External Dataset Capability Compensation for Data Intake Systems
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Solution Overview
Problem
Current data intake and query systems face challenges in seamlessly searching and analyzing diverse data types from various data sources, as their capabilities are often limited to internal data stores and lack the ability to route data to different destinations, restricting the scope of search and analytics operations.
Innovation Solution
A data intake and query system that employs a search process master and query coordinators combined with a scalable network of distributed nodes to collect and process data from diverse data systems, enabling search and analytics operations across internal and external data sources, including enterprise systems, open source technologies, and cloud storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data systems store and pre-process data based on anticipated analysis needs, then data retrieval efficiency is improved, but data flexibility and completeness are reduced
Solution Approach 1:
The system performs preliminary data collection and storage without pre-processing or filtering, retaining all raw data in its original form. This allows the data to be ready for immediate retrieval while maintaining complete flexibility for any future analysis needs, resolving the contradiction between retrieval efficiency and data flexibility
Solution Approach 2:
The system dynamically adapts data processing operations based on actual query requirements rather than anticipating them in advance. Data is processed and analyzed on-demand according to specific user needs, allowing the system to optimize for both retrieval speed and data flexibility simultaneously
2Adaptability or versatility
If tools search data systems separately and collect results over a network, then search capability is provided, but analysis efficiency and user experience are reduced
Solution Approach 1:
The system merges multiple separate data system searches into a single unified search operation. The unified search interface allows users to query across multiple data systems simultaneously, with results aggregated and presented in one consolidated view, thereby maintaining comprehensive search capability while dramatically improving analysis efficiency by eliminating the need for separate searches and manual result compilation
3Adaptability or versatility
If a scalable network of distributed nodes is employed to process data from diverse data systems, then search and analytics capabilities are extended, but system complexity increases
Solution Approach 1:
The distributed nodes are designed with universal interfaces and standardized protocols that enable them to handle diverse data types and formats from multiple data systems through a common architecture. This multi-functionality allows the system to extend search and analytics capabilities across various data sources without proportionally increasing system complexity, as the same node structure can adapt to different data sources
Data Source
AI summary
Systems and methods are disclosed for processing queries against an external data source utilizing dynamically allocated partitions operating on one or more worker nodes. The external data source can include data that has not been processed by the system. To query the external data source, a query coordinator can generate a subquery for the external data source based on determined functionality of the data source. The subquery can identify data in the external data source for processing and a manner for processing the data. In addition, the query coordinator can dynamically allocate partitions operating on worker nodes to retrieve and intake results of the subquery. In some cases, number of partitions allocated can be based on a number of partitions supported by the external data source.