Multi-level database building method and device for retrieval database and storage medium
A database and data technology, applied in the field of big data search, can solve the problems of large retrieval database, low frequency and low efficiency of retrieval database update, achieve high update efficiency and update frequency, ensure efficiency and stability, and the effect of general capacity
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Embodiment 1
[0066] see figure 1 As shown, a multi-level database building method for searching databases, including real-time database building, used to save the data information changed from the first time node in the past to the current time node, and the first time node is regularly updated so that the first time node The time interval from the current time node remains unchanged.
[0067] The real-time database building described in this embodiment includes:
[0068] Write the data information of business changes in the retrieval database into the publish-subscribe system in real time;
[0069] Subscribe to the publish-subscribe system to obtain real-time changed data information;
[0070] Generate forward index data according to the real-time changed data information, and push it into the real-time database fragments.
[0071] The real-time database building database in this embodiment is used to save the data information changed from the first time node in the past to the current...
Embodiment 2
[0188] see image 3 As shown, this embodiment provides a data update method for a retrieval database, the retrieval database includes a base database and an incremental database, and the base database and the incremental database are respectively produced during the indexing process. The intermediate files of the volume library and the intermediate files of the incremental library are stored;
[0189] Merge the data of the incremental database into the base database, match the intermediate files of the incremental database with the intermediate files of the base database, and balance the index data of the base database.
[0190] In a search engine, after the data is crawled, it will be indexed for easy retrieval. The index includes a forward index and an inverted index. The forward index means that the document ID is the key, and the number of occurrences of each keyword is recorded in the table. When searching, the information of each word in each document in the table is sc...
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