A Visual Query Method for Heterogeneous Data Sources

A technology of heterogeneous data sources and query methods, applied in structured data retrieval, electronic digital data processing, database management systems, etc., can solve problems such as query overflow and query time-consuming, and achieve the effect of improving usability
CN109815283BActive Publication Date: 2020-10-09JIANGSU DAWN INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
JIANGSU DAWN INFORMATION TECH CO LTD
Publication Date
2020-10-09

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Abstract

The invention discloses a heterogeneous data source visual query method. A user selects a query range on a foreground visual interface; whether the selected data source is loaded into a presto clusteror not is judged; if the selected data source is not loaded to the presto cluster, a to-be-loaded data source is added in the presto cluster; a query statement is sent to the presto cluster, and query is completed within the selected query range; detecting whether a plug-in required by a to-be-loaded data source is a built-in data source plug-in in a preload cluster, and if so, dynamically loading a configuration file in a calog folder by the preload cluster; And if not, creating the plug-in of the to-be-loaded data source, putting the plug-in into a Preto cluster, loading the configuration file in the calog folder, and completing the loading of the data source. According to the method, different data source basic information is configured, operation of a graphical interface is adopted, adata source is dynamically loaded, and query of a presto-based heterogeneous data source is achieved.
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Description

technical field

[0001] The invention relates to the field of computer technology, in particular to a visual query method for heterogeneous data sources. Background technique

[0002] In the era of big data explosion, there are many forms of data storage, mainly structured data, semi-structured data and unstructured data. Different data are stored in different data sources, and most structured data are stored in relational data sources, the mainstream of which are domestic databases such as mysql, oracle, sqlserver, Dameng and Jincang data sources; historical data or cleaned The converted data is stored in the data sources of big data platforms such as hive or MPP data sources based on the share nothing architecture; semi-structured data, such as streaming data, are mainly stored in Kafka, and a large number of regular log files are stored in the file server. Semi-structured key-value data stored in the memory database redis. The data in different data sources needs to be i...

Claims

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