Automated Translation of Functional Big Data Queries to SQL

Explore a 14-minute video presentation from OOPSLA1 2023 conference that introduces a novel technique for automatically translating functional big data queries to SQL. Learn about the RDD2SQL tool developed by researchers from North Carolina State University and the University of Texas at Austin, which uses a column-wise decomposition approach within the counterexample-guided inductive synthesis paradigm. Discover how this method can improve the efficiency of queries in popular big data analytics frameworks like Apache Spark and Flink by converting functional API calls to optimized SQL queries. Gain insights into the tool's effectiveness in translating real-world RDD queries and the significant performance benefits it offers. Understand the challenges and advantages of functional APIs in big data analytics, and how this automated translation approach bridges the gap between convenience and efficiency in query processing.