Visually exploring and analyzing event streams

• US 9,972,103 B2
• Filed: 09/25/2015
• Issued: 05/15/2018
• Est. Priority Date: 07/24/2015
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: de Castro Alves, Alexandre, Thukkaram, Prabhu, Markovskii, Dmitrii, Shikalov, Ilya, Bychkov, Vitaly, Nikiforova, Natalia
• Primary Examiner(s): Sheng, Xin
• Application Number:
  US14/866,512
• Publication Number:
  US 20170024912A1
• Time in Patent Office: 963 Days
• Field of Search: None
• CPC Class Codes: G06F 16/24568 Data stream processing; Continuous queries
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06T 11/206 Drawing of charts or graphs

Abstract

Some event ordering requirements can be determined based on continuous event processing queries. Other event ordering requirements can be determined based on distribution flow types being used to distribute events from event streams to node executing the queries. Events from event streams can be ordered according to ordering semantics that are based on a combination of all of these event ordering requirements. Additionally, virtual computing nodes can be associated with constraints, and computing processors can be associated with capabilities. Virtual computing nodes for processing event streams can be assigned to execute on various computing processors based on both these constraints and capabilities. Additionally, for each of several events in an event stream, a ratio between a total latency and a communication latency can be for determined. Based on an average of these ratios, a quantity of reducing nodes that will be involved in a map-reduce operation can be selected.

Claims

1. A method, comprising:

receiving, by one or more continuous query language (CQL) processors, source events;

storing, by the one or more CQL processors, the source events in a data store;

enriching, by the one or more CQL processors, the stored source events with contextual data contained in the data store;

receiving, from a service associated with the data store, Java application programming interfaces (APIs) particular to the data store for retrieving the enriched source events;

making, by the one or more CQL processors, API calls of the received Java APIs to the data store, the API calls configured to request an event stream that includes the enriched source events;

displaying, by the one or more CQL processors, a graph that includes a plurality of first points representing a plurality of first events from the event stream and a plurality of second points representing a plurality of second events from the event stream;

receiving, by the one or more CQL processors, a first event of the plurality of first events from the event stream;

in response to receiving the first event, plotting, in the graph, a first point corresponding to the first event with a first color that visually distinguishes the first point from at least a one other color associated with a remainder of the plurality of points;

receiving, by the one or more CQL processors, a second event of the plurality of second events from the event stream;

in response to receiving the second event;

determining a correlation coefficient between the first event and the second event;

determining a correlation color corresponding to the correlation coefficient; and

plotting, in the graph, a second point corresponding to the second event with the correlation color;

receiving, by the one or more CQL processors, a third event of the plurality of first events from the event stream; and

in response to receiving the third event;

plotting, in the graph, a third point corresponding to the third event with the first color; and

changing a color of the first point to match the at least one other color associated with the remainder of the plurality of points.

2. The method of claim 1, wherein the graph comprises a scatter plot.

3. The method of claim 1, wherein the X-axis or the Y-axis of the graph are based at least in part on a property of the plurality of events from the event stream.

4. The method of claim 3, further comprising receiving identification of the property from a user associated with the event stream.

5. The method of claim 3, further comprising selecting the property based at least in part on an order of output of the event stream.

6. The method of claim 5, wherein the property comprises a numeric value.

7. The method of claim 3, wherein the Y-axis represents a response variable.

8. The method of claim 1, wherein a size of each of the plurality of points is based at least in part on a respective property of each of the plurality of events from the event stream.

9. The method of claim 1, further comprising removing a number of the plurality of points from the graph, the number based at least in part on a visual characteristic of the graph.

10. The method of claim 1, wherein the graph comprises a scatter plot in which one axis represents a time of a particular event and another axis represents a value of the particular event, wherein the plurality of events of the event stream are received over a time interval, and the method further comprises:

plotting a point that corresponds to the particular event;

determining a revised smoothed curve fitter based at least in part on points contained in the scatter plot; and

re-drawing the revised smoothed curve fitter in the scatter plot.

11. The method of claim 1, wherein the graph comprises a scatter plot in which one axis represents a time of a particular event and another axis represents a value of the particular event, wherein the plurality of events of the event stream are received over a time interval, and the method further comprises:

plotting a point that corresponds to the particular event;

determining one or more clusters of points contained in the scatter plot; and

re-drawing, on the scatter plot, one or more shapes that represent the one or more clusters and include points belonging to those clusters.

12. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by one or more processors, configures one or more computer systems to perform at least:

instructions that cause the one or more continuous query language (CQL) processors to receive source events;

instructions that cause the one or more CQL processors to store the source events in a data store,

instructions that cause the one or more CQL processors to enrich the stored source events with contextual data contained in the data store;

instructions that cause the one or more CQL processors to receive, from a service associated with the data store, Java application programming interfaces (APIs) particular to the data store for retrieving the enriched source events;

instructions that cause the one or more CQL processors to make (API) calls of the received Java APIs to the data store, the API calls configured to request an event stream that includes the enriched source events;

instructions that cause the one or more CQL processors to display a graph that includes a plurality of first points representing a plurality of first events from the event stream and a plurality of second points representing a plurality of second events from the event stream;

instructions that cause the one or more CQL processors to receive a first event of the plurality of first events from the event stream;

instructions that cause the one or more CQL processors to plot, in the graph, a first point corresponding to the first event with a first color that visually distinguishes the first point from at least a one other color associated with a remainder of the plurality of points in response to receiving the first event;

instructions that cause the one or more CQL processors to receive a second event of the plurality of second events from the event stream;

instructions that cause the one or more CQL processors to, in response to receiving the second event;

determine a correlation coefficient between the first event and the second event;

determine a correlation color corresponding to the correlation coefficient; and

plot, in the graph, a second point corresponding to the second event with the correlation color;

instructions that cause the one or more CQL processors to receive a third event of the plurality of first events from the event stream; and

instructions that cause the one or more CQL processors to plot, in the graph, a third point corresponding to the third event with the first color and change a color of the first point to match the at least one other color associated with the remainder of the plurality of points in response to receiving the second event.

13. The non-transitory computer-readable medium of claim 12, wherein the one or more computer systems are further configured to perform instructions that cause the one or more CQL processors to receive identification, from a user, of a property of the plurality of events from the event stream.

14. The non-transitory computer-readable medium of claim 13, wherein the property is utilized to represent values of the X-axis or the Y-axis of the graph.

15. The non-transitory computer-readable medium of claim 13, wherein the property comprises a non-numeric value.

16. The non-transitory computer-readable medium of claim 12, wherein a size of each of the plurality of points is based at least in part on a respective property of each of the plurality of events from the event stream.

17. A system, comprising:

a memory storing a plurality of instructions; and

a continuous query language (CQL) processor configured to access the memory, the CQL processor further configured to execute the plurality of instructions to at least;

receive source events;

store the source events in a data store;

enrich the stored source events with contextual data contained in the data store;

receive, from a service associated with the data store, Java application programming interfaces (APIs) particular to the data store for retrieving the enriched source events;

make (API) calls of the received Java APIs to the data store, the API calls configured to request an event stream that includes the enriched source events;

display a graph that includes a plurality of first points representing a plurality of first events from the event stream and a plurality of second points representing a plurality of second events from the event stream;

receive a first event of the plurality of first events from the event stream;

in response to receiving the first event, plot, in the graph, a first point corresponding to the first event with a first color that visually distinguishes the first point from at least a one other color associated with a remainder of the plurality of points;

receive a second event of the plurality of second events from the event stream;

in response to receiving the second event;

determine a correlation coefficient between the first event and the second event;

determine a correlation color corresponding to the correlation coefficient; and

plot, in the graph, a second point corresponding to the second event with the correlation color;

receive a third event of the plurality of first events from the event stream; and

in response to receiving the third event;

plot, in the graph, a third point corresponding to the third event with the first color; and

change a color of the first point to match the at least one other color associated with the remainder of the plurality of points.

18. The system of claim 17, wherein the processor is further configured to execute the plurality of instructions to at least remove a number of the plurality of points from the graph, the number based at least in part on a visual characteristic of the graph.

19. The system of claim 17, wherein the graph comprises a scatter plot in which one axis represents a time of a particular event and another axis represents a value of the particular event, wherein the plurality of events of the event stream are received over a time interval, and wherein the processor is further configured to execute the plurality of instructions to at least:

plot a point that corresponds to the particular event;

determine a revised smoothed curve fitter based at least in part on points contained in the scatter plot; and

re-draw the revised smoothed curve fitter in the scatter plot.

20. The system of claim 17, wherein the graph comprises a scatter plot in which one axis represents a time of a particular event and another axis represents a value of the particular event, wherein the plurality of events of the event stream are received over a time interval, and wherein the processor is further configured to execute the plurality of instructions to at least:

plot a point that corresponds to the particular event;

determine one or more clusters of points contained in the scatter plot; and

re-draw, on the scatter plot, one or more shapes that represent the one or more clusters and include points belonging to those clusters.