BI Performance Analysis System for Live Bottleneck Detection
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Solution Overview
Problem
Existing business intelligence systems lack the ability to assess performance based on user-identified metrics, fail to identify and address performance bottlenecks, and require specific tools for analyzing logged data, often performing analysis in test environments rather than live or production scenarios.
Innovation Solution
A performance analysis system integrated with a search-analytical database that logs user interactions and generates performance data, allowing for the identification of bottlenecks and holistic characterization of performance, enabling users to analyze performance in live environments and re-execute queries to gather additional data points.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If business intelligence systems log and analyze performance data from live environments, then performance analysis capability is improved, but system complexity increases
Solution Approach 1:
The performance analysis system is nested within the existing business intelligence platform, reusing existing infrastructure components such as the data warehouse, query processing engine, and user interface framework. This allows the system to gain performance analysis capabilities without adding significant external complexity, as the analysis functions are integrated into the existing system architecture.
Solution Approach 2:
The system introduces a performance analysis module that acts as an intermediary between the existing business intelligence components and the performance metrics. This module captures query performance data, logs user interactions, and generates performance reports without fundamentally altering the core business intelligence system, thus improving measurement precision while controlling complexity growth.
2Measurement precision
If the system logs detailed data for each query including user, modular component, and action, then performance measurement precision is improved, but data processing complexity increases
Solution Approach 1:
The performance data is segmented into distinct categories corresponding to the modular components of the business intelligence system (data source module, data transformation module, data storage module, query module, etc.). Each logged entry includes the specific modular component identifier, allowing for granular performance analysis while organizing data in a structured manner that simplifies processing and analysis.
3Reliability
If the system analyzes performance in live or production scenarios rather than test environments, then reliability of performance assessment is improved, but risk of system impact increases
Solution Approach 1:
The system performs preliminary logging of query performance data and user interactions before conducting detailed analysis. Performance metrics are collected and stored in the data warehouse during normal system operation, and analysis is performed on this pre-collected data rather than during active query processing. This allows reliable performance assessment in live environments without impacting system performance or introducing risks during critical operations.
Data Source
AI summary
A performance analysis system that analyzes the performance of a business intelligence analytics application is provided. The performance analysis system logs data associated with one or more queries of a database within the database. The performance analysis system further generates performance data based on an analysis of the logged data, where the performance data includes data associated with one or more performance metrics of each query. The performance analysis system further generates one or more performance queries of the performance data, where a response to each performance query includes at least a portion of the one or more performance metrics stored within the database.