Containerized Query Nodes for Unified Raw Machine Data Search
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Solution Overview
Problem
Existing data analysis tools lack the ability to efficiently search and analyze large sets of raw machine data from diverse data systems, particularly in a visually understandable manner, leading to challenges in deriving insights from vast amounts of unprocessed data.
Innovation Solution
A data intake and query system utilizing a late-binding schema and flexible extraction rules to process and index machine data, enabling field-searchable events with a common information model across disparate data sources, allowing for real-time analysis and insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If tools search data systems separately and collect results over a network, then data can be retrieved from multiple sources, but the analysis process becomes piecemeal and inefficient
Solution Approach 1:
The patent combines multiple separate data system searches into a unified search interface. The system merges results from diverse data systems (databases, cloud services, file systems) into a single consolidated result set, allowing analysts to perform comprehensive searches across all systems simultaneously rather than separately collecting and analyzing results piecemeal.
Solution Approach 2:
The search tool is designed with universal functionality to handle multiple types of data systems through a common interface. It implements adaptable search capabilities that work across different data formats and system types (structured databases, unstructured files, cloud services) using a single unified tool rather than requiring separate specialized tools for each system.
2Adaptability or versatility
If massive quantities of raw data are stored for later retrieval, then greater flexibility and completeness of analysis is achieved, but the complexity of searching and analyzing the data increases
Solution Approach 1:
The patent introduces an intermediary layer between the stored raw data and the search interface. This intermediary includes automated parsing, filtering, and normalization components that process raw data into a standardized format suitable for searching. The intermediary handles the complexity of data heterogeneity and search optimization, shielding analysts from the underlying complexity while maintaining access to all raw data.
Solution Approach 2:
The system dynamically adjusts search parameters and data processing approaches based on the type and volume of data being searched. It automatically modifies search strategies, filtering criteria, and result presentation formats to optimize performance for different data characteristics, reducing the perceived complexity for users while handling massive diverse datasets.
3Productivity
If pre-processing extracts specified data items for efficient retrieval, then analysis speed improves, but the ability to analyze all generated data is reduced
Solution Approach 1:
The system performs preliminary indexing and metadata extraction on all raw data during storage, creating search-optimized structures without discarding any original data. This preliminary action prepares data for fast retrieval while maintaining the complete raw dataset, allowing both rapid search performance and comprehensive data analysis capability.
Solution Approach 2:
The patent creates indexed copies of raw data with extracted metadata and key characteristics, while preserving the original complete datasets. The indexed copies enable fast search and retrieval operations, while the original unprocessed data remains available for comprehensive analysis, eliminating the need to choose between speed and completeness.
Data Source
AI summary
Systems and methods are disclosed for processing and executing queries in a data intake and query system. The data intake and query system receives raw machine data at an indexing system, and stores at least a portion of the raw machine data in buckets using containerized indexing nodes instantiated in a containerized environment. The data intake and query system stores the buckets in a shared storage system.