PID Control for Data Processing Pipeline Throughput Stability
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Solution Overview
Problem
Existing systems for controlling data processing pipelines, such as data publishers and databases, face challenges in consistently and accurately managing data flow and processing, especially when handling real-time and batch data, leading to inefficiencies and resource wastage due to inadequate scaling and uncertainty about data rates.
Innovation Solution
A computer-implemented method using PID control to monitor data processing errors in data publishers and databases, adjusting data flow rates and resource consumption to maintain efficient data processing by instructing controllers to manage data flow and storage rates, thereby preventing overload and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data flow rate is increased to improve productivity, then data processing throughput is improved, but system overload and errors increase
Solution Approach 1:
The patent implements a feedback control system using PID controllers that continuously monitor data processing errors and adjust data flow rates accordingly. The controller receives feedback about processing errors and dynamically modifies the publisher data flow rate to maintain optimal operation, preventing both overload and underutilization.
Solution Approach 2:
The system dynamically adjusts the data flow rate based on real-time processing conditions rather than using a fixed rate. The PID controller continuously modifies operational parameters to adapt to changing system states, enabling the system to handle varying workloads efficiently while maintaining reliability.
2Reliability
If data flow rate is decreased to prevent system overload, then processing reliability is improved, but productivity decreases
Solution Approach 1:
The feedback control mechanism monitors processing errors and adjusts data flow rates in real-time. When errors indicate approaching overload conditions, the controller reduces the flow rate to maintain stability. When processing capacity is available, the controller increases the flow rate to maximize throughput, thus dynamically balancing reliability and productivity.
Solution Approach 2:
The system changes the data flow rate parameter dynamically based on processing conditions. The PID controller adjusts this parameter to optimize the balance between throughput and stability, preventing the system from operating in either extreme of overload or underutilization.
3Productivity
If PID control is implemented to optimize data flow, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The PID controller serves multiple functions: it monitors processing errors, determines optimal data flow rates, and adjusts publisher operations. This multi-functional approach consolidates control logic into a single component, managing complexity while achieving comprehensive optimization of data processing efficiency.
Data Source
AI summary
Systems, apparatuses, methods, and computer program products are provided herein. For example, a method included herein includes receiving monitoring data representing operations of a data publisher, a data processing unit, and a database. In some embodiments, the method may include determining a first data processing error associated with the data publisher and the data processing unit based at least in part on the monitoring data. In some embodiments, the method may include determining a second data processing error associated with the data processing unit and the database. In some embodiments, the method may include causing a first controller to control the data publisher or the data processing unit. In some embodiments, the method may include causing a second controller to control the data processing unit or the database based at least in part on the second data processing error.