Abstract: Example resource management systems and methods are described. In one implementation, a system includes a memory and a processing device operatively coupled to the memory. The processing device is to receive a query referencing database data stored in a storage platform, determine a task associated with processing the received query, and create an execution node comprising cache resources and processing resources. Furthermore, a size of the cache resources of the execution node is determined upon creation of the execution node, based at least in part on the task, and processing resources of the execution node are determined upon creation of the execution node, based at least in part on the task. The execution node is included within a plurality of execution nodes to process the task associated with processing the received query.

Abstract: Example resource management systems and methods are described. In one implementation, a resource manager is configured to manage data processing tasks associated with multiple data elements. An execution platform is coupled to the resource manager and includes multiple execution nodes configured to store data retrieved from multiple remote storage devices. Each execution node includes a cache and a processor, where the cache and processor are independent of the remote storage devices. A metadata manager is configured to access metadata associated with at least a portion of the multiple data elements.

Abstract: A system and method for pruning data based on metadata. The method may include receiving a query that includes a plurality of predicates and identifying one or more applicable files including database data satisfying at least one of the plurality of predicates. The identifying the one or more applicable files including reading metadata stored in a metadata store that is separate from the database data. The method further includes pruning inapplicable files including database data that does not satisfy at least one of the plurality of predicates to create a reduced set of files and reading the reduced set of files to execute the query.

Abstract: 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.

Abstract: A method and apparatus for managing a set of storage resources for a set of queries is described. In an exemplary embodiment, a method provisions processing resources of an execution platform and provisions storage resources of a storage platform. The execution platform uses the storage platform, which is shared with the execution platform, to process the set of queries. The method changes a number of the storage resources provisioned for the storage platform based on a storage capacity utilization by the set of queries of the storage resources. The method changes the number of the storage resources independently to a change of the processing resources in the execution platform. The method processes the set of queries using the changed number of the storage resources provisioned for the storage platform.

Abstract: A method, apparatus, and system for join operations of a plurality of relations that are distributed over a plurality of storage locations over a network of computing components.

Abstract: A system and method of scaling capacity of data warehouses to user-defined levels. The method includes determining a performance associated with processing one or more queries. The method includes receiving a request to process data stored on a storage platform. The method includes adjusting, by a processing device based on the performance, a timing associated with the processing of the one or more queries to adjust a different timing associated with processing the request.

Abstract: A system and method for just in time compilation for hash table probing are disclosed. In one implementation, the method of using just-in-time compilation is used to combine the stages of hash value computation and initial lookup into a single compound operation. In another implementation, the method of using just-in-time compilation is used to combine the stages of a hash table record and input record checking to detect if these records are equal, and if not, fetching the next possible record in the linked list of the per-bucket records.

Abstract: Example resource management systems and methods are described. In one implementation, a system includes a memory and a processing device operatively coupled to the memory. The processing device is to receive a query referencing database data stored in a storage platform, determine a task associated with processing the received query, and create an execution node comprising cache resources and processing resources. Furthermore, a size of the cache resources of the execution node is determined upon creation of the execution node, based at least in part on the task, and processing resources of the execution node are determined upon creation of the execution node, based at least in part on the task. The execution node is included within a plurality of execution nodes to process the task associated with processing the received query.

Abstract: A query directed to database data stored across a set of files is received. The query includes predicates applied against metadata of the set of files. One or more files are removed from the set of files whose metadata does not satisfy a predicate of the plurality of predicates. Rows of the one or more remaining files of the set of files are filtered based on the one or more predicates.

Abstract: A system and method for just in time compilation for hash table probing are disclosed. In one implementation, the method of using just-in-time compilation is used to combine the stages of hash value computation and initial lookup into a single compound operation. In another implementation, the method of using just-in-time compilation is used to combine the stages of a hash table record and input record checking to detect if these records are equal, and if not, fetching the next possible record in the linked list of the per-bucket records.

Abstract: Example caching systems and methods are described. In one implementation, a method receives a set of queries to be processed by a set of virtual warehouses. The method distributes the set of queries to the set of virtual warehouses to be executed and creates, during the processing of the set of queries by the set of virtual warehouses, a new virtual warehouse, wherein cache resources associated with the new virtual warehouse are populated with data files associated with the set of queries at the time the virtual warehouse is created and the cache resources vary among the processors, wherein a first subset of the processors comprises minimal cache resources and a second subset of processors comprises cache resources providing faster input-output operations. The method redistributes the set of queries across the set of virtual warehouses.

Abstract: Example resource management systems and methods are described. In one implementation, a resource manager is to be coupled to one or more virtual data warehouse instances that each comprise a plurality of computing resources. A resource manager receives a query directed to database data. The resource manager determines a task associated with the query. The resource manager distributes the task to a first virtual data warehouse instance of the plurality of virtual data warehouse instances. The resource manager determines that the first virtual data warehouse instance of the plurality of virtual data warehouse instances no longer accesses the database data. The resource manager reconfigures the first virtual data warehouse instance to delete a communication between the first virtual data warehouse instance and the database.

Abstract: A system and method of scaling capacity of data warehouses to user-defined levels. The method includes monitoring a processing of one or more queries by a data warehouse, the data warehouse including one or more processing resources and a storage platform. The method includes receiving a request to process database data stored on the storage platform. The method includes determining a performance of the processed request as observed by a user device. The method includes adjusting, by a processing device, a timing associated with the processing of the one or more queries based on the performance of the processed request.

Abstract: Example resource management systems and methods are described. In one implementation, a system includes a memory and a processing device operatively coupled to the memory. The processing device is to: provide a plurality of execution nodes, each execution node comprising a cache and a processor, each execution node communicatively coupled to a storage platform; determine at least one task associated with processing a received query referencing database data stored in the storage platform; and create a new execution node within the plurality of execution nodes to process the at least one task associated with processing the received query.

Abstract: Example resource management systems and methods are described. In one implementation, a resource manager is to be coupled to one or more virtual data warehouse instances that each comprise a plurality of computing resources. A resource manager receives a query directed to database data. The resource manager determines a plurality of tasks associated with the query. The resource manager distributes the plurality of tasks among the one or more virtual data warehouse instances to cause each computing resource of the plurality of computing resources of the one or more virtual data warehouse instances to process a respective task of the plurality of tasks. The resource manager receives results obtained from the processing of the plurality of tasks. The resource manager uses the results to respond to the query.

Abstract: Example caching systems and methods are described. In one implementation, a method identifies multiple files used to process a query and distributes each of the multiple files to a particular execution node to execute the query. Each execution node determines whether the distributed file is stored in the execution node's cache. If the execution node determines that the file is stored in the cache, it processes the query using the cached file. If the file is not stored in the cache, the execution node retrieves the file from a remote storage device, stores the file in the execution node's cache, and processes the query using the file.

Abstract: A method, apparatus, and system for join operations of a plurality of relations that are distributed over a plurality of storage locations over a network of computing components.

Abstract: A restricted view definition is received by a database system. The restricted view definition defines a view over a database table with one or more restrictions on use of the view. The view over the database table is generated based on the restricted view definition. A query directed at the view is received by the database system. The database system determines whether the query directed at the view is permitted based on the one or more restrictions on the use of the view.

Abstract: A computer system hosting a column-store database engine is responsive to database requests for the update and retrieval of data from within a stable data table and providing for the storage of database tuples within a column-store organized database structure. A positional delta tree data structure is implemented in the memory space of the database engine and is operatively coupled in an update data transfer path between a database engine interface and the stable data table. The positional delta tree data structure includes a differential data storage layer operative to store differential update data values in positionally defined relative reference to database tuples stored by the stable data table.