Abstract: The subject technology creates one or more partitions based on changes to a table, at least one of the one or more partitions overlapping with respect to values of one or more attributes with at least one of another partition and a previous partition, the creating of the one or more partitions resulting in a decrease in a degree of clustering of the table. The subject technology determines, after creating the one or more partitions, that the degree of clustering of the table is below a clustering threshold, the clustering threshold corresponding to a clustering ratio, the clustering ratio determined by at least a proportion of rows in a layout of the table that satisfy an ordering criteria based at least in part a particular attribute of the one or more attributes. The subject technology increases the degree of clustering of the table by reclustering partitions of the table.

Abstract: The subject technology creates partitions based on changes to a table, at least one of the one or more partitions overlapping with respect to values of one or more attributes with at least one of another partition and a previous partition. The subject technology maintains states for the partitions, each state from the plurality of states representing a particular degree of clustering of the table. The subject technology determines a number of overlapping partitions and a depth of the overlapping partitions, and determines a clustering ratio based at least n part on the number of overlapping partitions and the depth. The subject technology reclusters partitions of the table to increase the clustering ratio, the clustering ratio determined by at least a proportion of rows in a layout of the table that satisfy an ordering criteria based at least in part a particular attribute of the one or more attributes.

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.

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: 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 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 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 method includes storing table data for a table in a plurality of partitions and for maintaining approximate or good enough clustering. The method includes creating one or more new partitions based on changes to the table, wherein at least one of the one or more new partitions overlap with each other or previous partitions resulting in a decrease in a degree of clustering of the table. The method includes determining that a degree of clustering of the table data is below a clustering threshold. The method further includes reclustering one or more partitions of the table to improve the degree of clustering of the table in response to one or more of: determining that the degree of clustering has fallen below the clustering threshold, an explicit user command from a user, and/or as part of a DML command. Reclustering may be performed in incremental steps to iteratively improve clustering.

Abstract: 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.

Abstract: A system is described inkling a cache memory and a hardware processor. The hardware processor to determine that at least one of additional data storage capacity and additional processing capacity are needed based on data processing requests of a plurality of computerized query sources to be executed by an execution platform comprising a plurality of nodes, where the data processing requests are directed to database data stored on a plurality of shared storage devices collectively storing the database data. The hardware processor further to increase, in response to the determining, an amount of the data cached by the execution platform by adding one or more nodes to the plurality of nodes.

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 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: 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 system and method for pruning data based on metadata. The method may include receiving a query comprising a plurality of predicates and identifying one or more applicable files comprising 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 comprising 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: Example resource provisioning systems and methods are described. In one implementation, multiple processing resources are provided within a data warehouse. The processing resources include at least one processor and at least one storage device. At least one query to process database data is received. At least some of the processing resources may process the database data. When a processing capacity of the processing resources has reached a threshold processing capacity, the processing capacity is automatically scaled by adding at least one additional processor to the data warehouse.

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 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: Example resource provisioning systems and methods are described. In one implementation, multiple processing resources are provided within a data warehouse. The processing resources include at least one processor and at least one storage device. At least one query to process database data is received. At least some of the processing resources may process the database data. When a processing capacity of the processing resources has reached a threshold processing capacity, the processing capacity is automatically scaled by adding at least one additional processor to the data warehouse.

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 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.