Design Issues of JPQ: a Pattern-based Query Language for Document Databases

TL;DR

This paper discusses the design of JPQ, a pattern-based query language for document databases that enables expressive, declarative querying of hierarchical JSON-like data structures using tree-like patterns and logical relationships.

Contribution

It introduces JPQ, a novel pattern-based query language with a pattern composition mechanism and deductive features for complex document data retrieval.

Findings

JPQ effectively expresses complex document queries.

JPQ maintains logical relationships in hierarchical data.

JPQ demonstrates high expressiveness and declarativeness.

Abstract

Document databases are becoming popular, but how to present complex document query to obtain useful information from the document remains an important topic to study. In this paper, we describe the design issues of a pattern-based document database query language named JPQ. JPQ uses various expressive patterns to extract and construct document fragments following a JSON-like document data model. It adopts tree-like extraction patterns with a coherent pattern composition mechanism to extract data elements from hierarchically structured documents and maintain the logical relationships among the elements. Based on these relationships, JPQ deploys a deductive mechanism to declaratively specify the data transformation requests and considers also data filtering on hierarchical data structure. We use various examples to show the features of the language and to demonstrate its expressiveness and declarativeness in presenting complex document queries.