Deterministic progressive big data analytics
First Claim
Patent Images
1. A system comprising:
- a device that includes at least one processor, and a computer readable storage medium storing instructions for execution by the at least one processor, for implementing a distributed progressive analytics engine that comprises;
a data item acquisition component that obtains a plurality of data items, the respective data items comprising respective data tuples that are each respectively annotated with progress markers indicating progress points associated with atemporal processing progress of the respective data tuples, each respective progress marker including a respective progress interval associated with each respective one of the plurality of data tuples; and
a progressive distributed processing manager that initiates deterministic, massively parallel, progressive processing of the plurality of data items on a plurality of devices, the progress markers indicating which of the plurality of data tuples are to be incorporated into results of the progressive processing, the progress markers further indicating an ordering for incorporation of the respective data tuples into the results, each respective progress interval comprising a respective progress-start attribute value indicating a first logical point where the respective data tuple enters a portion of computation included in the progressive processing, and a respective progress-end attribute value indicating a second logical point where the respective data tuple exits the portion of computation.
2 Assignments
0 Petitions
Accused Products
Abstract
A plurality of data items that are annotated with progress markers may be obtained. The progress markers may indicate progress points associated with atemporal processing progress of the respective data items. Deterministic, massively parallel, progressive processing may be initiated on the plurality of data items on a plurality of devices, the progress markers indicating which of the plurality of data items are to be incorporated into results of the progressive processing, the progress markers further indicating an ordering for incorporation of the respective data items into the results.
-
Citations
20 Claims
-
1. A system comprising:
a device that includes at least one processor, and a computer readable storage medium storing instructions for execution by the at least one processor, for implementing a distributed progressive analytics engine that comprises; a data item acquisition component that obtains a plurality of data items, the respective data items comprising respective data tuples that are each respectively annotated with progress markers indicating progress points associated with atemporal processing progress of the respective data tuples, each respective progress marker including a respective progress interval associated with each respective one of the plurality of data tuples; and a progressive distributed processing manager that initiates deterministic, massively parallel, progressive processing of the plurality of data items on a plurality of devices, the progress markers indicating which of the plurality of data tuples are to be incorporated into results of the progressive processing, the progress markers further indicating an ordering for incorporation of the respective data tuples into the results, each respective progress interval comprising a respective progress-start attribute value indicating a first logical point where the respective data tuple enters a portion of computation included in the progressive processing, and a respective progress-end attribute value indicating a second logical point where the respective data tuple exits the portion of computation. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
13. A computer-readable storage medium storing executable instructions that, when executed, cause one or more processors to:
-
obtain a plurality of data items, the respective data items comprising respective data tuples that are each annotated with progress markers indicating progress points associated with atemporal processing progress of the respective data tuples, each respective progress marker including a respective progress interval associated with each respective one of the plurality of data tuples; and initiate deterministic, massively parallel, progressive processing of the plurality of data items on a plurality of devices, the progress markers indicating which of the plurality of data tuples are to be incorporated into results of the progressive processing, the progress markers further indicating an ordering for incorporation of the respective data tuples into the results, each respective progress interval comprising a respective progress-start attribute value indicating a first logical point where the respective data tuple enters a portion of computation included in the progressive processing, and a respective progress-end attribute value indicating a second logical point where the respective data tuple exits the portion of computation. - View Dependent Claims (14, 15, 16, 17, 18, 19)
-
-
20. A method comprising:
-
obtaining a plurality of data items, the respective data items comprising respective data tuples that each are annotated with progress markers indicating progress points associated with atemporal processing progress of the respective data tuples, each respective progress marker including a respective progress interval associated with each respective one of the plurality of data tuples; and initiating, via a device processor, deterministic, massively parallel, progressive processing of the plurality of data items on a plurality of devices, the progress markers indicating which of the plurality of data tuples are to be incorporated into results of the progressive processing, the progress markers further indicating an ordering for incorporation of the respective data tuples into the results, each respective progress interval comprising a respective progress-start attribute value indicating a first logical point where the respective data tuple enters a portion of computation included in the progressive processing, and a respective progress-end attribute value indicating a second logical point where the respective data tuple exits the portion of computation.
-
Specification