Abstract: A method and apparatus for compression units in an index block is provided. A particular leaf block of a database index for a table is generated. The particular leaf block corresponds to a particular range of key values. A compression scheme is determined for a plurality of index entries with key values within the particular range. A compression unit that includes a plurality of compressed index entries is generated by applying the compression scheme to the plurality of index entries. Compression metadata describing the compression scheme is generated. The compression unit and the compression metadata is stored in the particular leaf block. In response to a request, at least a portion of the compression unit is decompressed to access one or more index entries.

Abstract: The subject technology receives, during a query compilation process, a query directed to a set of source tables. The subject technology performs, during the query compilation process, a modification of the query for adjusting at least one pruning operation. The subject technology determines, during a pruning process of a second query, the second query directed to a set of files in a database system and including a set of pruning operations on the set of files, whether to perform a pruning cutoff on the set of pruning operations, the pruning process performing a depth first search of a pruner tree structure, the set of files comprising a set of micro-partitions. The subject technology performs the pruning cutoff based on the determining, the pruning cutoff ceasing at least one pruning operation from the set of pruning operations.

Abstract: A system and a method for determining potential revenue from a sales opportunity at a stage of generating a quotation therefor are provided. The system comprises an application programming interface configured to receive a draft quotation from a CRM application. The present system bundles two or more items of the draft quotation based on one or more predefined revenue allocation rules for the draft quotation; apply the variable consideration information for each of the bundled items to determine a revenue adjustment amount and a timeline for realization of revenue; group items based on substantially matching timelines therefor for realization of revenue; determine revenue recognition for each group based on price information and determined revenue adjustment amount for each of the items therein; and generate a revenue forecast resultant of the approval of the draft quotation based on the determined revenue recognition.

Abstract: During a query compilation process, a query is received that is 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. During the query compilation process, a modification of the query is performed for adjusting the at least one pruning operation, the modification being based 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 set of statistics indicating at least an amount of execution time for each previous query associated with each of the previous pruning operations. The query is compiled including the modification of the query. The compiled query is provided to an execution node of a database system for execution.

Abstract: The subject technology receives, during a query compilation process, a query directed to a set of source tables. The subject technology performs, during the query compilation process, a modification of the query for adjusting at least one pruning operation. The subject technology determines, during a pruning process of a second query, the second query directed to a set of files in a database system and including a set of pruning operations on the set of files, whether to perform a pruning cutoff on the set of pruning operations, the pruning process performing a depth first search of a pruner tree structure, the set of files comprising a set of micro-partitions. The subject technology performs the pruning cutoff based on the determining, the pruning cutoff ceasing at least one pruning operation from the set of pruning operations.

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: A query result set is an example of a type of body of data whose content is defined by a query. Modifications to a database can change the result of a query and therefore what the content of such a body of data, such as a result set, should be. Active Queries is an approach that enables a database server to detect database changes that alter the result of a query registered for a client and to notify a client of those changes. The notifications may be sent to, for example, a cache manager responsible for maintaining coherency of a result set cache generated by the query. The notification notifies the cache manager of when and/or what changes are needed to maintain the coherency of the cache.

Abstract: During a query compilation process, a query is received that is 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. During the query compilation process, a modification of the query is performed for adjusting the at least one pruning operation, the modification being based 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 set of statistics indicating at least an amount of execution time for each previous query associated with each of the previous pruning operations. The query is compiled including the modification of the query. The compiled query is provided to an execution node of a database system for execution.

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 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: Innovative techniques are disclosed for performing a combined sort and aggregation operation involving eagerly performing aggregation while sorting. The techniques described herein enable an aggregation and a group-by operation to be performed using an amount of system memory that is far less than the system memory required to store all the data records being processed while minimizing the need to spill data to disk. This combined sort and aggregation operation has better performance than conventional techniques since system memory is used more efficiently. In certain embodiments, a combined sort and aggregation operation is disclosed that enables the efficient sorting and aggregation of data records when the desired aggregation function is composable (such as SUM, COUNT, MIN and MAX aggregate operations).

Abstract: An apparatus has processing circuitry to perform, in response to decoding of an iterative-operation instruction by the instruction decoder, an iterative operation comprising at least two iterations of processing where one iteration depends on an operand generated in a previous iteration. Preliminary information generating circuitry performs a preliminary portion of processing for a given iteration to generate preliminary information. Result generating circuitry performs a remaining portion of processing for the given iteration, to generate a result value using the preliminary information. Forwarding circuitry forwards the result value as an operand for a next iteration of the iterative operation, for iterations other than the final iteration. The preliminary information generating circuitry starts performing the preliminary portion for the next iteration in parallel with the result generating circuitry completing the remaining portion for the current iteration, to improve performance.

Abstract: An apparatus has processing circuitry to perform, in response to decoding of an iterative-operation instruction by the instruction decoder, an iterative operation comprising at least two iterations of processing where one iteration depends on an operand generated in a previous iteration. Preliminary information generating circuitry performs a preliminary portion of processing for a given iteration to generate preliminary information. Result generating circuitry performs a remaining portion of processing for the given iteration, to generate a result value using the preliminary information. Forwarding circuitry forwards the result value as an operand for a next iteration of the iterative operation, for iterations other than the final iteration. The preliminary information generating circuitry starts performing the preliminary portion for the next iteration in parallel with the result generating circuitry completing the remaining portion for the current iteration, to improve performance.

Abstract: Innovative techniques are disclosed for performing a combined sort and aggregation operation involving eagerly performing aggregation while sorting. The techniques described herein enable an aggregation and a group-by operation to be performed using an amount of system memory that is far less than the system memory required to store all the data records being processed while minimizing the need to spill data to disk. This combined sort and aggregation operation has better performance than conventional techniques since system memory is used more efficiently. In certain embodiments, a combined sort and aggregation operation is disclosed that enables the efficient sorting and aggregation of data records when the desired aggregation function is composable (such as SUM, COUNT, MIN and MAX aggregate operations).

Abstract: Innovative techniques are disclosed for performing a combined sort and aggregation operation involving eagerly performing aggregation while sorting. The techniques described herein enable an aggregation and a group-by operation to be performed using an amount of system memory that is far less than the system memory required to store all the data records being processed while minimizing the need to spill data to disk. This combined sort and aggregation operation has better performance than conventional techniques since system memory is used more efficiently. In certain embodiments, a combined sort and aggregation operation is disclosed that enables the efficient sorting and aggregation of data records when the desired aggregation function is composable (such as SUM, COUNT, MIN and MAX aggregate operations).

Abstract: Innovative techniques are disclosed for performing a combined sort and aggregation operation involving eagerly performing aggregation while sorting. The techniques described herein enable an aggregation and a group-by operation to be performed using an amount of system memory that is far less than the system memory required to store all the data records being processed while minimizing the need to spill data to disk. This combined sort and aggregation operation has better performance than conventional techniques since system memory is used more efficiently. In certain embodiments, a combined sort and aggregation operation is disclosed that enables the efficient sorting and aggregation of data records when the desired aggregation function is composable (such as SUM, COUNT, MIN and MAX aggregate operations).

Abstract: A method and apparatus for compression units in an index block is provided. A particular leaf block of a database index for a table is generated. The particular leaf block corresponds to a particular range of key values. A compression scheme is determined for a plurality of index entries with key values within the particular range. A compression unit that includes a plurality of compressed index entries is generated by applying the compression scheme to the plurality of index entries. Compression metadata describing the compression scheme is generated. The compression unit and the compression metadata is stored in the particular leaf block. In response to a request, at least a portion of the compression unit is decompressed to access one or more index entries.

Abstract: Compression of extensive, rule-based grammars used to facilitate search queries is provided herein. Rule-based grammars include a list of rules that each comprise a sequence of token classes. Each token class is a logical grouping of tokens, and each token is a string of characters. A grammar is parsed to identify rules and token classes. Unimportant token classes are identified and sets of unimportant token classes are merged to generated merged token classes. A compressed grammar is generated by substituting the merged token classes into the grammar for corresponding unimportant token classes used to generate the merged token classes.

Abstract: Compression of extensive, rule-based grammars used to facilitate search queries is provided herein. Rule-based grammars include a list of rules that each comprise a sequence of token classes. Each token class is a logical grouping of tokens, and each token is a string of characters. A grammar is parsed to identify rules and token classes. Unimportant token classes are identified and sets of unimportant token classes are merged to generated merged token classes. A compressed grammar is generated by substituting the merged token classes into the grammar for corresponding unimportant token classes used to generate the merged token classes.

Abstract: Compression of extensive, rule-based grammars used to facilitate search queries is provided herein. Rule-based grammars includes a list of rules that each comprise a sequence of token classes. Each token class is a logical grouping of tokens, and each token is a string of characters. A grammar is parsed to identify rules and token classes. Unimportant token classes are identified and sets of unimportant token classes are merged to generated merged token classes. A compressed grammar is generated by substituting the merged token classes into the grammar for corresponding unimportant token classes used to generate the merged token classes.