Processing a text file that is over a billion lines long efficiently requires some optimization strategies. First, consider using buffered I/O, which minimizes disk access by reading data in chunks instead of line by line. This can significantly improve reading speed. Additionally, you can parallelize the processing by dividing the file into smaller chunks and processing them concurrently using multiple threads or processes. This way, you can take advantage of multi-core processors and perform operations in parallel, enhancing overall speed. Another approach is to use indexing or caching techniques to avoid repeatedly accessing the chromosome file. By creating an index or cache of the chromosome file, you can quickly retrieve the required sequences without scanning the entire file each time. Lastly, consider optimizing your algorithm for sequence retrieval, as this operation might be a bottleneck. Efficient data structures and algorithms, such as using a hash table or binary search tree, can speed up sequence retrieval. By employing these strategies, you can improve the processing speed of your bioinformatics project and analyze the entire database within your desired timeframe.

Thanks so much. From this and another tips I have been able to speed up my program by orders of magnitude!

The first step should be carefully converting the master text file into a database (e.g. MySql). Indeed, a database structure allows random access to its elements, allowing, also, parallel access. The database software itself performs some management optimization tricks.