13 results about "Query tree" patented technology

Implementations described herein relate to systems and methods to generate a response to a business intelligence question received from a user. In some implementations, a computer-implemented method may include receiving the question as a natural language string, determining one or more fragments based on the natural language string, identifying one or more query operators based on the one or more fragments, constructing a structured query tree based on the one or more query operators, executing at least a portion of the structured query tree on a data source, receiving, from the data source, an output result based on the execution, generating the response based on the output result, and providing the response to the user.

The invention belongs to the technical field of data query, and relates to a distributed data tracking method based on a micro-service architecture, which comprises the following steps: S1, performing task configuration based on a query demand, and constructing an associated query task crossing a plurality of micro-service systems into a query tree; s2, traversing and executing the query tree from a root node, and executing the following steps on the traversed current node: obtaining an intermediate result data set of a front node, and extracting values of predefined association key fields from the set to form an association key value list; binding the associated key value list and an external input parameter as a corresponding placeholder in a pre-configured SQL template of the current node, and generating an executable SQL statement; the result data obtained by executing the SQL statement and the intermediate result data of the front node are associated and merged to form new intermediate result data; and S3, performing output processing after traversal is completed. The problems of poor real-time performance, unstable performance and large resource consumption during database association query are solved.

Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.

The application relates to the technical field of database systems and data governance, in particular to a multi-source data relationship acquisition method based on a database kernel. The method comprises the following steps: in the analysis and parsing stage, table and column information of a target SQL query statement is extracted, and table-level and column-level initial dependency relationships are identified; in the rewriting stage, whether rewriting has an impact is analyzed, if yes, the initial dependency relationships are updated, and intermediate dependency relationships are obtained; in the optimization stage, a target path is determined according to initial costs, blood relationship complexity, blood relationship capture completeness and a preset blood relationship influence coefficient of each path corresponding to a query tree, and the intermediate dependency relationships are replaced or supplemented according to table-level and column-level blood relationship information extracted from the target path, so that static dependency relationships are obtained; in the execution stage, dynamic blood relationship information is captured, and the dynamic blood relationship information and the static dependency relationships are combined, so that target dependency relationships are obtained. The application can improve the accuracy and completeness of acquired data blood relationship information.

The present application discloses a method, system, and computer system for managing lineage data for data entities. The method includes generating lineage data, wherein generating the lineage data, and storing and indexing, in a data structure, the lineage data in association with the selected data entity. The generating the lineage data includes selecting a selected data entity, obtaining a query tree that was used to generate the selected data entity, and determining lineage data for the selected data entity based at least in part on the query tree.

This invention relates to the field of data processing. To address the problem of low efficiency in relational queries after database sharding and table partitioning, it provides a fast query method for tree-like relationships in massive code data. The code association table pre-stores all ancestor-descendant relationships, and the reverse linked list pre-stores the complete path, eliminating the need for recursion or multiple joins during queries. The partition key ensures that all queries are executed within a single shard, resulting in single code queries ≤20ms, tree queries ≤2 times, and query times ≤50ms for database access, improving performance by tens of times compared to traditional recursive queries.

The application relates to an ID fuzzy query method and device, electronic equipment and a storage medium. The method comprises the following steps: establishing an ID query tree; when a target message to be queried is received, determining the first target byte length corresponding to the ID of indefinite length in the target message; determining the first byte length group to which the first target byte length belongs from a plurality of preset byte length groups and determining the first preset byte length corresponding to the first byte length group; extracting the first N bytes from the target message, wherein N is the first preset byte length; determining the hash value of the first N bytes to obtain the target hash value corresponding to the ID of indefinite length in the target message; and according to the target hash value, querying the ID query tree and the prefix subset ID corresponding to each preset hash value to obtain the fuzzy query result corresponding to the ID of indefinite length in the target message. The application improves the efficiency of the query of the ID of indefinite length.

The application provides a database query processing method, a storage medium and a computer device, and the processing method comprises the following steps: obtaining a query statement, and performing analysis on the query statement to obtain a query tree of the query statement; performing traversal on tables involved in the query tree to obtain a pre-generated aggregation index on the tables; replacing a matching sub-tree on the query tree, which is matched with a query sub-tree, with the query sub-tree to obtain an optimized query tree; and generating an execution plan of the query statement according to the optimized query tree. When a statistical query is processed, the query sub-tree is used to perform the query according to the scheme of the application, so that the data table does not need to be scanned and complex aggregation operations are not needed, thereby greatly shortening the query execution time of the query statement and reducing the occupation of hardware resources.

The invention discloses a data query recommendation method and device for a digital cockpit, equipment and a storage medium, and the method comprises the steps: obtaining historical query data, and constructing a query tree according to the historical query data; simulating user interaction through Monte Carlo tree search, generating reinforcement learning training data, and training a reinforcement learning algorithm by using the reinforcement learning training data; performing query recommendation optimization on the query tree by using the trained reinforcement learning algorithm to construct a query recommendation agent model; and receiving an input query condition by utilizing the query recommendation agent model, and generating a corresponding query recommendation result. The query recommendation agent model is trained by simulating user behaviors and representing the search space, so that the exploration process of a user in a complex data environment is enhanced, and by introducing the reinforcement learning technology, the query process and the analysis efficiency are optimized, the data query recommendation efficiency and precision of the digital cockpit are improved, and the user experience is improved. And the user experience and the data exploration capability are greatly improved.

The application discloses a kind of multi-set model inter-collection mapping methods: mapping information is defined, mapping first needs to use script definition collection mapping mapping condition, mapping source model, the query tree between source model and mapping relationship;Mapping information is parsed, after the device starts, the parsing work of script is carried out in initialization stage, and the collection mapping information parsed forms collection mapping pool, for subsequent collection mapping use;According to the parsing result of mapping information, collection mapping processing is carried out.The application extracts the public paradigm in complex collection mapping, uses the scheme of framework coding plus script mapping, and solves complex technical problems such as data set definition, data search, condition judgment, condition mapping, etc., once;Make private model can adapt to open model, impact on existing private model is smaller, compatible with existing architecture, smooth evolution, while making the device embrace openness.The application also provides a corresponding multi-set model inter-collection mapping device.

This invention relates to database query execution optimization. Specifically, it describes techniques for optimal execution based on query interpretation translated into a domain-specific language (DSL) using optimizations such as partial evaluation, abstract syntax tree (AST) rewriting, just-in-time (JIT) compilation, dynamic analysis, speculative logic, and Futamura projection. In an embodiment, a database management system (DBMS) hosted on a computer generates a query tree representing a database query, which contains expressions represented by subtrees of the query tree. The DBMS generates a sequence of DSL instructions representing the subtrees. During the execution of the database query, the sequence of DSL instructions is executed to evaluate the expressions. In an embodiment, the AST is generated from the sequence of DSL instructions. In an embodiment, the DSL AST is optimally rewritten based on a runtime feedback loop that includes dynamic profiling information.

The invention discloses a data query recommendation method and device, computer equipment and a storage medium, and the method comprises the steps: collecting historical query data, and constructing a query tree according to the historical query data; wherein the historical query data comprises historical query conditions and historical query recommendation results; historical query conditions are set as input features of a deep learning framework, historical query recommendation results are set as output tags of the deep learning framework, model parameters are optimized through a gradient descent algorithm to generate a training data set, and then the deep learning framework is trained through deep learning training data; performing query recommendation optimization on the query tree by utilizing the trained deep learning framework to construct a query recommendation target model; and receiving an input target query condition by utilizing the query recommendation target model, and generating a corresponding query recommendation result. According to the method, the problems of data query and analysis under the urban data multi-source heterogeneous characteristic can be effectively solved, and the data query effect is improved.

The application discloses a shared query tree for complex event query and a construction method and a query method thereof. When the shared query tree is constructed, firstly, query instances of multiple complex events are reconstructed, then the multiple reconstructed queries are combined by adopting a shared prefix query node mode to obtain the shared query tree. The shared query tree can be regarded as a query containing multiple complex event queries, the semantics of the multiple queries are unified into one query, and the multiple queries are connected by sharing the prefix. The query nodes in the shared prefix only need to complete one event processing, thereby providing services for all single queries with the common query nodes, reducing repeated calculation of the complex event query, and greatly improving the processing efficiency of the complex event.