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Dynamic planning-based collaborative optimization method for distributed database systems

A distributed data and dynamic programming technology, applied in the field of Internet cloud computing and big data, can solve the problems of difficult and accurate modeling of high-concurrency task plans and the impact of optimization effects, and achieve strong real-time processing capabilities, good load balance, and high efficiency. high effect

Active Publication Date: 2018-06-15
中润普达(十堰)大数据中心有限公司
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Problems solved by technology

However, the above ideas take into account the synchronization of concurrent tasks, the additional overhead of the optimization process itself, the competition of multiple similar resources, and data skew and delay, making it difficult to accurately model high-concurrency task plans. In task planning, it will have a subversive impact on the optimization effect

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  • Dynamic planning-based collaborative optimization method for distributed database systems
  • Dynamic planning-based collaborative optimization method for distributed database systems
  • Dynamic planning-based collaborative optimization method for distributed database systems

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Embodiment Construction

[0046] refer to figure 1 , the present invention is based on the dynamic programming distributed database system collaborative optimization method comprising the following steps:

[0047] A. Using the block method based on data flow, block the indistinguishable relationship between the combined operation of the distributed data corpus on the data unit according to the planned task sequence into a series of data primitives that cannot be further divided:

[0048] In the field of big data processing, the biggest feature of computing resources, data, and processing request points is distribution, and the data shows a trend of unstructured, so it is expected that the data flow block method can play a good role in this type of distributed database system , it is necessary to design a data block method that fully considers the above problems, has low communication cost and reliable results.

[0049] In this method, the quaternary information system description method is used to exp...

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Abstract

The invention discloses a dynamic planning-based collaborative optimization method for distributed database systems. The method comprises the following steps of: dividing a distributed data set into data elements which cannot be divided by adoption of a data flow blocking method; optimizing concurrent processing tasks; optimizing load balance of distributed resources; and dynamically scheduling plan tasks. According to the method, a dimensionality reduction type search strategy is provided, so that the whole-course optimization of task execution plans is ensured in the multitask random processing process of distributed big data; and the method has the advantages of being high in efficiency, good in load balance, high in resource utilization rate and strong in real-time processing ability.

Description

technical field [0001] The invention relates to a dynamic programming-based collaborative optimization method for a distributed database system, which belongs to the fields of Internet cloud computing and big data. Background technique [0002] At present, in the field of concurrent task optimization of distributed databases, the common practice is to first use a general concurrent task plan expression model to describe the task plan, then give a resource cost model that needs to be consumed by the execution plan, and finally formulate the execution strategy so that the plan The task has the least cost. However, the above ideas take into account the synchronization of concurrent tasks, the additional overhead of the optimization process itself, the competition of multiple similar resources, and data skew and delay, making it difficult to accurately model high-concurrency task plans. In mission planning, it will have a subversive impact on the optimization effect. Contents...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F9/50G06F9/48
CPCG06F9/4806G06F9/5083G06F16/27
Inventor 曲逸文
Owner 中润普达(十堰)大数据中心有限公司
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