11 results about "Fact table" patented technology

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

Arrangements for partition handling for multi table scan semi join operations are provided. Partition information of a first logical relation may be determined. Partition information of a first physical operator may be determined based on the partition information of the first logical relation. The partition information of the first physical operator may be stored in a data structure which includes partition information of a fact table and of each reducer in a predefined sequence. Partition information of a second logical relation may be determined. The partition information of a second physical operator may be determined based on the partition information of the second logical relation and the partition information of the first physical operator. The partition information of the second physical operator may be stored in the data structure. Execution of the second physical operator may be performed using the stored partition information, skipping mappings between pairs of partitions.

This invention relates to the field of rural economic data analysis technology, specifically an artificial intelligence-based method for rural economic data analysis. The method includes: delineating an economic data perception domain in a geographic information system based on the administrative division vector data of the target administrative village; collecting multi-source heterogeneous economic data through a protocol parser of an agricultural IoT terminal and converting it into standardized economic behavior data; extracting entities using natural language processing technology to generate a structured rural economic behavior fact table; inputting the fact table into a pre-trained economic activity association model and constructing a rural industry relationship graph using a graph embedding algorithm; and calculating the centrality index of economic entities based on the graph topology to identify core operating entities. This method enables accurate processing and association analysis of rural economic data, clearly presenting industry relationships and providing effective technical support for rural economic analysis.

The present disclosure relates to a data processing method, platform, computer readable storage medium and electronic device, and relates to the technical field of big data processing. The method comprises the following steps: based on a preset standardized data interface, extracting original data to a message engine; wherein the original data comprises terminal data generated by a terminal device and / or system data generated by an application system (S110); reading the original data from the message engine and storing the original data in a distributed file system to form a fact table (S120); storing the fact table in a columnar database and obtaining target column data required for generating a target chart from the columnar database (S130); and generating the target chart according to the target column data (S140). The present disclosure improves the accuracy of data processing results.

The application relates to a management and query method for the same index of multi-fact tables based on an index center, which performs index definition on the same indexes of various source tables, and arranges the various source tables according to the data volume scale from small to large; according to the index query condition input by a user, the query dimension is acquired, and the source table matched with the query dimension is found and taken as a target source table; then, index query is carried out based on the target source table, and the corresponding index calculation result is returned. According to the screening dimension range of the index query condition, the available analysis dimensions on the various source tables are dynamically matched once, the current source table is selected to carry out data query when the matching succeeds, the best source table meeting the business requirement is found, and the index query efficiency is improved. The index platform does not need to create multiple indexes to respectively map different fact tables, one index is used for mapping, the query table is positioned according to the query condition and a preset table acceleration sequence, and the index management is simpler, and the index analysis is more intelligent.

The application discloses a kind of intelligent diagnosis and decision support method of coronary heart disease angina TCM syndrome factor based on HIS, it is related to medical information and TCM diagnosis and treatment technical field, the method will coronary heart disease angina TCM syndrome factor diagnostic criteria be deconstructed into standardization diagnostic item, build machine-readable weight rule base containing score, threshold and severity grading rule, response syndrome differentiation operation generates electronic collection form, receives structured data storage to the TCM syndrome factor fact table associated with patient main index and medical record, after structured data is submitted, trigger intelligent computing engine verification essential item, total score is accumulated, determine the establishment of syndrome factor and severity, through TCM diagnosis and treatment knowledge graph push personalized treatment or nursing suggestion in clinical business node, and continuously update rule base and knowledge graph through clinical data feedback.The application integrates corresponding function module to realize and deeply fuse with hospital information system, improves the standardization and efficiency of diagnosis and treatment, and has strong practicality.

The application discloses a system and method for multi-dimensional data correlation analysis based on unified modeling, and relates to the technical field of intelligent analysis of big data; the system comprises the following steps: step 1, semantic model construction is performed; step 2, query compilation and optimization are performed; step 3, query execution and scheduling are performed; step 4, interactive analysis and visualization are performed; end-to-end full-process visual display is provided by using a multi-dimensional report designer MRD, and interactive drilling and narrative analysis are supported; and step 5, closed-loop optimization is performed; the complexity of a bottom-layer data structure is shielded by the semantic model, automatic correlation analysis across fact tables is supported, and thus a business personnel can independently complete deep data exploration and decision support without mastering professional techniques such as SQL.

The invention discloses an official car operation data analysis method based on a multi-source heterogeneous data fusion and treatment technology, and relates to the technical field of official car operation data analysis, and the method comprises the following steps: accessing business data and GPS track flow data, and obtaining decision guidance data; correcting the real-time GPS track flow data based on an official car track anomaly detection algorithm of RVM; associating the decision guidance data with the corrected real-time GPS track flow data to generate a travel fact table; and storing the travel fact table in an HDFS (Hadoop Distributed File System) in a Parquet format for offline analysis, and carrying out real-time query by virtue of Phoenix and HBase. Through multi-source heterogeneous data fusion and association, the problem of historical business data islands is solved.

Arrangements for partition handling for multi table scan semi join operations are provided. Partition information of a first logical relation may be determined. Partition information of a first physical operator may be determined based on the partition information of the first logical relation. The partition information of the first physical operator may be stored in a data structure which includes partition information of a fact table and of each reducer in a predefined sequence. Partition information of a second logical relation may be determined. The partition information of a second physical operator may be determined based on the partition information of the second logical relation and the partition information of the first physical operator. The partition information of the second physical operator may be stored in the data structure. Execution of the second physical operator may be performed using the stored partition information, skipping mappings between pairs of partitions.

This invention discloses an auxiliary decision-making and precision diagnosis system based on interpretable multimodal reasoning, belonging to the field of medical informatics and clinical decision support technology. It includes: a data acquisition module for acquiring DKD clinical medical knowledge and multi-source patient data; a feature extraction module for processing the multi-source patient data to obtain a time-series data view of the patient; wherein the time-series data view includes: a fact table and a wide index table; multiple patient time-series data views constitute a structured feature warehouse; a knowledge graph construction module for constructing a medical knowledge graph based on DKD clinical medical knowledge; and a local reasoning module for constructing a local reasoning model and performing retrieval reasoning based on the structured feature warehouse and the medical knowledge graph to obtain the decision result.

Disclosed in the present application are a data warehouse creation method and apparatus based on a knowledge graph, and a computer device and a storage medium. Specifically, the data warehouse creation method based on a knowledge graph disclosed in the present application comprises: creating a data warehouse fact table layer, wherein the data warehouse fact table layer comprises a first node, and the first node corresponds to data in an external database; creating a data warehouse service layer, wherein the data warehouse service layer comprises a second node, and the second node corresponds to data obtained after nodes of the data warehouse fact table layer are aggregated; and creating a data application layer, wherein the data application layer comprises a third node, and the third node corresponds to data obtained after nodes of the data warehouse service layer are aggregated. By means of the method, the present application provides a new solution for creating a data warehouse on the basis of a knowledge graph, and allows the creation of subject-based aggregated wide tables without extracting original data into a local database, thereby enhancing both data sensitivity and the convenience of data warehouse creation operations.