Dynamic Search Head Assignment for Tenant Data Caching
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Solution Overview
Problem
Current data intake and query systems face challenges in efficiently searching and analyzing large quantities of diverse, minimally processed machine data due to the lack of user-friendly tools for visually identifying data subsets of interest, particularly in big data ecosystems with diverse data types and formats.
Innovation Solution
A data intake and query system that utilizes a metadata catalog and late-binding schema to process and store machine data, allowing for flexible schema development and extraction of insights through field-searchable events, with components like search nodes and search heads facilitating efficient query execution and data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in minimally processed or unprocessed form (raw data), then flexibility and completeness of analysis are improved, but data volume and storage requirements increase significantly
Solution Approach 1:
The patent segments the data processing architecture into multiple search heads and search nodes that can independently process different portions of raw data. This segmentation allows the system to handle large volumes of unprocessed data by dividing the analysis workload across multiple components, maintaining flexibility while managing data volume through distributed processing.
Solution Approach 2:
The patent introduces a temporal dimension to data processing by implementing real-time search capabilities alongside historical data analysis. The system processes raw data as it arrives and stores it for future retrieval, adding the time dimension to handle both immediate analysis needs and long-term data retention, thereby managing data volume through time-based data lifecycle management.
2Productivity
If multiple search heads and search nodes are used to process queries in parallel, then query processing speed and productivity are improved, but system complexity increases
Solution Approach 1:
The patent introduces a coordinator component that acts as an intermediary between the user interface and the distributed search nodes. This intermediary manages the complexity of coordinating multiple search heads and nodes by centralizing query distribution, result aggregation, and resource allocation logic, thereby enabling parallel processing while masking system complexity from end users.
Solution Approach 2:
The patent implements dynamic allocation and scaling of search nodes based on workload demands. The system can dynamically add or remove search nodes from the processing pool, adjust resource allocation in real-time, and adapt the degree of parallelization according to query complexity and system capacity, thereby improving productivity while managing complexity through flexible, adaptive architecture.
3Speed
If pre-processing is applied to extract specified data items, then retrieval efficiency is improved, but data completeness and flexibility are reduced
Solution Approach 1:
The patent applies preliminary indexing and metadata extraction to raw data without discarding the original unprocessed content. The system performs preliminary actions by creating searchable indexes and metadata structures that enable efficient retrieval, while simultaneously preserving the complete raw data for flexible analysis, thus resolving the contradiction between retrieval speed and data flexibility.
Solution Approach 2:
The patent creates multiple copies of data in different formats and levels of processing. The system maintains copies of raw data, indexed data, and processed data simultaneously, allowing queries to access pre-processed copies for fast retrieval while preserving access to original raw data for flexible analysis, thereby resolving the speed-flexibility trade-off through multi-format data storage.
Data Source
AI summary
Systems and methods are disclosed for mapping search nodes to a search head in a data intake and query system based on a tenant identifier in order to execute a query received by the data intake and query system. The mapping may allow same or similar search nodes to be used to execute queries that are associated with a particular tenant identifier, in order to take advantage of caching and local data stored with those search nodes. In some cases, search nodes can be mapped based on the tenant identifier using a hashing algorithm, such as a consistent hashing algorithm.