Automated Superset Job Flow Generation for Data Reproducibility
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Solution Overview
Problem
The challenge lies in efficiently managing and reusing large datasets across multiple job flows in distributed systems, where reproducibility and accountability are desired, and existing solutions lack mechanisms for effective organization and oversight, leading to inefficiencies in data utilization and collaboration.
Innovation Solution
An apparatus and method that generates a superset job flow by analyzing instance logs and job flow definitions to identify necessary tasks and data objects, creating a directed acyclic graph (DAG) that combines multiple job flows, enabling the reuse and oversight of data objects and task routines within a federated area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple separate job flows are executed to process large datasets, then data analysis tasks can be performed with reproducibility and accountability, but system complexity and execution overhead increase
Solution Approach 1:
The patent combines multiple separate job flows into a single unified job flow by automatically deriving a superset job flow definition that incorporates tasks from multiple source job flows. This merging reduces system complexity while maintaining the reproducibility and accountability benefits of structured job flow execution through centralized management of the consolidated workflow.
Solution Approach 2:
The automated derivation mechanism creates a universal superset job flow definition that can serve multiple purposes: it can be executed as a single unified workflow, broken down into individual job flows when needed, and used to generate instance logs for auditing. This multi-functionality allows the system to maintain reliability while reducing complexity through a single versatile job flow definition.
2Loss of information
If multiple distinct job flows are executed for data analysis, then specific tasks can be performed with detailed tracking, but execution time and resource consumption increase
Solution Approach 1:
The system performs preliminary action by automatically deriving the superset job flow definition before execution, analyzing and consolidating multiple source job flow definitions in advance. This pre-processing step organizes all necessary tasks and dependencies upfront, enabling more efficient single-execution workflows while maintaining detailed tracking information in the generated instance logs.
Solution Approach 2:
The patent creates a consolidated copy of task definitions from multiple source job flows into a single superset job flow definition. This copying and integration process preserves all necessary task details and tracking information while eliminating the need to execute multiple separate job flows, thereby reducing execution time without losing tracking detail.
3Adaptability or versatility
If job flow definitions and instance logs are stored in a federated area, then data reuse and collaboration are enhanced, but storage and retrieval complexity increase
Solution Approach 1:
The federated area serves as a universal storage repository that handles multiple functions: storing job flow definitions, storing instance logs, and enabling automated derivation of superset job flows. This multi-functional storage system enhances data reuse and collaboration while managing complexity through a unified access and management interface for all stored objects.
Solution Approach 2:
The federated area acts as an intermediary layer between multiple users and systems, providing a centralized repository that simplifies storage and retrieval operations. By mediating access to job flow definitions and instance logs, it enables data reuse and collaboration while abstracting away the underlying storage complexity from end users and applications.
4Productivity
If automated derivation of superset job flow is implemented, then the need for explicit execution of distinct flows is reduced, but processing overhead for analysis increases
Solution Approach 1:
The automated derivation of superset job flow definitions is performed as a preliminary action before workflow execution. By analyzing and consolidating multiple source job flow definitions upfront, the system reduces the need for repeated execution of distinct flows, improving overall productivity. The processing overhead is incurred once during derivation rather than repeatedly during execution.
Solution Approach 2:
The system creates a consolidated copy of task definitions and dependencies from multiple source job flows into a single superset job flow definition. This copying process, while requiring initial processing overhead, eliminates the need to repeatedly analyze and execute multiple separate flows, resulting in net productivity gains through reduced execution overhead and improved workflow efficiency.
Data Source
AI summary
An apparatus includes a processor to: receive a request to generate a superset job flow replacing multiple job flows including an output job flow and preceding job flows previously performed to generate an output data object; identify a first subset of mid-flow data object(s) generated by preceding job flow(s) as input(s) to the output job flow to generate the output data object; identify a second subset of the mid-flow data object(s) generated by preceding job flow(s) as input(s) to other preceding job flow(s) generating the first subset; in response to a lack of a second subset, derive the superset job flow and/or corresponding DAG to include at least one task of the output job flow and at least one task of each preceding job flow that generated the first subset; and transmit an indication of the generation of the superset job flow.