Mass data monitoring system
A monitoring system and massive data technology, applied in digital transmission systems, transmission systems, data exchange networks, etc., can solve problems such as the difficulty of massive data collection and monitoring, and achieve faster collection and processing speed, improved data processing speed, and improved The effect of data processing capacity
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Embodiment 1
[0024] The mass data monitoring system based on partition cluster technology partitions the mass data sources to be collected, and then uses cluster technology to build a three-level cluster architecture of front-end computer clusters, SCADA clusters, and worker station clusters to achieve parallel collection and monitoring of massive data. Monitor processing.
[0025] Specifically, such as figure 1 As shown, three pre-cluster servers, three SCADA cluster processing servers, two operator stations, and nine data simulation sources for partitioning are used. Here, nine data simulation sources are used instead of real data sources to complete the construction of a massive data monitoring system. Specifically, the nine data simulation sources are divided into three data source partitions according to certain physical and logical meanings, such as figure 1 As shown, data simulation sources 1, 2, and 3 are divided into data source partition A, data simulation sources 4, 5, and 6 ar...
Embodiment 2
[0032] The above-mentioned embodiment provides a kind of implementation mode of massive data monitoring system, as other implementation modes, such as figure 2 As shown, in each node of the SCADA cluster, corresponding to the real-time real-time database, a simulated real-time database is also provided in parallel. At the same time, a control service module for accessing the simulation state real-time library is also provided in the nodes of the SCADA cluster, and a control client for accessing the control service module in the SCADA cluster nodes is provided in each operator workstation. In this way, the advanced application of the upper layer is realized to conduct non-real-time data analysis and research, and make some trend predictions for the system.
Embodiment 3
[0034] The above-mentioned embodiments provide the implementation manners in which the massive data monitoring system collects and processes data in parallel. As other implementation manners, the massive data monitoring system also has a redundant function. like image 3 As shown, in each node of the pre-processing cluster, another pre-processing service module is set in parallel with the original pre-processing service module, and another data processing module is also set in parallel in each node of the SCADA cluster. Processing service module, real-time real-time database, simulation real-time database and control service module. like image 3 As shown, pre-processing service module 1 and pre-processing service module 2 are set in pre-cluster node A, pre-processing service module 1 collects data source partition A, and pre-processing service module 2 collects data source partitions B; pre-processing service module 2 and pre-processing service module 3 are set in pre-clust...
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