Metadata Catalog for Dynamic Query Parameter Identification
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Solution Overview
Problem
Current tools lack the ability to efficiently and visually search and analyze large sets of raw machine data across diverse data systems, making it challenging to derive insights from the vast amounts of data generated in IT environments.
Innovation Solution
A data intake and query system that utilizes a metadata catalog to facilitate the processing, indexing, and querying of machine data, allowing for flexible schema definition and late-binding schema application, enabling efficient storage and retrieval of raw data for analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If raw machine data is stored in massive quantities for later retrieval and analysis, then data flexibility and analysis capability are improved, but data management complexity and search difficulty increase
Solution Approach 1:
The patent introduces a metadata catalog as an intermediary layer between the raw data storage system and the query interface. The metadata catalog stores structured information about datasets including names, types, descriptions, and configuration parameters, enabling analysts to search and understand data without directly navigating the complexity of massive raw data storage systems.
2Productivity
If tools are designed to search and analyze large sets of raw machine data across diverse data systems, then data analysis capability is improved, but tool complexity and difficulty of operation increase
Solution Approach 1:
The metadata catalog serves as a mediator that simplifies the interaction between analysts and diverse data systems. By providing a unified interface that queries metadata across multiple data sources and translates user queries into appropriate data retrieval operations, the system maintains high analytical capability while improving ease of use.
Solution Approach 2:
The query system is designed to handle multiple types of queries across diverse data systems through a single unified interface. The metadata catalog stores information applicable to various data types and sources, allowing the same tool to efficiently search and analyze different kinds of machine data without requiring separate specialized tools for each data source.
3Speed
If pre-processing is applied to extract specified data items for efficient retrieval, then retrieval speed is improved, but data loss and flexibility are reduced
Solution Approach 1:
The metadata catalog acts as an intermediary that enables efficient retrieval without pre-extracting data items. By storing metadata that describes data locations, types, and characteristics, the system can quickly identify and retrieve relevant data from raw storage without needing to pre-process or extract specific items, thus maintaining both speed and data completeness.
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 parses the query and uses a metadata catalog to dynamically identify configuration parameters of datasets and/or rules associated with the query. The identified configuration parameters are communicated to a query processing component of the data intake and query system for use in executing the query.