Cloud computing index recommendation method and system

Abstract

The invention provides a cloud computing index recommendation method and system. The method comprises: obtaining unit computing cost and unit storage cost of a currently used cloud computing server in unit time; obtaining all historical query statements of the target user, extracting common features of all the historical query statements, and determining query indexes corresponding to the historical query statements according to the common features; determining the query cost of each query index according to the frequency and time of querying the database by the query indexes and the used computing resources; based on the obtained current query statement of the target user, determining a plurality of current query indexes corresponding to the current query statement; determining the total cost corresponding to each current query index through the unit calculation cost, the unit storage cost, the calculation resource usage amount and the usage time according to the plurality of current query indexes; and recommending the target query index to the target user. The method of the present disclosure exchanges computing resources with storage resources by recommending an index.

Description

technical field [0001] The present disclosure relates to the technical field of cloud computing, and in particular to a cloud computing index recommendation method and system. Background technique [0002] In recent years, the cloud computing industry has advanced by leaps and bounds, and more and more enterprises have begun to embrace the cloud environment on a large scale, whether it is OLTP (On-Line Transaction Processing, online transaction processing) applications or OLAP (On-Line Analytical Processing, online analytical processing ) applications are gradually migrating to the cloud, and mainstream cloud vendors provide reliable and elastic computing services and storage services to meet customer needs. [0003] One trend of the current big data architecture is the separation of computing and storage. Under the background of the cloud environment, computing services are deployed on elastic cloud servers provided by cloud vendors, and storage services can choose to use c...

AI Technical Summary

Problems solved by technology

[0004] After observing the product pricing of multiple mainstream cloud computing service providers, it can be seen that the cost of block storage is far lower than the cost of computing. In today's OLAP analysis field, many software systems adopt the MPP architecture. MPP ( The core idea of ​​MassivelyParallel Processing (Massively Parallel Processing) is to distribute tasks to multiple servers and nodes in parallel. In the cloud environment, when processing ultra-large-scale data sets, each query consumes a large amount of computing resources. Even repeated query analysis requirements will generate high analysis costs.

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