential network risks, and ensure the stable and healthy development of the network. The application of this analysis system effectively improves the service experience and brand loyalty of user terminals, and reduces the cost of network optimization. [0003] The analysis process of CDL-MR data of RNC by CDL-MR massive intelligent analysis system includes the following two parts: [0004] The first analysis process: analyze the data in the CDL-MR file, and store the analyzed data into the database; [0005] The sec...

AI Technical Summary

Problems solved by technology

[0008] The increase of memory consumption leads to the decline of system performance, which reduces the processing efficiency of the system;

[0009] Due to the limited memory requested, for example, for applications on 32-bit machines, the memory requested by a process cannot exceed 2G. With the gradual increase in memory consumption, when the consumed memory reaches the upper limit, it will cause the thread to fail to apply for memory, and then the thread will no longer be able to process the data

[0010] To sum up, when the CDL-MR mass intelligent analysis system uses multiple threads to process data at the same time, because the amount of data processed is relatively large, and the data to be processed by the thread selection is random, it does not take into account the time required for processing the data. The amount of memory resources consumed makes the use of thread memory resources unreasonable, which will consume a large amount of memory resources, resulting in a decline in system performance and a reduction in system processing efficiency

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