During the interview for the Software Engineer position at PayPal, you may be asked to implement a function in Java that reads a large CSV file and returns the total amount aggregated by user for a given date range. This task requires efficient processing of the file as it contains millions of rows. Here's a step-by-step guide on how to approach this question:
import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.math.BigDecimal;
import java.time.LocalDate;
import java.time.format.DateTimeFormatter;
import java.util.HashMap;
import java.util.Map;
public Map aggregateTransactions(String filePath, LocalDate startDate, LocalDate endDate) throws IOException {
Map userAmountMap = new HashMap<>();
// code for reading and processing the CSV file goes here return userAmountMap;
}
try (BufferedReader br = new BufferedReader(new FileReader(filePath))) {
String line;
while ((line = br.readLine()) != null) {
// code for processing each row goes here }
}
String[] transactionValues = line.split(",");
String transactionId = transactionValues[0];
String userId = transactionValues[1];
BigDecimal amount = new BigDecimal(transactionValues[2]);
LocalDate transactionDate = LocalDate.parse(transactionValues[3], DateTimeFormatter.ofPattern("yyyy-MM-dd"));
if (transactionDate.isAfter(startDate) && transactionDate.isBefore(endDate)) {
// code for aggregating the amount for each user goes here}
BigDecimal userAmount = userAmountMap.get(userId);
if (userAmount == null) {
userAmountMap.put(userId, amount);
}
else {
userAmountMap.put(userId, userAmount.add(amount));
}
return userAmountMap;
By following these steps, you can efficiently process and aggregate a large CSV file in Java. It's important to optimize your code for large datasets to avoid performance issues. Good luck with your interview!