How do you find a solution when you have to process requests with hundreds of millions of records?

When processing requests with hundreds of millions of records, it is important to optimize data handling and use approaches that minimize memory load and execution time:

• Pagination and lazy evaluation: process data in parts (batch processing) to avoid loading the entire dataset into memory.
• Using streams: in Java, you can use the Stream API for lazy data processing.
• Database query optimization: use indexes, filtering at the database level, aggregations to reduce the amount of data transferred.
• Parallel processing: use multithreading or frameworks for distributed processing (e.g., Apache Spark).
• Caching: if data is frequently repeated, use caching to speed up access.

Example of using Stream to process a large file line by line:

try (Stream<String> lines = Files.lines(Paths.get("largefile.txt"))) {
    lines.filter(line -> line.contains("someFilter"))
         .forEach(System.out::println);
}

This approach allows processing data without loading the entire file into memory.