Stream Operator Buffer Backlog Management via Tuple Selection
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Solution Overview
Problem
In stream computing applications, operators often face performance issues due to buffering of stale or unnecessary data tuples, which can lead to inefficient processing and increased workload, as the buffer size fluctuates based on workload and backpressure from downstream operators.
Innovation Solution
A method is introduced to monitor and optimize operator processing by examining the contents of operator buffers, identifying and removing or reordering tuples to eliminate unnecessary processing, using a buffer manager that selects tuples based on attributes and performs operations such as removal or reordering to alleviate backlogs and improve processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators buffer data tuples to handle variable workload and backpressure, then processing reliability is improved, but buffer size fluctuates causing inefficiency and increased workload
Solution Approach 1:
The buffer manager proactively identifies and removes stale or unnecessary tuples from the buffer before they accumulate and cause inefficiency. This preliminary action prevents buffer bloat and maintains optimal buffer size, resolving the contradiction between reliability (buffering) and productivity (efficiency).
Solution Approach 2:
The system extracts and removes specific problematic tuples (stale or unnecessary ones) from the buffer. By taking out only the harmful elements rather than clearing the entire buffer, the system maintains processing reliability while improving productivity by reducing unnecessary processing workload.
2Reliability
If operators process all data tuples in the buffer, then processing completeness is improved, but unnecessary processing increases workload
Solution Approach 1:
The buffer manager applies different quality treatment to different tuples in the buffer. Instead of treating all tuples uniformly, it identifies and processes only the necessary tuples (removing stale or unnecessary ones), thereby reducing overall processing workload while maintaining completeness for valid data.
Solution Approach 2:
The system discards stale or unnecessary tuples from the buffer, recovering processing resources that would otherwise be wasted on irrelevant data. This selective discarding maintains processing completeness for meaningful data while significantly reducing unnecessary processing workload.
3Quantity of substance
If buffer size increases to handle backlog, then data accumulation capability is improved, but processing time increases
Solution Approach 1:
The buffer manager performs preliminary removal of stale tuples to prevent buffer overflow and maintain optimal buffer size. This action allows the buffer to accumulate necessary data without excessive size, thereby maintaining data accumulation capability while preventing processing time increase.
Solution Approach 2:
The buffer size is dynamically managed through continuous monitoring and selective removal of tuples. The buffer adapts its effective size based on data characteristics and processing needs, maintaining optimal capacity for data accumulation while minimizing processing time through proactive management.
Data Source
AI summary
Method, system and computer program product for performing an operation, including providing a plurality of processing elements comprising one or more operators, the operators configured to process streaming data tuples, establishing an operator graph of multiple operators, the operator graph defining at least one execution path in which a first operator is configured to receive data tuples from at least one upstream operator and transmit data tuples to at least one downstream operator, providing each operator a buffer configured to hold data tuples requiring processing receiving a plurality of data tuples in a buffer associated with an operator, the data tuples comprising at least one attribute, determining a backlog exists in the first buffer, selecting at least one data tuple from the first buffer, examining an attribute of the selected data tuples to identify a candidate tuple, and performing a second operation on the candidate tuple.