Multi-field Search Query Expansion for Event Data Analysis
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Solution Overview
Problem
Existing data intake and query systems face challenges in efficiently searching and analyzing massive quantities of unstructured machine data, requiring cumbersome long query strings for global searches across multiple fields, which is inefficient and time-consuming.
Innovation Solution
The implementation of a data intake and query system that uses a flexible schema and late-binding schema to process and index machine data, allowing for field-searchable queries and the use of pipelined search languages to simplify the search process, enabling users to perform multi-field searches efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a data intake and query system performs search queries on event data to find events that satisfy search query criteria, then the system can retrieve relevant data from massive quantities of unstructured machine data, but performing additional global search queries on the result data set requires writing and inputting long query strings which is cumbersome and time-consuming
Solution Approach 1:
The system segments the search process into two distinct phases: (1) an initial search query that retrieves a result data set from event data, and (2) a subsequent global search query that operates specifically on the result data set. This segmentation allows the second search to be simplified since it only needs to search within the already-filtered results rather than the entire event data set, reducing query complexity and preparation time.
Solution Approach 2:
The system performs preliminary filtering by executing the first search query to generate a result data set before performing the global search. This preliminary action reduces the search space for the subsequent global query, allowing users to write shorter and simpler query strings since they are searching within a pre-filtered subset of data rather than the complete event data set.
2Adaptability or versatility
If the system writes and inputs long query strings to search across all fields of all events in the result data set, then comprehensive global search can be performed, but the process becomes highly inefficient and time-consuming
Solution Approach 1:
The search operation is divided into two stages: first searching event data with an initial query to produce a result data set, then performing global searches on that result data set. This segmentation enables the second search to achieve comprehensive coverage of relevant fields while operating on a smaller, pre-filtered data set, thereby improving efficiency without sacrificing search thoroughness.
Solution Approach 2:
Instead of requiring a single comprehensive query to search all fields of all events, the system performs a sequence of partial searches: first filtering events to create a result data set, then searching within that result. This partial action approach achieves the same comprehensive search goal but with simpler, shorter query strings at each stage, significantly improving productivity.
Data Source
AI summary
In accordance with various embodiments of the present disclosure, a data intake and query system (DIQS) performs a query on event data to return a result data set. A client device receives an input that includes one or more text strings and expands the received input into a multi-field search query, which is transmitted to the DIQS. The DIQS then parses the result data set by performing the multi-field search query on the result data set to return at least one event that includes one or more fields that have one or more values that correspond to the one or more text strings. The at least one event may then be caused to be displayed by the client device through a graphical user interface.