Abstract: Embodiments of the present disclosure may provide dynamic and fair assignment techniques for allocating resources on a demand basis. Assignment control may be separated into at least two components: a local component and a global component. Each component may have an active dialog with each other; the dialog may include two aspects: 1) a demand for computing resources, and 2) a total allowed number of computing resources. The global component may allocate resources from a pool of resources to different local components, and the local components in turn may assign their allocated resources to local competing requests. The allocation may also be throttled or limited at various levels.

Abstract: Systems, methods, and devices for feature release and workload capture in database systems are disclosed. The method includes determining a workload based on one or more client queries to be rerun to test a feature that is unreleased to one or more database clients. The method includes repeatedly executing a test run of the workload to determine a stability factor of the test run. The method includes re-executing, in response to determining the stability factor of the test run, the test run using resources with a different concurrency to confirm the stability factor of the test run. The method includes releasing the feature to the one or more database clients in response to confirming the stability factor of the test run.

Abstract: Systems, methods, and devices for feature release and workload capture in database systems are disclosed. The method includes determining a workload based on one or more client queries to be rerun to test a feature that is unreleased to one or more database clients. The method includes repeatedly executing a test run of the workload to determine a stability factor of the test run. The method includes re-executing, in response to determining the stability factor of the test run, the test run using resources with a different concurrency to confirm the stability factor of the test run. The method includes releasing the feature to the one or more database clients in response to confirming the stability factor of the test run.

Abstract: The subject technology receives, during a query compilation process, a query directed to a set of source tables, each source table from the set of source tables being organized into at least one micro-partition and the query including at least one pruning operation. The subject technology performs, during the query compilation process, a modification of the query for adjusting the at least one pruning operation, the modification being based at least in part on a set of statistics collected for previous pruning operations on at least a portion of the set of source tables and a set of heuristics. The subject technology compiles the query including the modification of the query. The subject technology provides the compiled query to an execution node of a database system for execution.

Abstract: The subject technology provides information, corresponding to properties of a build side of a join operation, to a bloom filter. The subject technology, based at least in part on the information from the bloom filter, determines, during executing of a query plan, at least one property of the join operation to determine whether to switch an aggregation operator to a pass through mode, the at least one property comprising at least a reduction rate. The subject technology, switches, in response to the reduction rate being below a threshold value, the aggregation operator to the pass through mode during runtime of the query plan and, while the aggregation operator is in the pass through mode, an input stream of data goes through the aggregation operator without being analyzed and the input stream of data matches an output stream of data flowing out of the aggregation operator.

Abstract: A method for selecting an operation mode of a mobile platform includes detecting a height grade of the mobile platform and selecting an operation mode of the mobile platform according to a result of the detecting.

Abstract: A system to repeatedly execute a test run of a workload using resources of a cloud environment to determine whether there is a performance difference in the test run. The system to, in response to determining that there is no performance difference, identify one or more sets of decreased resources of the cloud environment. The system to re-execute the test run using the one or more sets of decreased resources of the cloud environment to determine whether there is a performance difference in the test run that is attributed to the one or more sets of decreased resources of the cloud environment. The system to determine minimum resources of the cloud environment to repeatedly execute the test run using the minimum resources without existence of a performance difference in response to re-executing the test run using the one or more sets of decreased resources of the cloud environment.

Abstract: Embodiments of the present disclosure may provide a dynamic query execution model with fault tolerance and failure recovery techniques. Embodiments of the present disclosure may utilize checkpoints to map processed output files to their corresponding input files. Therefore, if an error occurs in processing one or more files, the system may only need to reschedule processing of selected file(s).

Abstract: Systems, methods, and devices for incrementally refreshing a materialized view are disclosed. A method includes generating a materialized view based on a source table. The method includes merging the source table and the materialized view to generate a merged table to identify whether an update has been executed on the source table that is not reflected in the materialized view. The method includes, in response to detecting an update made to the source table that is not reflected in the materialized view, applying the update to the materialized view.

Abstract: Embodiments of the present disclosure may provide a dynamic query execution model. This query execution model may provide acceleration by scaling out parallel parts of a query (also referred to as a fragment) to additional computing resources, for example computing resources leased from a pool of computing resources. Execution of the parts of the query may be coordinated by a parent query coordinator, where the query originated, and a fragment query coordinator.

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 provides the compilation context to a compiler. The subject technology invokes the compiler to perform a compilation process based on the compilation context, the compilation process comprising performing a lookup operation on a stored plan cache for an exact match based on information from the compilation context, the stored plan cache including a set of stored query plans, and determining whether the exact match of a particular query plan is found in the stored plan cache to avoid compiling the query using the compilation context.

Abstract: Disclosed herein are systems and methods for incremental reclustering of database tables based on local maxima of partition overlap. In an embodiment, a database platform makes a determination, based on one or more incremental-reclustering criteria, to incrementally recluster a database table, which has a clustering key and which is stored across a plurality of partitions. In response to making the determination, the database platform selects a subset of the partitions, and at least incrementally reclusters the selected subset. The selecting of the subset includes identifying a local maximum of a quantity of overlapping partitions in the plurality of partitions with respect to a domain of the clustering key of the table, where the overlapping partitions overlap with respect to the clustering key.

Abstract: Joining data using a disjunctive operator is described. An example computer-implemented method can include receiving a query that includes a first disjunctive predicate involving a first table and a second table. The method may also include determining a first set of rows from the first table and generating a filter from the first set of rows. The method may also further include applying the filter to the second table to generate a second set of rows. Additionally, the method may also include joining the first set of rows and the second set of rows using a first disjunctive operator of the first disjunctive predicate to generate a first results set.

Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.

Abstract: Systems, methods, and devices for incremental feature development and workload capture in database systems are disclosed. The method includes determining a workload based on one or more client queries to be rerun for testing the feature release. The method further includes repeatedly executing a test run of the workload to identify whether there is a performance difference in the test run. The method further includes re-execute, in response to identifying the performance difference, the test run using resources with a different concurrency to identify whether the performance difference still exists. The method further includes flagging the performance difference as a false positive in response to identifying that the performance difference no longer exists when the test run is re-executed using the resources with different concurrency.

Abstract: The subject technology determines whether a table is sufficiently clustered. The subject technology in response to determining the table is not sufficiently clustered, selects one or more micro-partitions of the table to be reclustered. The subject technology constructs a data structure for the table. The subject technology extracts minimum and maximum endpoints for each micro-partition in the data structure. The subject technology sorts each of one or more peaks in the data structure based on height. The subject technology sorts overlapping micro-partitions based on width. The subject technology selects based on which micro-partitions are within the tallest peaks of the one or more peaks and further based on which of the overlapping micro-partitions have the widest widths.

Abstract: Systems, methods, and devices for incremental feature development and workload capture in database systems are disclosed. The method includes determining a workload based on one or more client queries to be rerun for testing the feature release. The method further includes repeatedly executing a test run of the workload to identify whether there is a performance difference in the test run. The method further includes re-execute, in response to identifying the performance difference, the test run using resources with a different concurrency to identify whether the performance difference still exists. The method further includes flagging the performance difference as a false positive in response to identifying that the performance difference no longer exists when the test run is re-executed using the resources with different concurrency.

Abstract: Embodiments of the present disclosure may provide a dynamic query execution model. This query execution model may provide acceleration by scaling out parallel parts of a query (also referred to as a fragment) to additional computing resources, for example computing resources leased from a pool of computing resources. Execution of the parts of the query may be coordinated by a parent query coordinator, where the query originated, and a fragment query coordinator.

Abstract: A baseline run of a workload and a target run of the workload are compared to identify whether there is a performance regression in the target run, wherein the target run implements a feature that is not implemented in the baseline run. In response to identifying the performance regression, the target run is executed to identify whether the performance regression still exists. The performance regression is flagged as a false positive in response to identifying that the performance regression no longer exists when the target run is executed.

Abstract: Resource provisioning systems and methods are described. In an embodiment, a system includes a plurality of shared storage devices collectively storing database data, an execution platform, and a compute service manager. The compute service manager is configured to determine a task to be executed in response to a trigger event and determine a query plan for executing the task, wherein the query plan comprises a plurality of discrete subtasks. The compute service manager is further configured to assign the plurality of discrete subtasks to one or more nodes of a plurality of nodes of the execution platform, determine whether execution of the task is complete, and in response to determining the execution of the task is complete, store a record in the plurality of shared storage devices indicating the task was completed.