ElasticSearch (ES) query acceleration method

A technology of query conditions and query results, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as occupancy, achieve efficient operations, improve indexing efficiency, and improve concurrent query efficiency

Active Publication Date: 2018-09-07
南京烽火星空通信发展有限公司
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide an ElasticSearch query acceleration method, which solves the problem that the calculation of intersection and union will take a lot of time if the data volume of each result set is large when querying ES raw data, and improves the indexing efficiency

Method used

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  • ElasticSearch (ES) query acceleration method
  • ElasticSearch (ES) query acceleration method

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Embodiment Construction

[0044] Such as Figure 1 to Figure 4 An ElasticSearch query acceleration method shown includes the following steps:

[0045] Step 1: Establish a full-text index system. The full-text index system includes a Hadoop storage server cluster, a WEB interface server, a data import server and a data collection terminal. The data collection terminal is connected to the data import server through the Internet, and both the WEB interface server and the data import server are connected through the Internet. Hadoop storage server cluster;

[0046] Step 2: Establish a full-text retrieval platform in the Hadoop storage server cluster through the Lucene full-text information retrieval tool, and allocate an ES cluster in the Hadoop storage server cluster through the Lucene full-text information retrieval tool;

[0047] Step 3: The data collection terminal inputs stream data or text data to the data import server, and the data import server sends the stream data or text data to the Hadoop sto...

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Abstract

The invention discloses an ElasticSearch (ES) query acceleration method, and relates to the field of computer big-data index technology. According to the method, firstly, a Payload load domain is added for each field, then filtering operation is carried out on the basis of single sub-query-conditions through the Payload load domains, the problem that in ES raw-data queries, calculation of extracting intersection sets and union sets can occupy a lot of time if the data amount of each result set is very large is solved, and index efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of computer big data indexing. Background technique [0002] Today, an era of large-scale production, sharing and application of data is opening, data is rapidly expanding and becoming larger, and human beings have entered the Internet era. In particular, social networks, e-commerce and mobile communications have brought human beings into a new era of massive structured and unstructured data information. The huge amount of data leads to the high complexity of these massive data, which is full of changes and is very complicated to deal with. How to analyze and process massive data and provide simple and convenient services has become a problem that many IT companies and institutions must face. [0003] Massive data is divided into structured data and unstructured data. Structured data refers to such as corporate financial accounts and production data, student score data, statistical report data, etc., and u...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 王磊王胤然徐寅穆宁
Owner 南京烽火星空通信发展有限公司
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