Abstract: A system and method for hierarchical database operation accelerator for scaling a single node database with a plurality of accelerator cards is provided, including: a host, receiving a query plan, generating a corresponding query operation and distributing them, receiving and processing aggregated execution results; a hierarchy accelerator module, which is connected to the host, receiving the query operation distributed and returning the aggregated execution results; the hierarchy accelerator module comprises a master accelerator card and at least one slave accelerator card, the slave accelerator card returns the execution results to the master accelerator card, by the master accelerator card completes the subsequent query operation which is aggregated and assigned by the execution results, returning the aggregated execution results to the host; the accelerator system having a multi-level storage architecture of accelerator chip on-chip cache, the accelerator card memory, the accelerator card storage, and the

Abstract: The present disclosure relates to systems, methods, and computer-readable media for determining optimal index configurations for processing workloads in a database management system. For instance, an index configuration system can efficiently determine a subset of indexes for processing a workload utilizing one or more reinforcement learning models. For example, in various implementations, the index configuration system utilizes a Markov decision process and/or a Monte Carlo tree search model to determine an optimal subset of indexes for processing a workload in a manner that effectively utilizes computing device resources while also avoiding significant interference with customer workloads.

Abstract: A distributed processing apparatus 1 includes: a selection unit 12 that lists execution plans for a query related to a plurality of database apparatuses 2 and selects any of the execution plans based on data transfer time periods of the individual execution plans; a transmission unit 13 that divides the query in accordance with the selected execution plan, and transmits instructions that include divided queries obtained by dividing the query and transfer destinations of execution results of the divided queries to the corresponding database apparatuses 2; and an output unit 14 that receives the execution result of the query from the database apparatus 2, and outputs the execution result.

Abstract: Joining data using a disjunctive operator using a lookup table is described. An example computer-implemented method can include receiving a query with a set of conjunctive predicates and a set of disjunctive predicates. The method may also include generating a lookup table for each predicate in the sets of conjunctive predicates and disjunctive predicates. The method, for each row in a probe-side table, may also further include looking up a value associated with that row in each of the lookup tables and adding the row to a results set when there is a match. Additionally, the method may also include returning the results set.

Abstract: Methods, systems, and computer programs are presented for scheduling and executing request plans using an opportunistic approach. An opportunistic scheduler generates a request plan for a request on a cloud data platform, the request plan comprising a plurality of operations and identifies a plurality of contingent operations from the plurality of operations of the request plan. The opportunistic scheduler schedules the plurality of contingent operations for execution and sets the scheduled plurality of contingent operations to execute at a specific position in the request plan. The opportunistic scheduler sets remaining operations for execution by any available thread as threads that are processing the request plan become available and processes the request plan according to the scheduled plurality of contingent operations.

Abstract: A distributed database keeps user-defined functions separate from a query engine by using a frontend. The frontend allows a user-defined function to interact with a proxy application processing interface (API) that is based on an API of the query engine. The frontend sends serialized data to the query engine in order to interact with the API of the query engine. The user-defined function is executed in security environments separate from the frontend and the query engine.

Abstract: An embodiment generates an initial set of training data from monitoring data. The initial set of training data is generated by combining outputs from a plurality of pretrained classifiers. The embodiment trains a new classification model using the initial set of training data to identify anomalies in monitoring data. The embodiment performs a multiple-level clustering of the data samples resulting in a plurality of clusters of sub-clusters of data samples, and generates a review list of data samples by selecting a representative data sample from each of the clusters. The embodiment receives an updated data sample from the expert review that includes a revised target classification for at least one of the data samples of the expert review list. The embodiment then trains another replacement classification model using a revised set of training data that includes the updated data sample and associated revised target classification.

Abstract: The subject technology receives a query, the query including a set of statements for performing the query. The subject technology populates a compilation context based at least in part the query. The subject technology invokes a compiler to perform a compilation process based on the compilation context. The subject technology performs a lookup operation on a stored plan cache for an exact match based on information from the compilation context. The subject technology, in response to determining an exact match, determines whether the particular query plan requires re-compilation based on a data dependent optimization. The subject technology determines whether a plan cache entry corresponding to the particular query plan includes a data property constraint. The subject technology determines whether the data property constraint still holds based on a set of data properties.

Abstract: A system and method for processing of queries including receiving a query including a set operation and a sort operation, wherein the set operation includes a first data structure and a second data structure and the sort operation requests a result set that is sorted based on a column or attribute of the first data structure and a column or attribute of the second data structure; generating a query plan in which a sort operation occurs prior to the set operation; determining a first, partial set of one or more resultant rows responsive to the query; sending the first, partial set of one or more resultant rows responsive to the query to a client; determining a second, partial set of one or more resultant rows responsive to the query; and sending the second, partial set of one or more resultant rows to the client.

Abstract: Technologies are provided for tracking learning progress of an end user of a cloud computing platform when the end user is not registered with an external learning platform that provides an external learning application. In response to the end user interacting with virtual learning entities provided at the cloud computing platform, learning progress information with respect to the external learning application is generated. When a user service of the external learning platform receives a request to persist the learning progress information for the end user, the user service can determine whether a corresponding user account exists at the external learning platform that corresponds to the end user. If a corresponding user account does not exist, the user service can automatically provision an escrow user account that is associated with the end user. The escrow user account persists the learning progress information of the end user.

Abstract: Techniques described herein propose a new RIDDecode operator in a QEP that uses ROWID lookup and fetch, instead of dictionary decoding, to retrieve decoded values, in order to reduce memory pressure and speed up processing.

Abstract: A computer-implemented method dynamically switches access plans for a query during concurrent query execution. The method includes receiving a first query configured to be processed by a database system. The method also includes generating, for the first query, an access plan for each of identified resource sets. The method includes determining a first set of available resources that represent an available capacity for the database system. The method further includes selecting a first resource set of the one or more resource sets, where the selecting is based on the first set of available resources being closest to the first resource set. The method also includes selecting, based on the first set of available resources, a first access plan of the one or more access plans. The method includes executing the first query and returning results of the first query to a source of the first query.

Abstract: Methods, computer readable media, and devices for distributing risk of multiple realms across multiple resources based on a realm risk model are disclosed. One method may include determining a time score based on an average response, a traffic score based on an average client request rate, and a risk score based on the time score and the traffic score for a plurality of realms, distributing the plurality of realms across a fixed number of resources based on the risk scores of the plurality of realms, and in response to a change in a risk score of a realm, redistributing the plurality of realms across the fixed number of resources based on a difference between a maximum risk score and a minimum risk score.

Abstract: Compiling optimized database statements including receiving, by a query compiler from a client computing system, a state specification of a graphical user interface in response to a user manipulating the graphical user interface on the client computing system, wherein the state specification is in a standard file format and describes modifications to a plurality of visual elements of the graphical user interface; compiling, by the query compiler, a database statement from the state specification such that a limit clause within the database statement is processed by a database before at least one join clause; and sending, by the query compiler, the optimized database statement to a database on a cloud-based data warehouse.

Abstract: Computer-readable media, methods, and systems are disclosed for proactively compiling in-memory database management system (DBMS) query plans upon startup of the in-memory DBMS. During normal operation of the in-memory DBMS, alternative query plans having associated execution statistics are collected and captured. Thereafter, the alternative query plans are selectively persisted and in response to detecting performance regressions, the regressed query plan is compared with prior query plans. In response to determining that a prior query plan performs better, the regressed query plan is replaced with the prior query plan. Upon a restart of the in-memory DBMS, a selected portion of the plurality of alternative query execution plans is loaded, and the plurality of alternative query execution plans are compiled. New queries are received and executed based on the proactively compiled query plans.

Abstract: A method includes receiving, by a first computing entity of a database system, a query request that is formatted in accordance with a generic query format. The method further includes generating, by the first computing entity, an initial query plan based on the query request and a query instruction set. The method further includes determining, by the first computing entity, storage parameters. The method further includes determining, by the first computing entity, processing resources for processing the query request based on the storage parameters. The method further includes generating, by the first computing entity, an optimized query plan from the initial query plan based on the storage parameters, the processing resources, and optimization tools. The method further includes sending, by the first computing entity, the optimized query plan to a second computing entity for distribution and execution of the optimized query plan.

Abstract: A computing system for querying multiple data sources and a method therefor is provided. The computing system may comprise one or more nodes in communication with at least one data source of the multiple data sources to access data therefrom. The computing system may further comprise a second node in communication with the one or more nodes. The second node may be configured to receive a query instance and process the query instance to generate one or more relational query instances. The one or more relational query instances may be distributed among the one or more nodes to extract data from the at least one data source in communication therewith corresponding to the respective one or more relational query instances. The second node may be further configured to receive extracted data from each of the one or more nodes queried. The second node may be further configured to aggregate the extracted data.

Abstract: A large highly parallel database management system includes thousands of nodes storing huge volume of data. The database management system includes multiple query optimizers for determining low cost execution plans for queries. The database management system is adapted to receive a data query. An execution plan generator component of the database management system generates an initial execution plan for the query. The initial execution plan is fed as input to more than one query optimizers. Each optimizer starts with the initial execution plan, generates alternative execution plans, and determines a satisfactory execution plan that incurs the lowest cost. The database management system compares the selected execution plans by the optimizers and selects one with the lowest cost. The multiple query optimizers run in parallel.

Abstract: Systems and methods for reducing latency of probing operations of remotely located linear hash tables are described herein. In an embodiment, a system receives a request to perform a probing operation on a remotely located linear hash table based on a key value. Prior to performing the probing operation, the system dynamically predicts a number of slots for a single read of the linear hash table to minimize total cost for an average probing operation. The system determines a hash value based on the key value and determines a slot of the linear hash table to which the hash value corresponds. After predicting the number of slots, the system issues an RDMA request to perform a read of the predicted number of slots from the linear hash table starting at the slot to which the hash value corresponds.

Abstract: A method for functionally rewriting iterative queries for a relational database management system (RDBMS) is provided. The method comprises receiving a first iterative query, the first iterative query having a first non-iterative part that defines a first main table and a first iterative part that generates values in rows of a first working table based on values in rows of the first main table, determining that the first iterative part modifies all of the rows of the first working table, and rewriting the first iterative part, including: adding a renaming operation to rename the first working table to a new first main table and to rename the first main table to a new first working table, adding a first Delete operation to delete each row of the new first working table, and adding a first loop operation to repeat the first iterative part until a first termination condition is met.

Abstract: Methods and computer systems for storing a query plan in a cache are provided. The method can include: determining a use frequency of the query plan; determining a target storage layer for storing the query plan based on the determined use frequency, wherein the cache includes at least two storage layers and each of the storage layers is associated with a compression level of query plans; processing the query plan according to the compression level of the target storage layer; and storing the processed query plan in the target storage layer.

Abstract: Systems and methods include acquisition of a database system workload comprising a plurality of database queries, replay of the database system workload on each of a plurality of database systems to generate a plurality of failed events, each of the plurality of failed events associated with a plurality of attributes, assignment of a root cause to each of the plurality of failed events, and training of a classification model, based on the plurality of failed events an assigned root causes, to infer an output root cause based on an input plurality of attributes.

Abstract: A method for processing a plurality of queries is provided according to embodiments of the present disclosure. In this method, based on a plurality of queries and an execution plan for the plurality of quires, a plurality of record identification (ID) numbers can be stored into a pool in a numerical order. Each of the plurality of record ID numbers can identify a data record in a database. Then, the execution plan can be performed to batch a plurality of data records corresponding to the plurality of record ID numbers in the database based on a distribution of the plurality of record ID numbers in the pool.

Abstract: A computer-implemented method that includes receiving an ingestion request to ingest data to a database comprising physical shards and detecting that the ingestion request is directed to a first hotspot shard. The first hotspot shard has a contention level over a threshold value. The method also detects context characteristics within the data and generates a first virtual shard based on a first virtual shard key selected from the detected context characteristics. The first virtual shard virtually duplicates at least a portion of the first hotspot shard. The method also includes ingesting the data to the first virtual shard.

Abstract: A computer-implemented method is disclosed that includes operations of parsing a query comprised of a sequence of operators to detect each operator of the sequence of operators, where the sequence of operators includes a machine learning (ML) operator representing a trained ML model. Additionally, a schema of the ML operator is determined through metadata. A filter or a projection is generated based on the schema of the ML operator, where the filter or projection is configured to reduce an amount of data retrieved upon application of the filter of the projection to an operator of the sequence of operators comprising the query. The schema of the ML operator indicates a schema of input data to be provided to the ML operator and a schema of output data to be provided by the ML operator following processing.

Abstract: The present disclosure relates to a home appliance and an operating method thereof. The home appliance according to the present disclosure includes: a user input interface; a storage configured to store a database of a response history, and a controller configured to: in response to receiving an input requesting to perform a previous operation through the user input interface, verify whether a first operation, corresponding to the request for performing the previous operation, is present in the operation history; in response to there being the first operation, verify a type of a first command, mapped to the first operation, among commands included in the database; in response to the type of the first command being a first type, determine the first operation to be the previous operation; and in response to the type of the first command being a second type, generate a second operation corresponding to the first command, and determines the second operation to be the previous operation.

Abstract: A method incorporates data visualization into conversational interfaces. The method receives a user input specifying a natural language command via a conversational interface. The method analyzes the natural language command to determine the type of question. The method also obtains a user preference for viewing responses based on text and/or visualizations. When the user preference includes visualizations and the type of question is answerable using data visualizations, the method: (i) extracts one or more independent analytic phrases from the natural language command; (ii) queries a database using a set of queries based on the extracted analytic phrases, thereby retrieving a data set; and (iii) generates and displays, in the conversational interface, a response incorporating one or more data visualizations, based on the type of question, using the data set.

Abstract: Systems and methods for processing structured queries over clusters are provided herein. An example system includes a plurality of clusters, wherein a local cluster is configured to receive, from a client, a structured query language (SQL) structured query, determine, based on the SQL structured query, a list of remote clusters of the plurality of clusters, process the SQL structured query to generate a local query executable by a local search engine of the local cluster and remote queries executable by remote search engines of the remote clusters, send the remote queries to the remote clusters to obtain remote results, execute the local query to obtain local results, combine the remote results and the local results to obtain an aggregated result, and return the aggregated result to the client.

Abstract: A documentation generation engine coupled to a mutation handler are provided, configured to traverse a knowledge base to derive selective views. Organizations may configure a documentation generator application running on generator hosts to summarize records of a knowledge base storing institutional knowledge, and relationships therebetween, as human-readable reference documents. It is undesired for the documentation generator to query the knowledge base on a naive basis in response to updates in order to derive views required to generate updated documentation.

Abstract: Techniques for automatically preventing execution plan regressions are provided. In one technique, in a first user database session, in response to receiving a first database statement, a first execution plan is generated and, while executing the first execution plan, first performance data that indicates one or more first performance metrics of executing the first execution plan is recorded. In response to receiving a second database statement, where the first execution plan may be used to generate a result for the second database statement, a second execution plan is generated and second performance data that indicates one or more second performance metrics of executing the second execution plan is recorded. A comparison between the first performance data and the second performance data is performed. Based on the comparison, it is determined whether the second execution plan will be stored for future use to process a database statement.

Abstract: Methods and apparatus are disclosed for staged query compilation. One or more intermediate plans between a query and its execution plan are stored according to a common specification for plan data structures. Data sources, a plan flow, and annotations can be stored in respective fields of the plan data structure, which can be extended with a field for a serialized execution plan. Plan data structures provide a stable interface for integration of local and external software modules, and decouple plan representation from plan optimization. Use cases are disclosed for integrating offline optimization with inline software modules, for integrating local query handling with external services, for caching intermediate plans, and for archiving plans across version changes of optimizers. A hub architecture flexibly supports numerous compilation workflows. Disclosed technologies are suitable for cloud deployments and for migration of databases into the cloud.

Abstract: Techniques for presenting an alternative input representation to a user for testing and collecting processing data are described. A system may determine that a received spoken input triggers an alternative input representation for presenting. The system may output data corresponding to the alternative input representation in response to the received spoken input, and the system may receive user feedback from the user. The system may store the user feedback and processing data corresponding to processing of the alternative input representation, which may be later used to update an alternative input component configured to determine alternative input representations for spoken inputs.

Abstract: A computer implemented method can receive a request for a fallback query execution plan of a query in a database system. The query involves an object of the database system. The object is associated with a captured object. The method can evaluate whether the object and the captured object have the same logical structure. Responsive to an indication that the object and the captured object have the same logical structure, the method can reuse the fallback query execution plan to execute the query. The evaluating includes identifying a logical structure of the captured object stored in an object definition table, obtaining a current logical structure of the object, and comparing the logical structure of the captured object with the current logical structure of the object.

Abstract: A query engine or compute engine receiving a query request identifies a plurality of data sources for satisfying a query request, and determines, from among multiple data sources, one or more fields likely to incur substantial computational demands in processing the query request. Pre-positioning aggregation logic moves the determined fields one data source to another data source for positioning the moved fields to a single data source from which the query result will be computed.

Abstract: Disclosed are various embodiments for asynchronously generating consistent snapshots in a distributed system. In one embodiment, a snapshotting agent receives a respective local snapshot for individual processes in a distributed system. The respective local snapshot for a corresponding process includes a corresponding vector clock that comprises respective values indicating respective state changes in the corresponding process and other processes. The snapshotting agent determines whether a collection of the respective local snapshots for the individual processes represents a global consistent snapshot for the distributed system based at least in part on a comparison of the respective values of the corresponding vector clocks.

Abstract: The subject technology provides embodiments for enabling derivation of predicates not only from other predicates but also from metadata such as expression properties. In examples, predicates are derived, avoiding unwanted impact on cardinality estimation. In other examples, predicates are derived, avoiding artificial runtime errors and providing a way to avoid security issues with secure views.

Abstract: The subject technology receives a query directed to a set of source tables, each source table organized into a set of micro-partitions. The subject technology determines a set of metadata, the set of metadata comprising table metadata, query metadata, and historical data related to the query. The subject technology predicts, using a machine learning model, an indicator of an amount of computing resources for executing the query based at least in part on the set of metadata. The subject technology generates a query plan for executing the query based at least in part on the predicted indicator of the amount of computing resources. The subject technology executes the query based at least in part on the query plan.

Abstract: Examples of the present disclosure describe systems and methods for query execution across multiple graphs. In an example, a graph or isolated collection may be split into multiple subparts, such that each subpart may store information of the isolated collection. Cross-collection reference resources may be used to reference resources that are stored by other isolated collection subparts. A breadth-first search of an isolated collection subpart may be performed in order to identify matches or potential matches in an isolated collection subpart. In an example, a potential match may comprise a cross-collection reference resource, which may reference a resource in another isolated collection subpart. Once query execution has completed in the isolated collection subpart, query execution may be paused and transferred to another isolated collection subpart that comprises a resource referenced by a cross-collection resource reference.

Abstract: A method including inputting, into a phrase recognition model comprising a neural network, a vector comprising a plurality of ngrams of text. The method also includes applying, using the phrase recognition model, a filter to the plurality of ngrams during execution. The filter has a skip word setting of at least one. The method also includes determining, based on the skip word setting, at least one ngram in the vector to be skipped to form at least one skip word. The method also includes outputting an intermediate score for a set of ngrams that match the filter. The method also includes calculating a scalar number representing a semantic meaning of the at least one skip word. The method also includes generating based on the scalar number and the intermediate score, a final score for the set of ngrams. A computer action is performed using the final score.

Abstract: An agricultural monitoring system, apparatus and method(s) for providing crop-related forecasts by performing the steps of receiving seasonal image data from at least one source, where the seasonal image data is associated with at least one agricultural field, processing the seasonal image data using a Bayesian framework, where the Bayesian framework comprises one or more crop models configured to predict, based on the seasonal image data, one or more probabilities indicative of at least one crop state, updating at least one crop model of the Bayesian framework based on the one or more probabilities, and outputting a forecast of the at least one crop state based on the one or more probabilities.

Abstract: A system and method for performing large-scale data processing using a statistical programming language are disclosed. One or more high-level statistical operations may be received. The received high-level statistical operations may be dynamically translated into a graph of low-level data operations. The unnecessary operations may be removed and operations may be fused or chained together. Operations may then be grouped into distributed data processing operation. The low-level operations may then be run.

Abstract: A method for execution by a node of a computing device includes: determining level assignment data indicating assignment to a subset of levels of a plurality of levels of a query execution plan, wherein the plurality of levels includes a lowest level, at least one inner level, and a highest level; determining a query for execution; determining a query discriminator number corresponding to the query; determining to process the query at one of the plurality of levels based on determining the one of the plurality of levels is included in the subset of levels; generating query resultant data by facilitating execution of at least one query operator of the query in accordance with the one of the plurality of levels; selecting one of a plurality of possible parent nodes in a sequentially higher one of the plurality of levels based on the query discriminator number; and sending the query resultant data to the one of the plurality of possible parent nodes for processing.

Abstract: A method, computer program product, and computer system for improving performance of a SQL execution sequence of SQL statements. The SQL execution sequence is recorded in an event log. Original results of executing the SQL statements and an original CPU cost of executing the SQL statements in accordance with the original access path are recorded in a logical log. A new access path is generated from analysis of the event log and the logical log. The SQL statements are executed in accordance with the new access path resulting in new results of executing the SQL statements including a new CPU cost of executing the SQL statements in accordance with the new access path. In response to a determination that the new results replicate the original results and that the new CPU cost is less than the original CPU cost, the original access path is replaced with the new access path.

Abstract: Systems, devices, methods, and interfaces generally for use with database management systems (DBMSs) and DBMS interfaces (i.e. user interfaces, input interfaces, search interfaces, operating interfaces, etc.). In some aspects, the systems, devices, methods, and interfaces include using artificial intelligence (i.e. machine learning and/or anticipation functionalities, etc.) to learn a user's use of a DBMS or DBMS interface, store this “knowledge” in a knowledgebase, and anticipate the user's future operating intentions. In other aspects, the systems, devices, methods, and interfaces include disassembling user or other input into various types of portions (i.e. text, numbers, etc.) and determining one or more instructions for performing operations on a DBMS or DBMS interface based on the various types of portions. In further aspects, the systems, devices, methods, and interfaces include associative DBMS command construction. Other systems, devices, methods, interfaces, and features are also disclosed.

Abstract: A computer-implemented method to transform and execute queries by merging sparsely populated columns. The method includes receiving, from a host, a first query configured to perform a command on one or more target columns in a database. The method further includes analyzing a set of statistics for the database. The method also includes determining, based on the analyzing, a first column of the one or more target columns is included in a set of sparse columns. The method includes generating a plurality of access plans for the first query, including a first access plan that merges the first column with a second column. The method further includes transforming, based on the first access plan, the first query to merge the first column with the second column. The method also includes executing, in response to the transforming of the first query, the first query.

Abstract: Technologies are described for facilitating data workload capture, workload replay, and comparing the performance of a plurality of database systems. A plurality of requests for database operations are received from one or more database clients. The requests for database operations are executed. For the plurality of requests for database operations, execution context information is generated for a plurality of execution contexts. For the plurality of requests for database operations, a plurality of performance measures are generated. The execution context information and the performance measures are stored in a workload capture store, such as a file. The workload capture file is useable to replay the captured workload at a second database system using at least a portion of the execution context information and at least a portion of the performance measures.

Abstract: Systems, methods, and other embodiments associated with assessing and adaptively managing query loads are described. In one embodiment, a method includes determining that a query invoked by a client terminal against an application object has a duration that exceeds a completion threshold. In response to receiving a subsequent invocation of the query, statistics for the query are obtained. The obtained statistics are analyzed to determine whether the query causes the unacceptable negative impact on the application object. A data structure is modified to include a classification of the query into one of a plurality of different query classes based on a result of the analysis, and execution of the query in response to a future invocation is controlled based on the classification of the query in the modified data structure.

Abstract: Methods, apparatus, and processor-readable storage media for query processing based on a stochastic prediction model are provided herein. An example computer-implemented method includes maintaining information associated with a set of database operators corresponding to one or more historical query plans, wherein each of the historical query plans is associated with processing of a corresponding historical query in a database; building, based on the maintained information, a data structure comprising probabilities of each database operator in the set transitioning to each of one or more of the other database operators in the set; obtaining a new query to be processed in the database; applying a stochastic prediction algorithm to identify, from among the historical query plans, at least one candidate query plan for the new query based on the data structure; and executing the at least one candidate query plan to access data from the database for the new query.

Abstract: Methods and systems described herein are directed to aggregating and querying log messages. Methods and systems determine event types of log message generated by event sources of the distributed computing system. The event types are aggregated into aggregated records for a shortest time unit and event types are aggregated into aggregated records for longer time units based on the aggregated records associated with the shortest time unit. In response to a query regarding occurrences of an event type in a query time interval, the query time interval is split into subintervals with time lengths that range from the shortest time unit to a longest time unit that lie within the query time interval. The method determines a total event count of occurrences of the event type in the query time interval based on the aggregated records with time stamps in the subintervals. The event count in the query time interval may be used to detect abnormal behavior of the event sources.

Abstract: A method for scheduling tasks from a program executed by a multi-processor core system is disclosed. The method includes a scheduler that groups a plurality of tasks, each having an assigned priority, by priority in a task group. The task group is assembled with other task groups having identical priorities in a task group queue. A hierarchy of task group queues is established based on priority levels of the assigned tasks. Task groups are assigned to one of a plurality of worker threads based on the hierarchy of task group queues. Each of the worker threads is associated with a processor in the multi-processor system. The tasks of the task groups are executed via the worker threads according to the order in the hierarchy.