I'm dealing with two CSV files for a Python task. The first CSV has 'string' and 'updated' columns, while the second CSV has a 'pattern' column. My goal is to efficiently find the latest matching string for each pattern from the first CSV. However, the first CSV is large with around 8 million rows, whereas the second has 50,000 rows.
Given this situation, what would be the most efficient approach in Python to solve this task?
Initially, I tried using pandas, but processing the large first CSV was time-consuming. Then, I attempted Dask, which improved performance, but I faced a challenge: Dask operates with chunks, making it difficult to get the latest matching string for each pattern.