A method for a first set of processors and a second set of processors comprises, the first set of processors processing a set of queries, as a result of a change in utilization of the first set of processors, processing the set of queries using the second set of processors. The change in processors is independent of a change in storage resources, the storage resources shared by the first set of processors and the second set of processors.

An Artificial Intelligence (AI)-based data processing system processes current data to determine if the quality of the current data is adequate to be provided to data consumers and if the quality is adequate, the current data is further analyzed to determine if an impacted load including changes to dimension data of the current data or an incremental load including changes to fact data of the current data is to be provided to the data consumers. Depending on the amount of data to be provided to the data consumers, processing units (PUs) may be determined and assigned to carry out the data upload. Various machine learning (ML) models that are used to provide predictions from the current data are analyzed to determine the quality of predictions and if needed, can be automatically retrained by the data processing system.

A method includes generating array field distribution data for an array field of a dataset. A query expression for execution that includes a query predicate indicating the array field of the dataset is received. The array field distribution data for the array field is utilized to generate query plan data for the query expression based on the query expression including the query predicate indicating the array field. Execution of the query expression is facilitated in accordance with the query plan data.

The disclosed implementations include a method performed by a data intake and query system. The method includes receiving a search query at a search head, the search query including a branching operation between sets of data, generating a first subquery and a second subquery corresponding to the sets of data for execution by a search node, generating instructions for an intermediary node to combine partial results of the first subquery and the second subquery and instructions to concurrently communicate the subqueries to a search node, and executing the query by providing the instructions for the intermediary node to the intermediary node and the subqueries to the search node, the intermediary node receiving sets of partial search results for the subqueries, performing at least a portion of the branching operation on the partial results, and communicating the combined results to another intermediary node or the search head.

A method and system for executing database queries in parallel using a shared metadata store. The metadata store may reside on a master node, where the master node is the root node in a tree. The master node may distribute query plans and query metadata to other nodes in the cluster. These additional nodes may request additional metadata from each other or the master nodes as necessary.

A system includes an interface and a processor. The interface is configured to receive an indication that a change has occurred to partition data on a first node, wherein the partition data is stored on a partition on the first node. The processor is configured to: determine whether the change to the partition data causes a change to a predetermined partition result of a set of predetermined partition results stored by the partition; and in response to a determination that the change to partition data affects the predetermined partition result stored by the partition: determine a new value for the predetermined partition result; store the new value; and provide an indication to a service node that the new value for the predetermined partition result has been determined, wherein the service node is selected by a client application system to manage execution of a task.

An information processing system includes a first information processing device configured to accept an input of a query to be processed, and a second information processing device configured to execute the query for each of a plurality of tasks in parallel. The first information processing device determines whether or not an external database server contains records targeted by the query, and transmit the query and a connection information for accessing the external database server to the second information processing device. The second information processing device connects to the external database server based on the connection information received from the first information processing device, acquires information indicating a storage status of the records targeted by the query among records stored in the external database server, and determines a processing target range for each of the plurality of tasks relevant to the records targeted by the query, based on the acquired information.

Described herein is a graphics processing unit (GPU) comprising a first processing cluster to perform parallel processing operations, the parallel processing operations including a ray tracing operation and a matrix multiply operation; and a second processing cluster coupled to the first processing cluster, wherein the first processing cluster includes a floating-point unit to perform floating point operations, the floating-point unit is configured to process an instruction using a bfloat16 (BF16) format with a multiplier to multiply second and third source operands while an accumulator adds a first source operand with output from the multiplier.

A method includes: obtaining a multi-type service data report that requires data analysis; analyzing and processing the multi-type service data report to determine N types of service data that fluctuate in the multi-type service data report, where N is an integer greater than or equal to 1; and screening out abnormal service data that abnormally fluctuates from the N types of service data and exporting the abnormal service data. A system for big data analysis is further provided. Instead of simply regarding fluctuant service data as abnormal service data, the method and the system determine abnormal service data based on the N types of fluctuant service data in the multi-type service data report. This reduces overreactions and helps reasonably measure service data. Therefore, service data can be thoroughly analyzed.

A record processing and storage system operates by: generating a set of pages from a plurality of row data via a plurality of processing core resources, wherein each processing core resource in the plurality of processing core resources generate a corresponding subset of the set of pages, independently from and in parallel with processing of other subsets of the set of pages via other ones of the plurality of processing core resources; facilitating performance of a single storage transaction to store the set of pages; identifying a page set interval based on a plurality of row number intervals of the set of pages; generating, based on completing the single storage transaction, row durability data indicating a least favorably ordered row number of a plurality of row numbers corresponding to the plurality of row data; and transmitting the row durability data to a computing device associated with the plurality of row data.