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Task parameter optimization method for distributed iterative computing system

It is an iterative computing and distributed technology, which is applied in computing, digital data processing, and special data processing applications. The effect of pressure

Active Publication Date: 2016-10-12
TSINGHUA UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to propose a task parameter optimization method for a distributed iterative computing system in view of the problem that there are many task parameters in the existing distributed iterative computing system and it is not easy to configure well

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  • Task parameter optimization method for distributed iterative computing system
  • Task parameter optimization method for distributed iterative computing system
  • Task parameter optimization method for distributed iterative computing system

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[0023] The present invention proposes a task parameter optimization method in a distributed iterative computing system, which will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0024] The present invention proposes a task parameter optimization method in a distributed iterative computing system, the overall process is as follows figure 1 As shown, this method first collects the running data of the historical tasks in the distributed iterative computing system, and builds the historical database; when optimizing the task parameters, it filters the significantly irrelevant running data in the historical database according to the constraints; Calculate the similarity of the directed acyclic graph between the operating data in the corresponding historical database and the operating data after the first filter, and perform secondary filtering on the operating data whose similarity is lower than a certain threshold; fin...

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Abstract

The invention relates to a task parameter optimization method for a distributed iterative computing system, and belongs to the technical field of distributed data processing. The method comprises the following steps: firstly, acquiring operating data of a historical task in the distributed iterative computing system, and constructing a historical database; secondly, when performing task parameter optimization, performing primary filtering on significantly unrelated operating data in the historical database according to a constraint condition; thirdly, performing similarity calculation of a directed acyclic graph on operating data in the historical database corresponding to tasks to be optimized and operating data after the primary filtering, and performing secondary filtering on operating data with a similarity lower than a certain threshold; and finally, calculating and sorting results after twice filtering, and taking a task parameter corresponding to the operating data after sorting as a task parameter optimization result. The task parameter optimization method for the distributed iterative computing system provided by the invention can automatically perform task parameter optimization of the distributed iterative computing system, is a plug and play adaptive optimization method, and can obviously reduce the threshold of using the distributed iterative computing system by users.

Description

technical field [0001] The invention belongs to the technical field of distributed data processing, in particular to a task parameter optimization method in a distributed iterative computing system. Background technique [0002] Using distributed iterative computing systems to process large-scale data sets has become the main practice of data processing. Compared with traditional stand-alone data processing solutions, distributed iterative computing systems that are now popular and widely used, such as Apache Spark, use multiple machines to divide data, thereby greatly increasing the scale of data processing. Moreover, multiple machines participate in the data processing process, which increases the parallel number of data processing and speeds up the processing speed of large-scale data. [0003] Despite the above advantages, the normal operation of a distributed iterative computing system task requires reasonable task parameters. Unreasonable task parameters will reduce ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/217
Inventor 王建民龙明盛陈侨安黄向东
Owner TSINGHUA UNIV
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