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Method and device for realizing OLAP analysis based on ClickHouse

A distributed, entity table technology, applied in the field of data management, can solve problems such as limited memory, violation of HDFS design goals, difficulty in supporting ad hoc queries, etc., to achieve fast query speed, increase large-scale parallel computing capabilities, and low learning costs Effect

Inactive Publication Date: 2021-01-01
CHANGZHOU MICROINTELLIGENCE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This technology allows users to store or retrieve vast amount of data from different sources overnight faster than they had before. It simplifies how complex queries are done by analyzers without relying heavily upon any external equipment like disk space. Additionally, this system provides efficient access across multiple servers with minimal maintenance costs while still providing powerful analytical functions. Overall, these technical features improve overall efficiency and reliance during peak times when there may have many more requests being processed simultaneously compared against what was previously possible due to limited hardware capacity.

Problems solved by technology

The problem addressed by these inventions relating to analyzers like BigData Analyzers or Business Intelligence tools involves storing huge amounts of data on disk drives with slow access speeds due to their size and complexity. Additionally, there may also be issues associated with older systems where only partial updates can be done without affecting previous versions.

Method used

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  • Method and device for realizing OLAP analysis based on ClickHouse
  • Method and device for realizing OLAP analysis based on ClickHouse
  • Method and device for realizing OLAP analysis based on ClickHouse

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Embodiment Construction

[0031] 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. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0032] figure 1 It is a flowchart of a method for realizing OLAP analysis based on ClickHouse according to an embodiment of the present invention, such as figure 1 As shown, the method includes the following steps:

[0033] S1, receive kafak data in real time through ClickHouse's kafka engine table.

[0034] Further, receiving kafak data in real time through ClickHouse's kafka engine table may include: creating ClickHouse's kafka engine table to connect unbo...

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Abstract

The invention provides a method and device for achieving OLAP analysis based on ClickHouse. The method comprises the steps of receiving kafka data in real time through a kafka engine table of the ClickHouse; carrying out data partitioning on the kafak data; carrying out TTL management on the partitions; carrying out data fragmentation; indexing a primary key; generating dynamic code. Kafka data isreceived in real time through a kafka engine table of ClickHouse, big data processing is conducted in a database mode, the method is simpler and easier to use, maintenance is easy, the query speed ishigh, through data partition TTL management, the problem of data storage resource wasting is solved, through data fragmentation, the large-scale parallel computing capacity of a cluster is improved,and a query result is quickly returned. And moreover, transverse linear expansion can be realized, and a large-scale distributed cluster is constructed, so that the capacity of processing mass data isachieved.

Description

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Claims

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Application Information

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Owner CHANGZHOU MICROINTELLIGENCE CO LTD
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