Citation :

Velu Kaliappan, 2026. "Data System Languages: An Expressive Framework for Distributed Heterogeneous Data Analytics" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 4, Issue 1: 81-90.

Abstract :

This paper presents a new programming language designed for the evolving landscape of data analytics, where the increasing complexity of data pipelines demands robust support for varied data types and scalable operations. It introduces a novel language structure that facilitates data parallel processing across both data streams and data frames within a distributed computing environment. The paper details the language’s formal definition and its integration with modern compilation frameworks for efficient execution. By enabling flexible expression and deployment for diverse analytical tasks, this system offers an advanced paradigm for handling the challenges of large scale, multi-modal data analysis.

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Keywords :

Domain-Specific Language (DSL), Arc-Lang, Data Analytics, Intermediate Representation (IR), MLIR, Compiler Optimization, Rust Code Generation, Stream Processing, Tensor Computation, Graph Analytics, Distributed Systems, Type-Safe Programming, Dataflow Execution, IR Dialects, Runtime Systems.