This research introduces an innovative translation system that converts complex structural aggregation queries from array databases into optimized MapReduce code, improving big data processing efficiency.

• Addresses critical performance challenges in the big data era for data management applications
• Leverages array database management systems that handle n-dimensional data structures
• Creates a translator system that bridges specialized database queries with distributed computing frameworks
• Enables higher performance for large-scale data processing tasks

This engineering advancement matters because it removes barriers between specialized database queries and scalable distributed computing frameworks, potentially accelerating scientific and business data analysis.

A Novel Approach to Translate Structural Aggregation Queries to MapReduce Code