A method for execution by a query processing system includes determining a query request that indicates a plurality of operators, where the plurality of operators includes at least one relational algebra operator and further includes at least one non-relational operator. A query operator execution flow is generated from the query request that indicates a serialized ordering of the plurality of operators. A query resultant of the query is generated by facilitating execution of the query via a set of nodes of a database system that each perform a plurality of operator executions in accordance with the query operator execution flow, where a subset of the set of nodes each execute at least one operator execution corresponding to the at least one non-relational operator in accordance with the execution of the query.

Herein are techniques for dynamic aggregation of results of a database request, including concurrent grouping of result items in memory based on quasi-dense keys. Each of many computational threads concurrently performs as follows. A hash code is calculated that represents a particular natural grouping key (NGK) for an aggregate result of a database request. Based on the hash code, the thread detects that a set of distinct NGKs that are already stored in the aggregate result does not contain the particular NGK. A distinct dense grouping key for the particular NGK is statefully generated. The dense grouping key is bound to the particular NGK. Based on said binding, the particular NGK is added to the set of distinct NGKs in the aggregate result.

Systems and processes for efficient accessing, storing and transmitting of fixed data elements and dynamic data elements, each having its own native form. The data elements are organized according to a schema, with (a) all fixed data elements stored in their native forms in a fixed memory allocation, and (b) each dynamic data element stored in memory in its own native form, in its own data allocation. With this memory structure, computational overhead of converting data elements from their native forms to JSON, XML or other markup language is avoided, making accessing data (getting), updating data (setting), converting data to a serial stream for transmission or other manipulation (serializing), deserializing, and other manipulations of the data elements much more CPU efficient and requiring less bandwidth.

Various embodiments set forth techniques for free space management in a block store. The techniques include receiving a request to allocate one or more blocks in a block store, accessing a sparse hierarchical data structure to identify an allocator page identifying a region of a backing store having a greatest number of free blocks, and allocating the one or more blocks.

A method, software, database and system for attribute partner identification and social network based attribute analysis are presented in which attribute profiles associated with individuals can be compared and potential partners identified. Connections can be formed within social networks based on analysis of genetic and non-genetic data. Degrees of attribute separation (genetic and non-genetic) can be utilized to analyze relationships and to identify individuals who might benefit from being connected.

A verification platform may include a data connection to receive a stream of industrial asset data, including a subset of the industrial asset data, from industrial asset sensors. The verification platform may store the subset of industrial asset data into a data store, the subset of industrial asset data being marked as invalid, and record a hash value associated with a compressed representation of the subset of industrial asset data combined with metadata in a secure, distributed ledger (e.g., associated with blockchain technology). The verification platform may then receive a transaction identifier from the secure, distributed ledger and mark the subset of industrial asset data in the data store as being valid after using the transaction identifier to verify that the recorded hash value matches a hash value of an independently created version of the compressed representation of the subset of industrial asset data combined with metadata.

A method for managing big metadata using columnar techniques includes receiving a query request requesting data blocks from a data table that match query parameters. The data table is associated with system tables that each includes metadata for a corresponding data block of the data table. The method includes generating, based on the query request, a system query to return a subset of rows that correspond to the data blocks that match the query parameters. The method further includes generating, based on the query request and the system query, a final query to return a subset of data blocks from the data table corresponding to the subset of rows. The method also includes determining whether any of the data blocks in the subset of data blocks match the query parameters, and returning the matching data blocks when one or more data blocks match the query parameters.

A method for execution by a dispersed storage network (DSN) managing unit includes receiving access information from a plurality of distributed storage and task (DST) processing units via a network. Cache memory utilization data is generated based on the access information. Configuration instructions are generated for transmission via the network to the plurality of DST processing units based on the cache memory utilization data.

Systems and methods are described for exporting bucket data from one or more buckets to one or more worker nodes. The system can identify data from different bucket data from buckets stored in a data intake and query system that is to be processed by one or more worker nodes. The system can allocate one or more execution resources, such as a processing pipeline, to process and export the bucket data from the buckets. The system can assign bucket data corresponding to individual buckets to the execution resource based on a bucket distribution policy. The indexer can export the bucket data to the worker nodes for further processing based on the bucket data-execution resource assignment.

Systems and methods for managing Application Programming Interfaces (APIs) are disclosed. Systems may involve automatically generating a honeypot. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a client device, a call to an API node and classifying the call as unauthorized. The operation may include sending the call to a node-imitating model associated with the API node and receiving, from the node-imitating model, synthetic node output data. The operations may include sending a notification based on the synthetic node output data to the client device.