Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: Systems and methods that provide for executing a machine learning model in lockstep with a real-time transaction processing system are described. An example system includes a feature store in a memory, processes storing real-time data, including a clock signal, in designated memory regions in the feature store, and processes controlling the execution of the machine learning model in accordance with the clock signal.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Abstract: Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.

Abstract: Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction request could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.

Abstract: A cloud computer system is provided that includes a plurality of computer devices and a database. The plurality of computer devices execute a plurality of virtual machines, with one of the virtual machines serving as a controller node and the remainder serving as worker instances. The controller node is programmed to accept a request to initiate a distributed process that includes a plurality of data jobs, determine a number of worker instances to create across the plurality of computer devices, and cause the number of worker instances to be created on the plurality of computer devices. The worker instances are programmed to create a unique message queue for the corresponding worker instance, and store a reference for the unique message queue that was created for the corresponding worker to the database. The controller node retrieves the reference to the unique message queues and posts jobs to the message queues for execution by the worker instances.

Abstract: A computer system is provided for retrospectively processing a data structure that includes a plurality of entries. The computer system determines if certain data transactions requests that have been recorded in the data structure could have been executed differently (e.g., by being processed at an earlier point in time). For a given entry in the data structure, the system determines if data transaction quest could have at least partly succeeded against a prior recorded state of at least one of two ordered lists of pending data transaction requests. Another entry is then found that caused the initial entry to fail in execution and a time delta is stored between the timestamp of the another entry and the timestamp of the initial entry.