EPL: The Event Processing Language for Streaming Data
Samuele Langhi, Riccardo Tommasini, Angela Bonifati, Thomas Bernhardt · Information Systems · 2025
Stream Processing (SP) engines play a crucial role in realtime analysis within the Big Data landscape, handling infinite data streams to analyze massive, noisy, and heterogeneous information flows.While initially inheriting programming interfaces from Hadoop MapReduce, a recent trend involves adopting declarative languages for expressing analyses.The Event Processing Language (EPL) and its implementation Esper, a mature query language in streaming and event processing, have gained prominence. EPL, with SQL-like syntax, uniquely combines Complex Event Processing (CEP) and streaming analytics.However, it lacks formal semantics.This work addresses this gap by formalizing a core fragment of EPL, focusing on the aspects of Data Definition Language (DDL) and Data Manipulation Language (DML).The formalization resolves semantic ambiguities, identifies potentially harmful constructs, and specifies EPL's data and processing model.This effort addresses a major gap in the formalization of stream processing languages, aligning with recent initiatives from similar domains like graph query languages.