Abstract:

 With the rapid development of information technology, big data analysis has become increasingly important in several fields, and the performance of database optimizer algorithm directly affects the speed and quality of the analysis, so the purpose of this paper is to explore how to optimize the database optimizer algorithm to improve the efficiency and accuracy of big data analysis. The research methodology uses tools such as Python, PostgreSQL and cuBLAS to complete the optimization of the database optimizer algorithm, builds the optimization environment on a high-performance server, and verifies the feasibility of the optimization algorithm. The results show that using the above tools allows the optimization algorithm to show better performance in processing large-scale and high-dimensional datasets and maintains efficient operation under different data characteristics, proving its usefulness and effectiveness in big data analysis.

Key words:  big data analysis')">

 big data analysis, database optimizer algorithm, performance optimization strategy