Methods for operation fragmentation with metadata serialization in query processing pushdowns are performed by systems and devices. A compute node receives a query directed to database data, and generates query text fragments. Portions of metadata of the database are read from different page servers, and are serialized by the compute node. Page identities of data pages in a page server that stores the data are determined from a page index at the compute node, and the compute node provides the text fragments, the serialized metadata, and the page identities to the page server storing the data. The page server compiles the text fragments based on the serialized metadata to generate an executable query plan for the query. The page server initializes and performs execution of the executable query plan against the data as a pushdown query operation, and a result of pushdown query operation is provided to the compute node.

A data layout model generation system generates, with reinforcement learning, a node configuration and a data layout key in a distributed parallel database. This system includes a sample acquisition processor that acquires, on the basis of a predetermined acquisition method, sample data from data stored in the distributed parallel database, a data layout estimator having, as states in the reinforcement learning, the node configuration and the data layout key including information regarding an order of sorting columns that constitute the data and information regarding a method for distribution between nodes, the data layout estimator estimating layout of the data on the basis of the state and the sample data, a reward calculator that calculates a reward in the reinforcement learning on the basis of a result obtained by estimating the layout of the data, the node configuration, and a processing cost of a query executed on the distributed parallel database.

A method for workload balancing is implemented in a computer system including a primary database system and a secondary database system, the secondary database system being configured as a backup system for the primary database system. The method includes compiling a query received from a client application. The query indicates one or more source tables have corresponding replicate tables. The compiling comprises replace the one or more source tables with the corresponding replicate tables. The method can generate a query execution plan based on the compiled query, determine a per-table result lag based on minimum commit times of the corresponding replicate tables, and compare the per-table result lag with a predefined threshold. Responsive to a determination that the per-table result lag exceeds the predefined threshold, the method can recompile the query by falling back to the one or more source tables from the corresponding replicate tables.

A method including obtaining resource overheads according to feature information of a received query request; according to the resource overheads and a compute node resource, dynamically adjusting a compute node in a resource pool; and querying, by using the compute node, data corresponding to the query request. A compute node in a resource pool may be dynamically adjusted, so that the compute node in the resource pool may process all the received query requests, and therefore, the processing efficiency and a resource utilization rate of the compute node are more effectively improved, such that the compute node may more efficiently perform parallel processing on the multiple query requests, and the utilization rates of a CPU resource, a memory resource and a network bandwidth resource are increased, thus achieving better effect from the perspectives of overall computing resource and user query load and improving the usage experience of a user.

A computer-implemented method for quality inspection of a component of a manufacturing device includes obtaining operational data relating to operation of the manufacturing device. The operational data includes a time series of one or more physical properties of the manufacturing device. Status data relating to a component of the manufacturing device is obtained. The status data includes events relating to and/or characteristic properties relevant for utilization of the component within the manufacturing device. The computer-implemented method includes labelling one or more subsets of the operational data by associating one or more of the events and/or characteristic properties to the one or more subsets and providing the one or more subsets as labelled training data for training a machine learning model. The machine learning model serves for outputting a quality indicator based on the labelled training data input. The trained machine learning model is provided for quality inspection.

A method for automated data access management can include creating a project that manages data access to data sources by a plurality of users, wherein each user has user attributes indicating data access policies for the data sources. The method can also include performing project equalization for the project, wherein the project equalization determines a set of user attributes shared by the users. Additionally, the method can include modifying the user attributes of each user for the project, wherein the user attributes of each user are modified to conform to the set of user attributes determined by the project equalization, and detecting a query to retrieve data from the data source. The method can include modifying the query to produce a modified query by applying the modified user attributes associated with the project to the query and retrieving the data from the data source based on the modified query.

A method for processing a query for data stored in a distributed database includes receiving, at an edge device, the query for data stored in the distributed database from a query device. The method includes causing, by the edge device, the query to be stored on a dynamic ledger maintained by the distributed database. The method includes detecting, by the edge device, that summary data has been stored on the dynamic ledger. The method includes generating, by the edge device, an approximate response to the query based on the summary data stored on the dynamic ledger. The method includes transmitting, to the query device, the approximate response.

A computer-implemented method for propagating queries across a plurality of datasources that includes receiving user input via an administrative user interface. The input at least in part defines a plurality of asset paths within the datasources. A plurality of adapters corresponding to the datasources is automatically invoked and the input is automatically consolidated via the adapters for collective invocation in response to queries. A search query is received via an application user interface and the datasources are automatically queried at least in part by invoking the adapters and passing the input and the search query to the adapters. Responsive results for the search query from at least one of the datasources are automatically presented at an end user computing device.

A processor may receive a request with a column-oriented operation. The query request may be related to updates to a row-oriented database based on the query request previously performed on the row-oriented database. The processor may determine the amount of time for replicating the updates to a column-oriented database. If the amount of time for replicating the updates to the column-oriented database is greater than a threshold amount of time, then the processor may create a transient file with the updates. The transient file may be in a format that is recognized by the column-oriented database. The processor may query the column-oriented database based on the query request and the transient file.

A method, system, and computer program product for conserving resources in segment trend analytics query processing using event data. A set of events of an entity is aggregated and sorted from earliest to last, and sequentially processed to incrementally set a subset therefrom. A predicate function for determining segment membership is applied respective of a linear timeline of events of the subset represented by a time of an event processed. A data record comprising identification of the entity, time, and respective segment is generated and stored. Data records are aggregated by respective identification of a segment and a time comprised therein, and at least one analytic measure respective of entities which identification thereof is comprised therein, is calculated and stored. An indication of the at least one analytic measure calculated respective of a segment and a time queried is returned, whereby determination of a trend of the segment is enabled.