Unstructured event log data classification and storage method and device
An unstructured, data storage technology, applied in the direction of unstructured text data retrieval, text database clustering/classification, electronic digital data processing, etc., can solve the problems affecting the amount of information, retrieval efficiency and comprehensive impact, and achieve Easy to filter effects
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Embodiment 1
[0024] First, the data information of different locations and sensors is collected through the data acquisition module, and then passed to the data classification module through the data transmission module. According to the time and coordinate information of the event data, the space is firstly divided in the form of a grid. Each grid To correspond to a square area in geographical space, arrange them in chronological order, and finally store the divided data in the data storage module. The data storage module uses 8MB data blocks to store them in slices, and divides each shard into a series of Segment, each Segment contains a series of Events, and then extracts a specific domain Field for the Event, and performs word segmentation on the entire Event information, and finally creates a full-text index to realize data filtering, data conversion, data grouping, and data aggregation processing, which is convenient Subsequent data retrieval.
Embodiment 2
[0026] First, the data information of different locations and sensors is collected through the data acquisition module, and then passed to the data classification module through the data transmission module. According to the time and coordinate information of the event data, the space is firstly divided in the form of a grid. Each grid In order to correspond to a square area of geographical space, it is arranged in sequence according to time, and finally the divided data is stored in the data storage module. The data storage module uses a 16MB data block and adopts a fragmented storage method to divide each shard into a series of Segment, each Segment contains a series of Events, and then extracts a specific domain Field for the Event, and performs word segmentation on the entire Event information, and finally creates a full-text index to realize data filtering, data conversion, data grouping, and data aggregation processing, which is convenient Subsequent data retrieval.
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