SPLWare/esProc
EsProc
esProc 是一个分布式 ETL 框架和嵌入式数据计算引擎。它为 Java 虚拟机提供了一种结构化数据语言，专为关系查询、复杂数据计算和结构化数据分析而设计。
该系统具有自然语言数据查询界面，利用大语言模型将请求转换为针对结构化数据集的可执行查询。它采用具有简洁语法的领域特定查询语言来建立表关系并检索信息。
该平台涵盖跨不同关系型和 NoSQL 源的数据集成，并管理 ETL 工作流以在文件和数据库之间移动数据。其他功能包括结构化数据报告生成、用于分步执行可视化的实时网格界面，以及集成自定义外部共享库的能力。
Features
- ETL Workflows - Provides a distributed framework for extracting, transforming, and loading data across cluster servers and disparate sources.
- Cross-Source Data Integration - Enables joining and merging datasets from diverse external relational and NoSQL sources into a single result set.
- Hybrid Data Integration - Orchestrates data movement and transformation across disparate relational and NoSQL sources without a centralized warehouse.
- Embedded Analytics Engines - Provides a lightweight, embeddable database component for native query and analysis capabilities within applications.
- Large-Scale Data Computation - Provides a JVM-based environment for executing complex data analysis and computation graphs across distributed clusters.
- Query Domain Specific Languages - Employs a domain-specific query language with concise syntax to define table relationships and retrieve structured information.
- Embedded SQL Query Engines - Integrates a JVM-based engine that executes queries directly against connected data sources.
- JVM-Based Runtime Executions - Executes data computations and scripts within a JVM to ensure cross-platform compatibility and memory efficiency.
- Structured Data Languages - Implements a specialized structured data language for the JVM designed for complex relational queries and analysis.
- Core Engine Embedding - Implements an architectural pattern for integrating the core data engine into other software environments for localized processing.
- Distributed Cluster Coordination - Provides mechanisms for synchronizing state and scheduling across multiple compute nodes to handle large-scale processing.
- Natural Language Command Translation - Integrates large language models to translate natural language requests into executable data query commands.
- Natural Language Querying - Allows users to retrieve and analyze structured datasets using natural language queries powered by large language models.
- Natural Language Querying Interfaces - Includes an interface that translates natural language prompts into structured queries for data retrieval.
- Complex Data Structure Transformation - Performs complex data analysis and reshaping using set operations and relational queries.
- Execution Visualizers - Provides a real-time grid interface for step-by-step execution visualization to debug and verify data flows.
- Execution Visualizers - Ships a real-time grid interface to visualize and debug data computation steps.
