Abstract: A database system is operable to determine a query expression that includes a call to a differentiation function, and execute the query expression based on determining an ordered set of input rows to the differentiation function based on accessing a corresponding plurality of relational database rows in at least one relational database table, and further based on generating an ordered set of output values as output of executing the differentiation function upon the ordered set of input rows based on performing a window function upon each row in the ordered set of input rows to return a differentiation output value for the each row as a function of a set of multiple consecutive rows in the ordered set of input rows that includes the each row.

Abstract: A query processing system is operable to determine a set of query rules that includes a minimum result set size rule. A query is received from a requesting entity. A size of a result set of the query is determined. Compliance data is determined based on determining whether the size of the result set complies with the minimum result set size rule. When the compliance data indicates the size of the result set complies with the minimum result set size rule, a query result for the query is generated based on the result set, and the query result is generated to the requesting entity. When the compliance data indicates the size of the result set does not comply with the minimum result set size rule: transmission of the query result to the requesting entity is foregone.

Abstract: A method includes obtaining a plurality of data partitions of a data set for storage in a database system. The method further includes determining a first data storage coding scheme for a first partition of the plurality of data partitions, where the first data storage coding scheme includes first encoding parameters regarding encoding the first partition into first data segments and first parity segments. The method further includes determining a second data storage coding scheme for a second partition of the plurality of data partitions. The method further includes dividing the first partition to produce a first number of first raw data segments, where the first number is based on the first data storage coding scheme. The method further includes dividing the second partition to produce a second number of second raw data segments, where the second number is based on the second data storage coding scheme.

Abstract: A database system is operable to determine a query for execution against at least one relational database table and executing the query. Executing the query is based on identifying a plurality of required binomial coefficient values required for generating a set of output values for the query. The plurality of required binomial coefficient values are precomputed and stored in cache memory resources. Generating each output value of the set of output values is based on identifying a subset of the plurality of required binomial coefficient values for generating the each output value, and accessing the subset of the plurality of required binomial coefficient value in the cache memory resources. Each output value is generated as a function of the subset of the plurality of required binomial coefficient values.

Abstract: A node of a computing system includes a main memory and a plurality of processing core resources. The main memory includes a computing device section and a database section. The computing device section includes a computing device operating system area and a computing device general area. The database section includes a database section that includes a database operating system area, a disk area, a network area, and a database general area. The database operating system area allocates at least one portion of the main memory for database operations that is locked from access by the computing device operating system area.

Abstract: A database system is operable to read a plurality of rows from memory of a relational database stored in memory resources. Each of the plurality of rows are assigned to a corresponding one of a plurality of training data subsets of the plurality of rows based on performing a row dispersal process. A plurality of sets of candidate model coefficients are generated based on executing a plurality of parallelized optimization processes. Each set of candidate model coefficients is generated based on executing a corresponding parallelized optimization process upon a corresponding training data subset independently from executing other ones of the plurality of parallelized optimization processes upon other ones of the plurality of training data subsets. A most favorable set of candidate model coefficients is selected from the plurality of sets of candidate model coefficients generated via the plurality of parallelized optimization processes.

Abstract: A database system is operable to generate a query operator execution flow for a query that includes a plurality of operators implementing a plurality of parallelized optimization processes configured to facilitate generating of a machine learning model. The query operator execution flow is executed in conjunction with executing the query based on executing the plurality of operators. Executing each of the plurality of parallelized optimization processes includes generating a corresponding set of candidate model coefficients of a plurality of sets of candidate model coefficients. A corresponding set of candidate model coefficients is based on processing the set of best positions generated via the second type of optimization algorithm. The machine learning model is generated in executing the query based on selection of a most favorable set of candidate model coefficients from a plurality of sets of candidate model coefficients outputted via the plurality of parallelized optimization processes.

Abstract: A computing device includes a computing device controller hub and a plurality of parallelized nodes coupled to the computing device controller hub. Each node of the plurality of parallelized nodes includes a central processing module, a main memory, and at least one disk memory. The plurality of computing devices is operable to collectively execute query requests against at least one database table stored by the plurality of computing devices based on each node of each computing device performing corresponding operations independently from other nodes of the plurality of parallelized nodes.

Abstract: A node includes a plurality of processing core resources. Each processing core resource of the plurality of processing core resources includes a corresponding processing module, a corresponding memory interface module, a corresponding memory device, and a corresponding cache memory. The plurality of processing core resources of the node is operable to collectively perform corresponding operations of the node. Each processing core resource of the plurality of processing core resources of the node is operable to perform operations independently from other ones of the plurality of processing core resources of the node.

Abstract: A computing system is operable to generate a plurality of lines of coding blocks that includes a plurality of data blocks and a plurality of parity blocks. Each of the plurality of lines of coding blocks includes a corresponding subset of data blocks a corresponding subset of parity blocks. A set of segments of a segment group are generated to collectively include the plurality of lines of coding blocks. Different coding blocks of each of the plurality of lines of coding blocks are included within different ones of the set of segments, and the plurality of parity blocks are dispersed across all of the set of segments. The set of segments are stored via a plurality of nodes sets, where different segments of the set of segments are stored via memory resources of different node sets of the plurality of node sets.

Abstract: A database system is operable to determine a plurality of queries for execution. Query data for each query of the plurality of queries is determined, where the query data for the each query indicates a memory usage estimate, an internal runtime estimate, and an external runtime estimate. Query initiation data is generated by determining whether to initiate execution of one query of the plurality of queries at a first temporal period occurring after initiating execution of a subset of the plurality of queries and occurs before the execution of the subset of the plurality of queries is complete, based on the query data of the one query. Execution of the one query is initiated when the query initiation data indicates a determination to initiate execution of the one query in the first temporal period.

Abstract: A node of a database system is operable to receive a plurality of data blocks. Based on backlog detection data, at least one feedback data block is generated to be sent to the set of source nodes. Feedback relay node selection data selecting at least one of the plurality of nodes in the database system for facilitating routing of the at least one feedback data block from the node to at least one of the set of source nodes via a prioritized feedback communication mechanism is generated. The at least one feedback data block is sent to the at least one of the plurality of nodes selected in the feedback relay node selection data. The at least one of the plurality of nodes facilitates routing of the at least one feedback data block from the node via the prioritized feedback communication mechanism.

Abstract: An analytics system is operable to receive a first plurality of query requests from a plurality of requesting entities. Query pricing scheme data is automatically generated based on the first plurality of query requests. A second plurality of query requests are received from the plurality of requesting entities. Query cost data is automatically generated for each of the second plurality of query requests by utilizing the query pricing scheme data. The query cost data for each of the second plurality of query requests is transmitted to a corresponding one of the plurality of requesting entities.

Abstract: A method includes receiving, by a first computing entity of a database system, a data set that is organized in rows and columns. The method further includes determining whether to partition the data set based on a parameter associated with the data set. When determining to partition the data set, the method includes determining partitioning parameters for the data set, and partitioning the data set into a plurality of data partitions in accordance with the partitioning parameters. The method further includes determining a first coding scheme for a first data partition and determining a first number of first raw data segments for a first segment group of the first partition based on the coding scheme. The method further includes dividing the first partition to produce the first number of first raw data segments for storage in the database system.

Abstract: The invention relates to methods for producing an RSV F protein trimer in a fed batch cell culture.

Abstract: A method includes determining a first set of query rules and receiving a query from a requesting entity. The first set of query rules is filtered to generate a proper subset of the first set of query rules by selecting only ones of the first set of query rules with parameter data comparing favorably to parameters of the query. Compliance data indicating whether the query complies with the first set of query rules is generated by determining whether the query complies with the proper subset of the first set of query rules. When the compliance data indicates the query complies with the first set of query rules, a query result is determined for the query and the query result is transmitted to the requesting entity. When the compliance data indicates the query does not comply with the first set of query rules, transmission of the query is foregone.

Abstract: A computing device of a database system includes a plurality of processing modules, a computing device operating system, and an application specific operating system. The application specific operating system includes at least one custom instruction set that configures operation of a configurable set of processing modules of the plurality of processing modules based on generating, for each processing module of the configurable set of processing modules, a corresponding configuration signal indicating a selected instruction set of either the computing device operating system or the application specific operating system. Each processing module of the configurable set of processing modules operates in accordance with the selected instruction set based on the corresponding configuration signal.

Abstract: A query processing system is operable to determining a query pricing scheme and receive a query request from a requesting entity that indicates at least one query function for execution against a database system. Query cost data is generated based on the at least one query function by utilizing the query pricing scheme. The query cost data is transmitted to the requesting entity.

Abstract: A database system is operable to determine a query that includes a join expression for execution. A set of input rows are dispersed for processing via a plurality of parallelized join processes in conjunction with executing the join expression based on identifying a first proper subset of the set of input rows based on a null-handling strategy. First rows in the first proper subset are dispersed for processing across the plurality of parallelized join processes in accordance with the null-handling strategy. second rows in a set difference between the set of input rows and the first proper subset are dispersed across the plurality of parallelized join processes in accordance with a join key-based assignment strategy. The set of input rows are processed via the plurality of parallelized join processes.

Abstract: A query processing system is operable to receive a query expression that includes a call to a computing window function indicating an expression that includes a column reference that includes a prior row index identifier. The computing window function is executed based on accessing at ordered set of rows of the database indicated in the call to the computing window function. An output column is generated based on generating output for each row of a set of rows in the ordered set of rows by evaluating the expression based on performing at least one operation upon a column value, determined based on applying the column reference, of a previous row in the ordered set of rows. A query resultant for the query expression is generated based on the output column generated for the rows in the ordered set of rows.