An instrumentation analysis system processes data streams by executing instructions specified using a data stream language program. The data stream language allows users to specify a search condition using a find block for identifying the set of data streams processed by the data stream language program. The set of identified data streams may change dynamically. The data stream language allows users to group data streams into sets of data streams based on distinct values of one or more metadata attributes associated with the input data streams. The data stream language allows users to specify a threshold block for determining whether data values of input data streams are outside boundaries specified using low/high thresholds. The elements of the set of data streams input to the threshold block can dynamically change. The low/high threshold values can be specified as data streams and can dynamically change.

Writing data to storage utilizing a diverged thread for asynchronous write operations is provided. On a first thread, an analysis engine analyzes and identifies changed information to write to storage and an I/O manager copies the writes into buffers and places the buffers into a queue, while on a second thread, a flushless transactional layer (FTL) drive executes the writes to storage. By allowing the analysis to continue and enqueue writes on a first thread while the writes are written to storage on a second thread, the CPU and I/O of the system are utilized in parallel. Accordingly, efficiency of the computing device is improved.

A method for sorting a data table is provided. The method may include providing a plurality of attribute value information for each data block of the data table. The method may also include receiving a query requiring a sorting on the first attribute of the data table. The method may further include determining a plurality of sequences of a plurality of data blocks having disjoint value ranges of the first attribute based on the provided plurality of attribute value information. The method may also include, for each determined sequence of the plurality of data blocks, reading a plurality of data, sorting the read plurality of data from each data block, and concatenating the sorted plurality of data from the plurality of data blocks within the determined sequence, thereby providing a sorted plurality of sequences. The method may further include merging the sorted plurality of sequences.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.

Systems and methods for transaction/file-based management of a plurality of processes associated with various jobs are provided. Through the management of discrete applications, a file distribution manager/scheduler orchestrates automated execution of different types of jobs. The processes executed for the various processes can vary based on job type, or other parameters.

Techniques are disclosed relating to processing database transactions that include application operations defined by different object relational mapping (ORM) libraries. A transaction router module executing on a computer system receives, from an application, a request for a first database transaction, where the first database transaction includes first and second application operations. The transaction router module then translates the first application operation to one or more first database operations using a first ORM library and the second application operation to one or more second database operations using a second ORM library. Then, the transaction router module determines one or more database connections for the one or more first database operations and the one or more second database operations. Such techniques may advantageously allow applications to switch between using different persistence frameworks and message broker frameworks without substantial adjustments to application code.

A transaction data processing method includes: receiving a first transaction document from a device of a transaction initiator, the first transaction document being associated with identity labels of a plurality of transaction participants; separately performing identity authentication on the plurality of transaction participants according to the identity labels of the plurality of transaction participants, to obtain an identity authentication result. The method also includes adding the identity authentication result into the first transaction document when the identity authentication results indicates identity authentication of each of the plurality of transaction participants is successful, to generate a second transaction document carrying the identity authentication result; separately transmitting a signature request for the second transaction document to devices of the plurality of transaction participants; and generating a third transaction document according to responses returned by the devices of the plurality of transaction participants in response to the signature request.

An instrumentation analysis system processes data streams by executing instructions specified using a data stream language program. The data stream language allows users to specify a search condition using a find block for identifying the set of data streams processed by the data stream language program. The set of identified data streams may change dynamically. The data stream language allows users to group data streams into sets of data streams based on distinct values of one or more metadata attributes associated with the input data streams. The data stream language allows users to specify a threshold block for determining whether data values of input data streams are outside boundaries specified using low/high thresholds. The elements of the set of data streams input to the threshold block can dynamically change. The low/high threshold values can be specified as data streams and can dynamically change.

Disclosed in some examples are systems, methods, devices, and machine-readable mediums to detect and terminate programmable atomic transactions that are stuck in an infinite loop. In order to detect and terminate these transactions, the programmable atomic unit may use an instruction counter that increments each time an instruction is executed during execution of a programmable atomic transaction. If the instruction counter meets or exceeds a threshold instruction execution limit without reaching the termination instruction, the programmable atomic transaction may be terminated, all resources used (e.g., memory locks) may be freed, and a response may be sent to a calling processor.

A verification device operates to evaluate consistency of input values from a client device used by a server to execute a task. In an example the task may be installation of software into the client device, and the consistency evaluation of the input values may involve evaluating whether identifiers used to obtain attribute values of components of the client device for the installation apply to the same client device. To initiate execution of the task, the client device commands a plurality of data source servers to supply the attribute values. The data source servers return response messages defining the attribute values associated with the identifiers supplied by the client device. The client device supplies the response messages to the server for use in the execution of the task. Before executing the task, the server supplies information from the response messages to a verification device, the information defining a combination of the identifiers of the response messages, as well as the combination of data source servers that have defined attribute values associated with the identifiers. The verification device performing a consistency evaluation on said combination of identifiers, dependent on whether said combination of identifiers is consistent or inconsistent with previously stored combinations of identifiers for said combination of data source servers stored for previously executed tasks and/or whether values of a corresponding further attribute associated with the identifiers in the data source servers in the combination of data source servers are consistent. The server selecting between executing the task or not dependent on a result of the consistency evaluation.