Optimizing Performance in CEP Systems via CPU Affinity

• US 20180196701A1
• Filed: 01/31/2018
• Published: 07/12/2018
• Est. Priority Date: 05/27/2014
• Status: Active Grant

• Current Assignee: Sybase Incorporated (SAP SE)
• Original Assignee: Sybase Incorporated (SAP SE)
• Inventors: Ahmed, Ibrahim, Gandhi, Palaniappan, Theiding, Mark
• Granted Patent: US 10,503,556 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 9/5033 considering data affinity

Abstract

In an example embodiment performance is optimized in a complex event stream (CEP) system. Information about a plurality of CEP threads is obtained. Then nearness among the plurality of CEP threads is determined, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread. Based on the determined nearness, the plurality of CEP threads are organized into a plurality of CEP thread groups. Then, each of the plurality of CEP thread groups are assigned to a different processing node, with each processing node having one or more processors and a memory.

Claims

1. (canceled)

2. A method for optimizing performance in a complex event stream (CEP) system, the method comprising:

obtaining, using one or more hardware processors, information about a plurality of CEP threads;

determining, using the one or more hardware processors, nearness among the plurality of CEP threads, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread, the nearness between the first and second threads being measured by calculating an actual amount of data transmitted between the first and second threads during a set period;

organizing the plurality of CEP threads into a plurality of CEP thread groups, based on the determined nearness; and

assigning, using the one or more hardware processors, each of the plurality of CEP thread groups to a different processing node of a plurality of processing nodes, each processing node having one or more processors and a memory.

3. The method of claim 2, wherein each processing node is a non-uniform memory access (NUMA) node.

4. The method of claim 2, further comprising:

assigning each of the plurality of CEP threads a value representing processing capacity requested by a corresponding CEP thread; and

wherein the organizing is also based on the values for each of the plurality of CEP threads and information about processing capacity of each processing node.

5. The method of claim 4, wherein the determining nearness includes creating a directed acyclic graph (DAG) with each of the plurality of CEP threads assigned a different node in the DAG and edges between nodes representing data dependencies among the threads;

and

wherein each edge in the DAG is assigned a nearness value.

6. The method of claim 2, wherein the method is performed during startup time.

7. The method of claim 2, wherein the method is performed during runtime.

8. The method of claim 2, further comprising:

creating a thread graph for the plurality of CEP threads; and

wherein the determining nearness includes summing up edges in the thread graph between nodes in the thread graph representing the first and second CEP thread.

9. The method of claim 2, wherein the nearness is determined at least partially based on one or more user hints, the one or more user hints indicating whether a particular thread is dynamic, semi-static, or static.

10. An apparatus comprising:

an event stream processing engine comprising;

an affinity analyzer executable by a processor and configured to;

obtain information about a plurality of CEP threads;

determine nearness among the plurality of CEP threads, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread, the nearness between the first and second threads being measured by calculating an actual amount of data transmitted between the first and second threads during a set period;

organize the plurality of CEP threads into a plurality of CEP thread, groups, based, on the determined nearness; and

assign each of the plurality of CEP thread groups to a different processing node, each processing node having one or more processors and a memory.

11. The apparatus of claim 10, wherein the apparatus is coupled to one or more input adapters receiving input from at least one of the following:

market data feeds, a message bus, network monitoring, application transactions, and internal event streams.

12. The apparatus of claim 10, wherein the analyzer is further configured to create a thread graph for foe plurality of CEP threads, wherein the determining nearness includes summing up edges in the thread graph between nodes in the thread graph representing the first and second CEP thread.

13. The apparatus of claim 10, wherein the nearness is determined at least partially based on one or more user hints, the one or more user hints indicating whether a particular thread is dynamic, semi-static, or static.

14. A non-transitory machine-readable storage medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform operations for optimizing performance in a complex event stream (CEP) system, the operations comprising:

obtaining, using one or more hardware processors, information about a plurality of CEP threads;

determining, using the one or more hardware processors, nearness among the plurality of CEP threads, wherein nearness between a first and a second CEP thread indicates how much interaction is expected to occur between the first and second CEP thread, the nearness between the first and second threads being measured by calculating an actual amount of data transmitted between the first and second threads during a set period;

organizing the plurality of CEP threads into a plurality of CEP thread groups, based on the determined nearness; and

assigning, using the one or more hardware processors, each of the plurality of CEP thread groups to a different processing node of a plurality of processing nodes, each processing node having one or more processor'"'"'s and a memory.

15. The non-transitory machine-readable storage medium of claim 14, wherein each processing node is a non-uniform memory access (NUMA) node.

16. The non-transitory machine-readable storage medium of claim 14, further comprising:

assigning each of the plurality of CEP threads a value representing processing capacity requested by a corresponding CEP thread; and

wherein the organizing is also based on the values for each of the plurality of CEP threads and information about processing capacity of each processing node.

17. The non-transitory machine-readable storage medium of claim 16, wherein the determining nearness includes creating a directed acyclic graph (DAG) with each of the plurality of CEP threads assigned a different node in the DAG and edges between nodes representing data dependencies among the threads;

and

wherein each edge in the DAG is assigned a nearness value.

18. The non-transitory machine-readable storage medium of claim 14, wherein the method is performed during startup time.

19. The non-transitory machine-readable storage medium of claim 14, wherein the method is performed during runtime.

20. The non-transitory machine-readable storage medium of claim 14, wherein the operations further comprise:

creating a thread graph for the plurality of CEP threads; and

wherein the determining nearness includes summing up edges in the thread graph between nodes in the thread graph representing the first and second CEP thread.

21. The non-transitory machine-readable storage medium of claim 14, wherein the nearness is determined at least partially based on one or more use hints, the one or more user hints indicating whether a particular thread is dynamic, semi-static, or static.