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AssigneeHuawei Technologies Co., Ltd.
InventorsYunlong Shi, Mingzhen Xia, Cheng He
Estimating the term…
A stream computer system and a method for processing a data stream in a stream computing system are disclosed. In an embodiment, the method includes collecting data traffic information between each working node and other working nodes and processing speed information for each working node, determining an optimized parallelism degree for each working node according to the collected data traffic information and processing speed information and adjusting a parallelism degree of the working node according to the optimized parallelism degree of the working node.
A method for processing a data stream in a stream computing system, wherein the stream computing system comprises a control node and multiple working nodes, the method comprising:
A control node in a stream computing system, wherein the stream computing system comprises the control node and multiple working nodes, and wherein the control node comprises a processor, and a non-transitory memory coupled to the processor, the processor is configured to execute instructions stored in the memory so as to:
A stream computing system comprising:
Dependencies are inferred from the claim text.
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Wherein the services involve a main real-time session and one or more additional parallel real-time or time sensitive sessions, e.g. white board…:…
Allocation of resources, e.g. of the central processing unit [CPU]: techniques for rebalancing the load in a distributed system
Processing captured monitoring data, e.g. for logfile generation: for graphical visualisation of monitoring data
Miscellaneous aspects: allocation of resources per group of connections, e.g. per group of users
About 8 years 9 months of term left · ends 8 Aug 2035 (estimated)
The present invention relates to the field of computer technologies, and in particular, to a data processing method in a stream computing system, a control node, and a stream computing system.
Currently, data-intensive services have been widely applied, and typical data-intensive services include financial services, network monitoring, telecommunications data management, Web applications, and the like. In a data-intensive service, data is characterized by a large volume and a high speed, and is time varying. Therefore, it is not suitable to use a durable and stable relationship model to perform data modeling, but suitable to use a transient data stream model to perform data modeling, and therefore research on data stream computing emerges. Data stream computing is a pipeline-like data processing mode. Data stream computing comes from a concept that data value decreases as time elapses. Therefore, after an event triggers generation of data, the data needs to be processed as soon as possible. It is optimal that data is processed instantly as soon as the data is generated, that is, data processing is performed once instantly as soon as one event occurs, instead of buffering data for batch processing.
In a stream computing system, data stream computing is performed based on a streaming data processing model. As shown in FIG. 1, service data processing logic generally needs to be converted into a data processing mode shown in a directed acyclic graph (DAG; or referred to as a flow graph), an operator (Operator) in the graph bears a data processing operation, a data stream (stream) represents data transmission between Operators, and all Operators may be executed in a distributed mode.
To describe the technical solutions in the embodiments of the present invention or in the prior art more clearly, the following briefly introduces the accompanying drawings required for describing the embodiments or the prior art. Apparently, the accompanying drawings in the following description show merely some embodiments of the present invention, and a person of ordinary skill in the art may still derive other drawings from these accompanying drawings without creative efforts.
FIG. 1 is a schematic diagram of a DAG graph in the prior art;
FIG. 2 is a flowchart of a data processing method in a stream computing system according to an embodiment of the present invention;
To make the objectives, technical solutions, and advantages of the present invention clearer and more comprehensible, the following further describes the technical solutions provided in the present invention in detail with reference to the accompanying drawings and embodiments. Apparently, the described embodiments are merely some but not all of the embodiments of the present invention. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.
The following describes a main implementation principle, specific implementation manners, and corresponding achievable benefits of the technical solutions provided in the embodiments of the application with reference to the accompanying drawings.
As shown in FIG. 2, an embodiment of the present invention provides a data processing method in a stream computing system. The method provided in this embodiment of the present invention may be used in the stream computing system, where the stream computing system generally includes a control node and multiple working nodes (also referred to as operators, Operator), and the control node may send a corresponding control instruction to a subordinated working node, so that the working node invokes, according to the control instruction, an execution unit to process a data stream generated by a service.