Graphical Interface for Streaming Data Pipelines
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Solution Overview
Problem
Current data processing systems face challenges in efficiently analyzing and searching massive quantities of diverse and unstructured machine data from various sources, lacking intuitive tools for quick visualization and analysis of raw data subsets.
Innovation Solution
A data intake and query system with a graphical programming interface for designing data processing pipelines, enabling unified processing of both indexed and streaming data, and utilizing a late-binding schema for flexible data extraction and querying.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is pre-processed to extract specified data items for efficient retrieval, then data retrieval efficiency is improved, but data flexibility and analysis capability are worsened because most generated data is discarded
Solution Approach 1:
The system performs preliminary indexing of all raw data without discarding any information, creating a foundation that enables both efficient retrieval and flexible analysis. The indexing process prepares data for future queries while preserving the complete dataset for unforeseen analysis needs.
Solution Approach 2:
The data processing system is designed to handle multiple types of queries and analysis operations on the same raw data without requiring separate pre-processing pipelines. A single indexing structure supports both efficient retrieval of specific items and flexible exploration of diverse data subsets.
2Adaptability or versatility
If tools are provided to search and analyze large sets of raw machine data, then data analysis capability is improved, but tool complexity and difficulty of use are worsened
Solution Approach 1:
The system introduces an intermediary layer between the raw data and the user that handles the complexity of data processing automatically. This intermediary processing layer translates user-friendly queries into complex data operations without requiring users to understand the underlying complexity.
Solution Approach 2:
The system automatically performs data processing, indexing, and analysis operations without requiring manual configuration or complex tool setup. The processing system serves itself by autonomously managing the complexity of handling raw machine data while presenting simple interfaces to users.
3Adaptability or versatility
If all generated data is stored for later analysis, then data flexibility is improved, but storage requirements and system complexity are worsened
Solution Approach 1:
The system segments the storage and processing of raw data into manageable components, organizing data by source, time, or type while maintaining the ability to retrieve and analyze complete datasets. This segmentation reduces the apparent complexity of handling massive quantities of diverse data.
Data Source
AI summary
Systems and methods are disclosed for implementing a data processing workflow user interface for a streaming data processing system. The workflow is visually represented as a series of modules along with interconnections for the modules. Each module represents an operation on a streaming data object, such as a data transformation. The user interface enables selection of a workflow template based on a user-specified data source, and then allows the user to customize the workflow template by specifying additional operations to apply to data objects. The interface may show the user a preview of output data objects processed according to the customized workflow.