A method includes generating a plurality of parity blocks from a plurality of lines of data blocks. The plurality of lines of data blocks are stored in data sections of memory of a cluster of computing devices of the computing system by distributing storage of individual data blocks of the plurality of lines of data blocks among unique data sections of the cluster of computing devices. The plurality of parity blocks are stored in parity sections of memory of the cluster of computing devices by distributing storage of parity blocks of the plurality of parity blocks among unique parity sections of the cluster of computing devices.

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.

Aspects of the present disclosure relate to systems and methods for automatic management of digital data volumes logically maintained in a dynamically scalable fault tolerant matrix. The data volumes may be distributed across a cluster of connected server nodes included in a cloud computing architecture. A processing device in communication with the matrix ensure that read/write request may be serviced by the matrix to access the digital data maintained within the data volumes may be continuously accessed, regardless of data volume failure that are missing, offline, or in a failed state.

A data input sub-system of a large scale application specific computing system receives a data set that includes a plurality of records, each with a plurality of data fields, and divides the data set into a plurality of data segments. The data input sub-system further restructures records of data segments based on a key field of the plurality of data fields to produce restructured data segments and generates storage instructions for storing the restructured data segments. A data storage and processing sub-system of the computing system interprets the storage instructions to determine resources to engage and stores the restructured data segments using engaged resources. A query and results sub-system of the computing system generates an initial query plan based on a data processing request, optimizes the initial query plan to produce an optimized query plan, and sends the optimized query plan to the data storage and processing sub-system for execution.

One or more aspects of the present disclosure relate to recovering at least one failed disk. In embodiments, determining a storage reserve capacity allocated for recovering at least one storage device of a storage array is determined. Zero or more storage portions from each storage device of at least one storage cluster for disk recovery are adaptively assigned based on the storage reserve capacity. The failing and/or failed disk using the assigned storage portions is recovered in response to detecting a failing and/or failed disk.

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.

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.

A computing device comprises a plurality of nodes and a plurality of operating system layers. The plurality of operating system layers includes a local database operating system and a sub-system database operating system. The plurality of nodes utilize the local database operating system to execute at least one database operation independently of other ones of the plurality of nodes. The computing device utilizes the sub-system database operating system in conjunction with other ones of a plurality of computing devices of at least one sub-system to facilitate execution of at least one sub-system operation of the at least one sub-system.

A method includes generating a plurality of parity blocks from a plurality of lines of data blocks. The plurality of lines of data blocks are stored in data sections of memory of a cluster of computing devices of the computing system by distributing storage of individual data blocks of the plurality of lines of data blocks among unique data sections of the cluster of computing devices. The plurality of parity blocks are stored in parity sections of memory of the cluster of computing devices by distributing storage of parity blocks of the plurality of parity blocks among unique parity sections of the cluster of computing devices.

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.