Incremental Statistics Calculation in Data Processing Pipelines
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Solution Overview
Problem
Current data processing systems, such as Apache Spark, calculate statistics only after the dataset has been fully processed, making them unavailable for optimizing operations within the pipeline, leading to inefficiencies and wasteful use of resources.
Innovation Solution
Calculating statistics as the dataset is built, allowing for immediate availability and use in optimizing downstream operations, including join operations, and providing controls for users to configure the pipeline based on these statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If statistics are calculated after the dataset is fully processed, then the complete dataset is available for analysis, but the statistics are unavailable for optimizing operations within the pipeline
Solution Approach 1:
The patent applies preliminary action by calculating statistics during the dataset building process rather than after completion. The system computes statistics incrementally as data is processed, making them available for optimizing downstream operations before the pipeline executes those operations. This resolves the contradiction by performing the measurement action (statistics calculation) in advance of when it is needed for optimization.
2Productivity
If statistics are calculated during dataset building, then real-time optimization is enabled, but additional computational resources are required
Solution Approach 1:
The patent merges the statistics calculation function with the existing data processing pipeline operations. Instead of running statistics calculation as a separate post-processing step, it is integrated into the dataset building process itself. This combining approach enables real-time optimization while minimizing additional computational resources by utilizing the same processing infrastructure already present in the pipeline.
3Measurement precision
If statistics are updated as each row is built, then real-time availability is achieved, but processing speed decreases
Solution Approach 1:
The patent implements continuity of useful action by performing statistics updates continuously as data rows are processed, without interruption to the main data building flow. The statistics calculation is done in parallel with data processing operations, maintaining continuous progress on both tasks simultaneously. This approach achieves real-time statistics availability while preserving overall processing speed through concurrent execution.
Data Source
AI summary
Systems and methods are provided that are useful for configuring data processing pipelines. During building of a dataset in a data processing pipeline, statistics can be calculated relating to the dataset.