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Case Study 1: Implementing Data Query Language

Case Study 1: Implementing Data Query Language

Implement Data Query Language with ANTLR and JastAdd.

In this lesson, we explore the applicability of ANTLR and JastAdd in defining and implementing real-world grammar and complex language features. By delving into practical case studies, we illustrate how these tools can be employed to tackle sophisticated language design, and implementation challenges. This lesson aims to provide a deeper understanding of how ANTLR and JastAdd can be leveraged in advanced projects and real-world scenarios.

To demonstrate this, we will design an SQL-like query language for data analysis. This process will involve defining its syntax, enforcing semantic constraints, and implementing necessary processing steps. By the end of this lesson, learners will gain hands-on experience in using ANTLR for parsing and JastAdd for semantic analysis, ultimately seeing how these tools contribute to building structured, extensible, and formally defined languages.

SQL-like query language for data analysis

Consider designing a Data Query Language (DQL) tailored for querying and analyzing datasets efficiently. As a streamlined subset of SQL, DQL focuses on three fundamental operations. These include selection, which filters data based on specific conditions, projection which retrieves selected columns from a dataset, and aggregation, which performs computations such as COUNT, SUM, and AVG. By providing a simplified yet powerful query interface, DQL retains SQL’s expressiveness while eliminating unnecessary complexity, making it ideal for use cases that do not require full SQL support.

Example DQL query

The following example demonstrates a basic Data Query Language (DQL) query used to retrieve specific data from a dataset. This query selects the name and age columns from the employees table while applying a condition to filter only those employees whose age is greater than 30.

SELECT name, age FROM employees WHERE age > 30

DQL implementation

To implement DQL using ANTLR and JastAdd, we will follow a structured approach that ensures both syntactic correctness and semantic integrity. ANTLR helps define the grammar and generate a parser, while JastAdd enables modular ...