Data storage method based on compressed graph, storage medium, storage device and server
A data storage and image compression technology, applied in the computer field, can solve the problems of lack of intuitive description language, heavy sorting workload, and affecting the flexibility of map building during the map building process.
Active Publication Date: 2019-10-29
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology
[0005] (1) The mapping process of the primary key and the association process of nodes cannot be reused. For each map building operation, the corresponding data needs to be remapped to ensure the continuity of node numbers, and the associated data of nodes also needs to be rebuilt. This comes with a huge overhead;
[0006] (2) The mapping process lacks an intuitive description language
For the definition of a compressed graph, the existing technology needs to be described in the form of code, which not only increases the development cost, but also affects the flexibility of graph construction;
[0007] (3) The sorting workload involved in the construction of the map is relatively large
Method used
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Embodiment Construction
[0064] Such as figure 1 , Figure 8 Shown, the implementation step of the inventive method comprises:
[0065] S100, building a point table and importing data
[0066] The point table can be constructed by the following SQL statement:
[0067]
[0068] ENGINE=V means the point table engine, and the point table must be designated as the associated primary key, that is, the Key key, specified with the keyword Key; other columns are other attributes of the point table. Multiple point tables can be created for multiple types of points, each point table represents a point type, and the point table name is the point type name.
[0069] For example, the user point table, movie point table, and producer point table in the above figure can be established by the following statements:
[0070] create table user(name String Key, age UInt16) engine=V;
[0071] create table movie(name String Key, genre UInt8) engine=V;
[0072] create table producer(name String Key, capital UInt64)...
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The invention relates to a data storage method and system based on a compressed graph and a storage medium, and the method comprises the steps: 100, generating a point table logic definition, constructing a point table according to the logic definition, and inserting data into the point set; step 200, generating a side table logic definition, constructing a side table according to the logic definition, selecting a point table associated with the side table from the point tables, and inserting data into the side table; step 300, setting and executing a compressed graph definition command, generating a mapping logic of the compressed graph, setting a function to obtain the edge table associated with the compressed graph definition, forming an edge set group, and generating an agent structureof the point table associated with the compressed graph definition; and 400, setting and executing a compressed image reset command, and constructing the compressed image according to the mapping logic of the compressed image. According to the method, the expenditure of multiple mapping and multi-class graph building is reduced, the flexibility and representativeness of graph building are improved, and the sorting workload of repeated mapping is reduced.
Description
technical field [0001] The invention relates to the field of computer technology, and particularly designs a data storage method, storage medium, storage device and server based on a relational data compression graph construction method. Background technique [0002] Relational data is currently the mainstream structured data storage object, and its operating primitive is SQL. For multi-layer nested relational calculations, using SQL's Join operator brings a large performance loss. In order to better model and analyze complex association relationships, mainstream solutions use compressed graph structures to represent data association relationships, and use graph-based node-edge calculation operations on this structure to replace Join operations, achieving great computing performance promote. [0003] The conversion process from the current relational structure to the compressed graph structure is mainly divided into the following three steps: (1) Map the primary key attrib...
Claims
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Login to View More IPC IPC(8): G06F16/22
CPCG06F16/22
Inventor 程学旗郑天祺王征赵程张志斌刘悦赵鹏郭嘉丰
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI