Ephemeral Data Handling in Microservices - Technical Report

TL;DR

This paper introduces a novel integrated query framework for ephemeral, tree-shaped data in microservices, formalizing MQuery within Jolie to enable real-time data processing without external databases.

Contribution

It formalizes and implements a tree-oriented MQuery variant within Jolie, facilitating real-time ephemeral data handling in microservices.

Findings

Framework successfully processes heterogeneous tree data formats.

Evaluation demonstrates efficiency in eHealth use case.

Unified approach simplifies ephemeral data management.

Abstract

In modern application areas for software systems --- like eHealth, the Internet-of-Things, and Edge Computing --- data is encoded in heterogeneous, tree-shaped data-formats, it must be processed in real-time, and it must be ephemeral, i.e., not persist in the system. While it is preferable to use a query language to express complex data-handling logic, their typical execution engine, a database external from the main application, is unfit in scenarios of ephemeral data-handling. A better option is represented by integrated query frameworks, which benefit from existing development support tools (e.g., syntax and type checkers) and execute within the application memory. In this paper, we propose one such framework that, for the first time, targets tree-shaped, document-oriented queries. We formalise an instantiation of MQuery, a sound variant of the widely-used MongoDB query language, which we implemented in the Jolie language. Jolie programs are microservices, the building blocks of modern software systems. Moreover, since Jolie supports native tree data-structures and automatic management of heterogeneous data-encodings, we can provide a uniform way to use MQuery on any data-format supported by the language. We present a non-trivial use case from eHealth, use it to concretely evaluate our model, and to illustrate our formalism.