Distributed Search Head Architecture for Query Scalability
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Solution Overview
Problem
Existing data intake and query systems face scalability issues due to bottlenecks at the search head when processing large volumes of data across numerous nodes, as the capacity of the single node performing reduce operations is exceeded, leading to inefficiencies and potential failures in generating search results.
Innovation Solution
The implementation of intermediary nodes that pre-combine partial search results from peer indexers, offloading reduce operations from the search head and allowing it to operate below capacity, thereby minimizing bottlenecks and improving system scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single search head performs all reduce operations on partial search results from numerous peer indexers, then the system can generate final search results, but the search head capacity is exceeded and bottlenecks occur
Solution Approach 1:
The patent divides the single search head into multiple search heads that can independently perform reduce operations. Each search head processes a portion of the partial search results from peer indexers, segmenting the reduce operation workload across multiple nodes instead of concentrating it on a single node, thereby preventing capacity exhaustion and improving scalability.
Solution Approach 2:
The patent introduces an additional dimension to the architecture by adding multiple search heads at the same hierarchical level, transforming the single-point reduce operation into a distributed multi-point operation. This dimensional expansion allows the system to handle larger volumes of partial search results without overloading a single node.
2Measurement precision
If the search head processes all partial search results from many peer indexers, then complete search results are obtained, but processing time increases and efficiency decreases
Solution Approach 1:
The patent segments the processing of partial search results across multiple search heads, allowing parallel reduce operations to occur simultaneously. Each search head processes a subset of partial results independently, reducing the total processing time while maintaining complete search result coverage through the collective output of all search heads.
Solution Approach 2:
The patent enables continuous parallel processing by having multiple search heads simultaneously perform reduce operations on different portions of partial search results. This continuous parallel action eliminates the sequential bottleneck that would occur with a single search head, significantly reducing processing time while maintaining result completeness.
3Quantity of substance
If more peer indexers are added to handle larger data volumes, then data coverage increases, but the search head becomes overwhelmed and capacity is exceeded
Solution Approach 1:
The patent segments the reduce operation capacity across multiple search heads, allowing the system to linearly scale data coverage by adding peer indexers without overwhelming a single search head. Each additional search head provides additional reduce operation capacity, maintaining a balanced architecture that can handle increased data volumes proportionally.
Solution Approach 2:
The patent creates a universal architecture where multiple search heads can independently perform the same reduce operations that a single search head would perform. This multi-functionality allows any combination of search heads to handle the reduce operations, providing flexibility and scalability as data volume requirements increase.
Data Source
AI summary
The disclosed embodiments include a method performed by a data intake and query system. The method includes receiving a search query by a search head, defining a search process for applying the search query to indexers, delegating a first portion of the search process to indexers and a second portion of the search process to intermediary node(s) communicatively coupled to the search head and the indexers. The first portion can define a search scope for obtaining partial search results of the indexers and the second portion can define operations for combining the partial search results by the intermediary node(s) to produce a combination of the partial search results. The search head then receives the combination of the partial search results, and outputs final search results for the search query, where the final search results are based on the combination of the partial search results.