Data Intake Query System Task Assignment
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Solution Overview
Problem
Current data intake and query systems face challenges in seamlessly searching and analyzing large sets of diverse data from various data sources, including external systems, due to limited scope and unidirectional processing flows, which restricts the ability to derive comprehensive insights from combined data types.
Innovation Solution
A data intake and query system is developed with a search process master and query coordinators, coupled with a scalable network of distributed nodes, enabling the system to execute big data analytics across diverse data sources, extend search and analytics capabilities beyond internal data stores, and process data from external systems like MySQL, NoSQL databases, and cloud storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is pre-processed and stored in traditional data systems, then retrieval efficiency is improved, but data flexibility and analysis scope are reduced
Solution Approach 1:
The patent segments data into different storage locations (hot data in traditional systems, cold data in object storage) and processes queries in multiple stages. First, hot data is retrieved quickly for immediate analysis, then cold data is fetched from object storage to supplement the analysis, achieving both fast retrieval and comprehensive analysis capability
Solution Approach 2:
The patent adds a new dimension to the data architecture by introducing object storage as a separate layer beyond traditional data systems. This creates a multi-dimensional data access model where data can be retrieved from different storage layers depending on accessibility requirements, enabling both fast access to recent data and comprehensive access to historical data
2Adaptability or versatility
If all raw data is stored for later analysis, then data flexibility is improved, but storage cost and data management complexity increase
Solution Approach 1:
The patent applies local quality by storing different types of data in different locations based on their access characteristics. Frequently accessed recent data is stored in traditional systems with fast retrieval, while less frequently accessed historical data is stored in object storage. This creates a quality-gradient storage system where each location optimizes for its specific access pattern
Solution Approach 2:
The patent changes the storage parameter from uniform high-performance storage to differentiated storage based on data age and access frequency. By transitioning cold data to object storage, the system optimizes storage capacity utilization while maintaining data accessibility, effectively managing the quantity of stored data according to actual needs
3Device complexity
If search is limited to internal data stores, then system simplicity is maintained, but search scope and insight capability are reduced
Solution Approach 1:
The patent makes the search system universal by enabling it to query multiple data sources (traditional data systems and object storage) through a unified interface. The enhanced search functionality automatically determines which data sources to query based on the search parameters, providing comprehensive insight capability while maintaining ease of use through a single search command
Data Source
AI summary
Systems and methods are described for assigning a processing task from one component of a data intake and query system to a different component of the data intake and query system. As part of processing a query, the system can determine that a particular processing task is to be executed by a particular component of the data intake and query system. Based on the characteristics of the component that is to execute the processing task, the system can assign the task or a supplemental task to one or more other components of the data intake and query system.