Search-time field extraction in data intake systems
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Solution Overview
Problem
Current data intake and query systems face challenges in efficiently searching and analyzing large sets of raw machine data due to the lack of user-friendly tools for visually identifying data subsets of interest, particularly in handling diverse and rapidly growing volumes of structured, semi-structured, and unstructured data.
Innovation Solution
A data intake and query system that utilizes a late-binding schema for field extraction, allowing extraction rules to be applied at search time, enabling flexible schema development and refinement, and incorporating a pipelined search language for efficient data processing and query execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is pre-processed and extracted at intake time, then data retrieval efficiency is improved, but data flexibility and analysis capability are reduced
Solution Approach 1:
The system performs preliminary indexing of raw data at intake time without full extraction, creating a searchable index structure that enables efficient retrieval while preserving the ability to extract different fields at search time based on analytical needs
Solution Approach 2:
The field extraction process is made dynamic by allowing extraction rules to be applied at search time rather than fixed at intake time, enabling the system to adapt to different analysis requirements while maintaining efficient data storage
2Adaptability or versatility
If all raw data is stored for later analysis, then data analysis flexibility is improved, but search and analysis complexity increases
Solution Approach 1:
The system segments data processing into two distinct phases: intake time for data ingestion and basic indexing, and search time for field extraction and analysis. This segmentation reduces complexity by handling different operations at appropriate times rather than simultaneously
Solution Approach 2:
The system introduces an intermediary indexing layer that stores raw data in a structured format without full extraction, serving as a mediator between raw data storage and final analysis, thereby reducing search complexity while preserving data flexibility
3Speed
If field extraction is performed at intake time, then data retrieval speed is improved, but schema flexibility is reduced
Solution Approach 1:
The system performs preliminary indexing at intake time to enable fast retrieval, but defers the actual field extraction action to search time when schema flexibility is needed, combining the benefits of both approaches
Solution Approach 2:
The system changes the timing parameter of field extraction from intake time to search time, allowing the extraction process to be adapted dynamically based on the specific search requirements and schema needs
Data Source
AI summary
An improved data intake and query system that can perform and display ingest-time and search-time field extraction, redaction, copy, and/or categorization is described herein. As described herein, ingest-time field extraction, redaction, copy, and/or categorization may refer to field or field value extraction, redaction, copy, and/or categorization that is performed by a log observer system of the data intake and query system on raw machine data as the raw machine data is ingested or received from a publisher. As described herein, search-time field extraction, redaction, copy, and/or categorization may refer to field or field value extraction, redaction, copy, and/or categorization that is performed by the log observer system and/or other components of the improved data intake and query system on historical raw machine data that has already been ingested and indexed by the improved data intake and query system.