Unified Search Interface for Raw Machine Data Analysis
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Solution Overview
Problem
Current data intake and query systems lack efficient tools for quickly searching and analyzing large sets of raw machine data, particularly in IT environments, due to the complexity and diversity of data types and formats generated by various sources.
Innovation Solution
A data intake and query system architecture that includes containerized indexing and search nodes, enabling flexible schema management and late-binding schema application, allowing for real-time processing and querying of machine data across disparate sources, with features like bucket management, caching, and query acceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tools search data systems separately and collect results over a network, then data retrieval is possible, but the analysis process becomes piecemeal and inefficient
Solution Approach 1:
The patent combines multiple separate data systems into a unified search interface that allows analysts to search across all systems simultaneously. The system merges search capabilities across diverse data sources (databases, cloud services, machine data systems) into a single coherent tool, eliminating the need to separately search and aggregate results from multiple systems.
Solution Approach 2:
The search tool is designed with universal functionality to handle diverse data types and formats from various sources. It provides a unified interface that can search structured, semi-structured, and unstructured data across different systems, making it applicable to all data analysis needs rather than requiring system-specific tools.
2Adaptability or versatility
If massive quantities of raw data are stored for later retrieval, then data flexibility and analysis completeness are improved, but search and analysis complexity increases
Solution Approach 1:
The patent introduces an intermediary layer (the unified search interface and processing system) that mediates between the stored raw data and the analyst. This intermediary handles the complexity of searching across diverse data formats and systems, presenting a simplified interface to users while managing the underlying complexity of data retrieval and processing.
Solution Approach 2:
The system changes the parameters of data storage and retrieval by maintaining raw data in various formats while implementing a unified search mechanism that adapts to different data types. The search system dynamically adjusts its processing parameters based on the data being searched, handling structured, semi-structured, and unstructured data appropriately without requiring pre-processing.
3Speed
If pre-processing is applied to reduce data volume, then retrieval efficiency is improved, but data flexibility and ability to analyze all generated data is reduced
Solution Approach 1:
The system performs preliminary organization of data into manageable structures (buckets, indexes, metadata) without pre-processing or filtering the actual data content. This preliminary action prepares the data for efficient retrieval while preserving all original data for flexible analysis, avoiding the trade-off by separating organization from filtering.
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 a query identifying a set of data to be processed and a manner of processing the set of data. The data intake and query system uses a search node catalog to identify search nodes that are available to execute the query and uses a bucket catalog to identify buckets to be searched. The data intake and query system executes the query using the identified bucket and search nodes.