Method for big data retrieval based on time characteristics and supporting complicated conditions

Abstract

The invention relates to a method for big data retrieval based on time characteristics and supporting complicated conditions. According to timestamps generated during data storage or according to user defined time characteristics, data information is segmented according to the time characteristics, indexes are established on different collections on a full-text retrieval engine Solr; on the conditions that users already know the time of queried information generation, quick positioning can be performed on an index database of a collection of the same month to perform retrieval, the retrieval range can be greatly reduced, and the efficiency is improved. On the conditions that users cannot determine information generation time, results conforming to user query are provided for users for reference and selection. According to the method, not only is the shortcoming that a distributed database HBase has no secondary index overcome, but also the index establishment is more flexible, the retrieval on different demand conditions is met, and the retrieval efficiency can be guaranteed.

Description

technical background [0001] The invention relates to a large data retrieval method that supports complex conditions based on time features. Background technique [0002] In the environment of big data, it is the foundation and an important part of big data applications to quickly and accurately retrieve the information that users care about and are interested in according to the conditions provided by users. At present, there are two main deficiencies in big data retrieval: first, in the big data environment, in order to provide the best query performance, a big data all-in-one machine integrating software and hardware is generally used, which significantly increases the cost of the project; second, in the big data environment, After the amount of data increases and the cluster expands, the performance of retrieval tends to decrease significantly. Contents of the invention [0003] The purpose of the present invention is to provide a large data retrieval method based on...

AI Technical Summary

Problems solved by technology

At present, there are two main deficiencies in big data retrieval: first, in the big data environment, in order to provide the best query performance, a big data all-in-one machine integrating software and hardware is generally used, which significantly increases the cost of the project; second, in the big data environment, After the amount of data increases and the cluster expands, the performance of retrieval tends to decrease significantly

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