Data Intake Query System External Source Integration
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Solution Overview
Problem
Current data intake and query systems face challenges in seamlessly searching and analyzing diverse data types across various data sources, as their capabilities are often isolated to internal data stores, limiting the ability to derive insights from external data systems and lacking scalability to handle large volumes of diverse data.
Innovation Solution
A data intake and query system that employs a search process master and query coordinators combined with a scalable network of distributed nodes to collect and process data from diverse data systems, enabling search and analytics operations across internal and external data sources, including big data ecosystems like MySQL, PostgreSQL, and cloud storage systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in internal data stores only, then search and analytics capabilities are contained within the system, but the ability to search and analyze diverse data from external sources is limited
Solution Approach 1:
The search process master and query coordinator are designed to handle multiple data source types (internal data stores, external databases, cloud storage) through a unified query processing architecture. The system can ingest data from diverse sources including MySQL, PostgreSQL, and cloud storage systems while maintaining consistent search and analytics capabilities across all sources.
Solution Approach 2:
The search process master acts as an intermediary between the user query and distributed data sources. It coordinates query execution across multiple data sources, manages the complexity of accessing diverse data types, and aggregates results into a unified response, thereby shielding users from data source heterogeneity.
2Quantity of substance
If the system processes large volumes of diverse data, then comprehensive insights can be derived, but processing time and system resources increase
Solution Approach 1:
The system divides data processing into segments by distributing query execution across multiple nodes in the network. Each node processes a portion of the data independently, and results are aggregated by the query coordinator. This segmentation enables parallel processing of large datasets, reducing overall processing time while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The system performs preliminary data ingestion and indexing of data from external sources into the search process master's data stores. This preliminary action prepares data in advance for rapid query processing, reducing the time required for subsequent search and analytics operations on large datasets.
3Adaptability or versatility
If the system integrates with big data open stack technologies, then scalability is improved, but system complexity and integration requirements increase
Solution Approach 1:
The search process master is designed with universal connectors and protocols that enable integration with major big data open stack technologies including MySQL, PostgreSQL, and cloud storage systems. The system uses standardized data formats and query languages to interact with diverse data sources, reducing the need for custom integration code for each technology.
Solution Approach 2:
The search process master serves as an intermediary layer between the query coordinator and big data open stack technologies. It abstracts the complexity of integrating with diverse data sources by providing a unified interface for data ingestion, storage, and retrieval, thereby simplifying integration requirements while maintaining scalability.
Data Source
AI summary
Systems, methods, and computer readable media are disclosed for generating and providing concurrent journey visualizations associated with different journey definitions. In computer-implemented embodiments, a data intake and query system, or a journey visualization computing tool, can be used to generate and provide concurrent representations corresponding with different journey definitions. In operation, a set of journey instances associated with a journey having a set of steps is obtained. Each step may be associated with at least one event that includes raw machine data produced by a component of an information technology environment. Upon obtaining different journey definitions specifying filters to apply to the set of journey instances, the data intake and query system can generate journey visualizations in accordance with the journey definitions. Thereafter, the journey visualizations corresponding with the journey definitions can be concurrently displayed by a computing device via a graphical user interface.