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Distributed system multi-target cluster mounting strategy automatic matching method and system

A distributed system, automatic matching technology, applied in transmission systems, database distribution/replication, electrical components, etc., can solve problems affecting data read and write performance, etc., to improve file read and write performance, improve read and write speed, and highlight the essence effects of sexuality

Active Publication Date: 2021-01-05
INSPUR SUZHOU INTELLIGENT TECH CO LTD
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AI Technical Summary

Problems solved by technology

If the user does not have a deep understanding of the Hadoop RBF multi-target mounting strategy, and does not specify a mounting strategy when mounting, the system will mount with the default strategy, and this default mounting strategy is not the optimal strategy, which will affect data reading. The problem of writing performance, the present invention is a distributed system multi-target cluster mounting strategy automatic matching method and system

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  • Distributed system multi-target cluster mounting strategy automatic matching method and system
  • Distributed system multi-target cluster mounting strategy automatic matching method and system
  • Distributed system multi-target cluster mounting strategy automatic matching method and system

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Embodiment Construction

[0058] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention. Key terms appearing in the present invention are explained below.

[0059] Such as figure 1 As shown, the embodiment of the present invention provides a distributed system multi-target cluster mounting strategy automatic matching method, including the following steps:

[0060] S1: The distributed system client submits a file writing req...

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Abstract

The invention provides a distributed system multi-target cluster mounting strategy automatic matching method and system. The method comprises the following steps: a distributed system client submits afile writing request to a router; after the request is received, the router queries mounting strategy information of a distributed system client path from the state storage module, analyzes an optimal mounting strategy according to the queried mounting strategy information and sends the optimal mounting strategy to the distributed system client; when the distributed system client receives the optimal mounting strategy, whether the strategy needs to be modified or not is determined; if so, a strategy modification command is executed; the modified path strategy is stored into a state storage module; the router queries the sub-clusters meeting the requirements from the state storage module, forwards the request to a running management node, and starts to execute file writing operation; if not, the request is forwarded to the running management node, and execution of the file writing operation is started. Load balance can be guaranteed, cluster resources are reasonably used, and file read-write performance is improved.

Description

technical field [0001] The invention relates to the technical field of distributed system storage, in particular to an automatic matching method and system for multi-target cluster mounting strategies of a distributed system. Background technique [0002] In Hadoop, the number of metadata (files + blocks) stored by Namenode in memory will be limited by the heap size of the JVM where Namenode is located. To increase the storage capacity of the cluster, Namenode must be expanded, but the vertical expansion of NameNode memory will lead to service startup. It takes too long. Taking 50GB of data as an example, it takes more than half an hour to start the service; the frequency of Full GC increases and the risk increases, and the pause time of the application will reach hundreds of seconds. In order to solve the drawbacks of Namenode vertical expansion, Hadoop successively released HDFS (Hadoop Distributed File System, Hadoop Distributed File System) Federation and Hadoop RBF (Rou...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/08G06F16/27
CPCH04L67/10H04L67/1097G06F16/27
Inventor 崔新辉
Owner INSPUR SUZHOU INTELLIGENT TECH CO LTD
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