Distributed Job Progress Visualization via Intermediary Monitoring
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Solution Overview
Problem
Existing systems lack effective visualization tools to monitor and analyze the progress of distributed computational jobs across multiple execution points, making it difficult for developers to identify and address performance issues in real-time.
Innovation Solution
A processing gathering module collects and stores processing information from multiple vertices of a computational job at various execution instances, and a user interface module presents this information graphically, allowing developers to replay, pause, and navigate through the job execution, with visual emphasis on performance deviations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed computational jobs are divided into multiple vertices and processed across multiple network nodes, then processing efficiency and parallelization are improved, but monitoring and analyzing job progress becomes more difficult
Solution Approach 1:
The patent introduces an intermediary visualization system that collects processing information from multiple vertices across the distributed network and presents it through a unified graphical interface. This intermediary layer bridges the gap between the complex distributed processing operations and the user's need for simple monitoring, allowing developers to track job progress without directly interacting with the complexity of individual vertex operations.
Solution Approach 2:
The patent creates a visual copy or representation of the actual computational job progress through graphical displays. Instead of requiring users to directly observe and analyze raw processing data from multiple nodes, the system generates a simplified visual model that replicates the essential progress information, making it easier to monitor and analyze distributed job execution.
2Measurement precision
If processing information is collected at multiple instances in time, then performance analysis capability is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex task of performance monitoring into manageable components by collecting processing information at discrete time instances rather than continuously. This segmentation allows the system to capture performance data at key moments without the overhead of constant monitoring, reducing system complexity while maintaining adequate measurement precision for performance analysis.
Solution Approach 2:
The patent applies partial action by collecting processing information at selected time instances rather than continuously monitoring all aspects of job execution. This approach provides sufficient performance analysis capability by capturing data at critical moments without the excessive complexity and resource consumption that would result from comprehensive continuous monitoring.
3Measurement precision
If visualization tools provide detailed information about job execution, then performance issue identification is improved, but ease of operation deteriorates
Solution Approach 1:
The patent applies local quality by providing detailed visualization information specifically at locations or points where performance issues are detected, rather than uniformly detailed information throughout the entire interface. This allows the system to maintain ease of operation for general monitoring while providing enhanced detailed information locally where needed for performance issue identification.
Solution Approach 2:
The patent uses partial action by providing detailed performance information only when and where it is necessary for identifying performance issues, rather than displaying all possible data continuously. This maintains ease of operation by keeping the default interface simple while enabling detailed analysis on-demand when performance problems need to be investigated.
Data Source
AI summary
The visualization of progress of a distributed computational job at multiple points of execution. After a computational job is compiled into multiple vertices, and then those multiple vertices are scheduled on multiple processing nodes in a distributed environment, a processing gathering module gathers processing information regarding processing of multiple vertices of a computational job, and at multiple instances in time in the execution of the computational job. A user interface module graphically presents a representation of an execution structure representing multiple nodes of the computational job, and dependencies between the multiple nodes, where the nodes may be a single vertex or a group of vertices (such as a stage).