Systems and methods for evaluating analytic queries comprising disjunctive Boolean expressions are described. A method may include receiving an analytic query comprising a first disjunctive Boolean expression. The method may further include transforming the analytic query to obtain a transformed analytic query comprising at least one nondisjunctive Boolean expression and at least a second disjunctive Boolean expression. The method may also include evaluating the transformed analytic query, wherein complete evaluation of the at least one nondisjunctive Boolean expressions and the at least a second disjunctive Boolean expressions yields the same results as evaluation of the first disjunctive Boolean expression.

A method and apparatus managing a set of processors for a set of queries is described. In an exemplary embodiment, a device receives a set of queries for a data warehouse, the set of queries including one or more queries to be processed by the data warehouse. The device further provisions a set of processors from a first plurality of processors, where the set of processors to process the set of queries, and a set of storage resources to store data for the set of queries. In addition, the device monitors a utilization of the set of processors as the set of processors processes the set of queries. The device additionally updates a number of the processors in the set of processors provisioned based on the utilization/Furthermore, the device processes the set of queries using the updated set of processors.

Disclosed aspects relate to data arrangement management in a distributed data cluster environment of a shared pool of configurable computing resources. In the distributed data cluster environment, a set of data is monitored for a data redistribution candidate trigger. The data redistribution candidate trigger is detected with respect to the set of data. Based on the data redistribution candidate trigger, the set of data is analyzed with respect to a candidate data redistribution action. Using the candidate data redistribution action, a new data arrangement associated with the set of data is determined. Accordingly, the new data arrangement is established.

Systems and a method are provided. A system includes a Temporal Behavior Query Language (TBQL) server having a processor and a memory operably coupled to the processor. The TBQL server configured to construct a TBQL query using a grammar inference technique based on syntactic sugar to expedite query construction. The TBQL server is further configured to execute the TBQL query to generate TBQL query results.

The present disclosure involves systems, software, and computer implemented methods for improved design and implementation of data access metrics for automated physical database design. An example method includes identifying a database workload for which index advisor access counters are to be tracked. Each SQL statement in the database workload is executed. For each SQL statement, attribute sets are determined for which a selection predicate filters a result for an SQL statement. An output cardinality of each selection predicate is determined. A logarithmic counter for an attribute set corresponding to the selection predicate is determined based on the output cardinality of the selection predicate. The determined logarithmic counter is incremented. Respective values for logarithmic counters of the determined attributes are provided to an index advisor. The index advisor determines attribute sets for which to propose an index based on the logarithmic counters of the respective attribute sets.

A serverless query processing system receives a query and determines whether the query is a recurring query or a non-recurring query. The system may predict, in response to determining that the query is the recurring query, a peak resource requirement during an execution of the query. The system may compute, in response to determining that the query is the non-recurring query, a tight resource requirement corresponding to an amount of resources that satisfy a performance requirement over the execution of the query, where the tight resource requirement is less than the peak resource requirement. The system allocates resources to the query based on an applicable one of the peak resource requirement or the tight resource requirement. The system then starts the execution of the query using the resources.

A locally optimized plan for executing a command using a sequence of steps can be determined for a single computing node. However, the locally optimized sequence of steps may not be optimized for a combined system comprising multiple computing nodes, any one of which may be tasked with executing the command. A plan that is optimized for the combined system may be determined by comparing the predicted cost of locally optimized plans for computing nodes in the combined system.

A database query comprising predicates may be received. Each predicate may operate on database columns. The database query may be determined to comprise strict operators. An upper bound neural network may be defined for calculating an adjacent upper bound and a lower bound neural network may be defined for calculating an adjacent lower bound. The upper bound neural network and the lower bound neural network may be trained using a selected value from data of a database table associated with the database query to be executed through the upper bound neural network and the lower bound neural network. The upper bound neural network and the lower bound neural network may be adjusted by passing in an expected value using an error found in expressions. The adjacent lower bound and the adjacent upper bound may be calculated in response to completion of initial training for the database columns.

The present disclosure provides a computer implemented method and system for processing queries. The first data table comprises a set of data blocks. Each of the set of data blocks may be assigned respective attribute value information. A query involving a query condition on at least a first attribute of the first data table may be received. And a subset of the set of data blocks to be accessed may be selected based on the query condition and using the attribute value information. Furthermore, a guaranteed bound may be determined for a statistical metric on the first attribute based on at least one of the number of data blocks of the subset of data blocks and the attribute value information of the subset of data blocks. The guaranteed bound for the statistical metric may be used when determining a query execution plan for the received query.

The following description relates to a query optimization method in distributed query engine and an apparatus thereof. A query optimization method according to an exemplary embodiment includes establishing a query plan based on query; classifying data to be included in result data of a high level operation from result data of a low level operation as a first data to be used for intermediate operations existing between the low level operation and the high level operation and a second data not to be used for the intermediate operations, based on the query plan; and modifying the query plan for the second data not to be an input value for the intermediate operations