Data access method and device for distributed graph learning architecture
A data access device and data access technology, applied in other database retrieval, other database indexing, electronic digital data processing, etc., can solve the problem of waste of memory space in graph learning equipment
Active Publication Date: 2021-12-17
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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According to this processing method, it is necessary to store a complete backup of the Master data in the memory of the graph learning device where each Mirror node is located, resulting in a waste of memory space for the graph learning device
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[0048] The subject matter described herein will now be discussed with reference to example implementations. It should be understood that the discussion of these implementations is only to enable those skilled in the art to better understand and realize the subject matter described herein, and is not intended to limit the protection scope, applicability or examples set forth in the claims. Changes may be made in the function and arrangement of elements discussed without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as needed. For example, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, features described with respect to some examples may also be combined in other examples.
[0049] As used herein, the term "comprising" and its variants represent open terms meaning "including but not limited to". The...
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Embodiments of this specification provide a data access method and device for a distributed graph learning architecture. In this data access method, the graph nodes at the first graph learning device are grouped into a plurality of graph node groups with priorities, and the priority of each graph node group is determined based on graph node dependencies, which are used for Reflects the dependency of graph nodes with respect to mirror nodes during graph learning. Based on the graph node dependencies, determine the mirror nodes that each graph node group depends on; and according to the priority of the graph node group, allocate cache space for the mirror nodes that each graph node group depends on from the public buffer of the first graph learning device . For the graph node that has completed the cache space allocation, initiate a data access process to the second graph learning device where the corresponding graph node of the mirror node that the graph node depends on is located; and cache the acquired graph node data in the allocated cache space middle.
Description
technical field [0001] The embodiments of this specification generally relate to the field of graph data processing, and in particular, relate to a data access method and a data access device for a distributed graph learning architecture. Background technique [0002] In the graph learning architecture, if the graph nodes used are very large-scale graph nodes, the graph learning architecture needs to be deployed as a distributed graph learning architecture, and the graph nodes are distributed to each distribution in the graph learning architecture through the graph partitioning algorithm. graphic learning device. When the graph nodes are distributed to each distributed graph learning device, there will be critical nodes among the distributed graph nodes. Part of the neighbor nodes of the critical node are stored in the graph learning device where the critical node is located, and the rest of the neighbor nodes of the critical node are stored in other graph learning devices....
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IPC IPC(8): G06F3/06G06F16/901
CPCG06F3/0656G06F3/0644G06F3/061G06F3/067G06F16/9024G06N20/00G06F12/0875G06F3/0608G06F3/0683
Inventor 郭志强
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD