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Data query method, device, server and storage medium

A data query and queryer technology, applied in the field of big data, can solve the problems of slow query speed, large amount of network data transmission traffic, low efficiency of aggregation query, etc., to achieve the effect of improving speed and avoiding transmission.

Active Publication Date: 2021-01-01
NEW H3C BIG DATA TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, currently, when SparkSQL aggregates the data in the database, the aggregation query includes group aggregation query and regular aggregation query, for example, "count the sum of the grades of the students whose gender field is "male" and "female" in the student table", "Statistics on the average age of people in the user table", etc., SparkSQL will read all the data in the data table into Spark and then perform aggregation calculations, which may generate a large amount of network data transmission traffic, resulting in low efficiency and slow query speed of aggregation queries

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  • Data query method, device, server and storage medium
  • Data query method, device, server and storage medium
  • Data query method, device, server and storage medium

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Embodiment Construction

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts belong to the protection scope of the present invention.

[0022] It should be noted that like numerals and let...

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Abstract

The embodiment of the invention relates to the technical field of big data. The invention provides a data query method and device, a server and a storage medium. When aggregated query is performed ondata in a distributed database through a querier in a distributed environment, the method comprises the following steps: analyzing a received structured query language (SQL) statement, and pushing down an aggregation operation in the SQL statement to a connector; and then, receiving an aggregation result fed back by the connector, the aggregation result being obtained by re-aggregating a pluralityof pre-aggregation results obtained by pre-aggregating the data table by the distributed database according to the aggregation operation. Compared with the prior art, the data aggregation is carriedout in the connector and the distributed database, and the querier receives the aggregation result fed back by the connector, so that the transmission of a large amount of data is avoided, and the aggregation query speed of the querier is effectively improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of big data, and in particular, relate to a data query method, device, server, and storage medium. Background technique [0002] Spark is a memory-based distributed computing framework, including SparkSQL capable of processing SQL (StructuredQuery Language, Structured Query Language) statements, through which data in various databases can be read, analyzed and counted. However, currently, when SparkSQL aggregates the data in the database, the aggregation query includes group aggregation query and regular aggregation query, for example, "count the sum of the grades of the students whose gender field is "male" and "female" in the student table", "Statistics on the average age of people in the user table", etc., SparkSQL will read all the data in the data table into Spark and then perform aggregation calculations, which may generate a large amount of network data transmission traffic, resu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/2455G06F16/2458
CPCG06F16/2455G06F16/2471
Inventor 丁远普户蕾蕾
Owner NEW H3C BIG DATA TECH CO LTD