Prioritized Data Plan Execution via Partial Cost Estimation
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Solution Overview
Problem
The challenge lies in efficiently obtaining and processing large volumes of data while optimizing plan execution costs, as existing methods often result in higher-than-anticipated costs due to varying system resources, latency, and throughput, leading to delayed results in data visualization.
Innovation Solution
The system prioritizes data retrieval and processing plans based on estimated costs, utilizing partial execution to determine cost factors such as latency and throughput, allowing for the comparison and optimization of plans to minimize delays and costs, and adjusts execution accordingly to prioritize lower-cost paths and data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data is obtained and processed using optimized plans, then complete data visualization is achieved, but execution costs exceed expectations due to varying system resources, latency, and throughput
Solution Approach 1:
The system performs preliminary partial execution of plans to estimate their actual costs before full execution. By running a portion of each plan and measuring the resources consumed, latency experienced, and throughput achieved, the system can predict the total execution cost and prioritize plans accordingly, avoiding the waste of executing high-cost plans to completion.
Solution Approach 2:
The system dynamically adjusts plan execution priorities based on real-time cost estimates. Instead of using static optimized plans, the system continuously monitors actual execution costs and reorders the execution queue, suspending or canceling high-cost plans and prioritizing low-cost plans, thereby adapting to varying system resources, latency conditions, and throughput capabilities.
2Productivity
If plan execution is prioritized without partial execution, then execution speed is increased, but cost estimation accuracy deteriorates
Solution Approach 1:
The system performs partial execution of plans by running only a portion of each plan to gather cost data. This partial execution provides sufficient information to estimate total costs accurately without requiring complete execution, thus balancing the need for speed with the need for accurate cost measurement.
Solution Approach 2:
The system uses feedback from partial plan executions to continuously refine cost estimates. By measuring actual resources consumed, latency incurred, and throughput achieved during partial execution, the system adjusts its cost predictions and uses this feedback to make informed decisions about which plans to execute fully and which to suspend or cancel.
3Loss of time
If multiple plans are executed in parallel, then data retrieval time is reduced, but resource consumption and execution cost increase
Solution Approach 1:
Before executing multiple plans in parallel, the system performs preliminary partial execution to estimate the costs of each plan. This allows the system to identify and prioritize the most cost-effective plans, ensuring that parallel execution resources are allocated to plans that will provide the best return in terms of data retrieval speed versus resource consumption.
Solution Approach 2:
The system dynamically manages parallel plan execution by continuously monitoring resource consumption and cost estimates. Based on real-time feedback, the system adjusts the number and priority of plans executed in parallel, suspending or canceling high-cost plans and prioritizing low-cost plans, thereby optimizing the balance between data retrieval speed and resource consumption.
Data Source
AI summary
Systems and methods of prioritizing execution of plans for obtaining and/or processing data based on partial execution of the plans are presented herein. In certain implementations, one or more plans may be executed. Costs associated with individual ones of the plans may be estimated based on partial execution of respective ones of the plans. Based on a comparison between the estimated costs, the execution of at least one of plans may be prioritized over at least the execution of the other ones of the plans.