How to Effectively Utilize MDC with Parallel Streams in Java and Logback

Question

How can I use Mapped Diagnostic Context (MDC) effectively with parallel streams in Java when logging with Logback?

// Sample code snippet for using MDC with parallel streams
import org.slf4j.MDC;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;

public class MDCExample {
    public static void main(String[] args) {
        List<Integer> numbers = IntStream.range(1, 10)
                                          .boxed()
                                          .collect(Collectors.toList());
        // Using parallel stream
        numbers.parallelStream().forEach(number -> {
            MDC.put("requestId", String.valueOf(number)); // Setting MDC value
            System.out.println("Logging number: " + number);
            // Log messages using Logback framework
            // (Assuming a logger is defined and configured)
            MDC.clear(); // Clear MDC after logging
        });
    }
}

Answer

Using Mapped Diagnostic Context (MDC) with parallel streams in Java can be tricky due to the way parallel streams handle threads. Ensuring thread safety and correct logging is crucial to avoid context leakage between different threads.

// Setting and clearing MDC values correctly in parallel execution
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.slf4j.MDC;

private static final Logger logger = LoggerFactory.getLogger(MDCExample.class);

public static void main(String[] args) {
    List<Integer> numbers = IntStream.range(1, 10)
                                      .boxed()
                                      .collect(Collectors.toList());
    // Using parallel stream safely with MDC
    numbers.parallelStream().forEach(number -> {
        try {
            MDC.put("requestId", String.valueOf(number));
            logger.info("Processing number: {}", number);
        } finally {
            MDC.clear(); // Ensure to clear after processing
        }
    });
}

Causes

MDC is thread-local, meaning each thread has its own context which may not persist when using parallel processing.
Without proper management, MDC values may not correspond to the correct log entries due to thread switching.

Solutions

Always set and clear MDC values within the scope of the parallel processing to prevent context leakage.
Utilize the appropriate logging framework (like Logback) that supports MDC properly and ensure that logging setup is done prior to invoking parallel streams.

Common Mistakes

Mistake: Failing to clear MDC after logging, which can lead to incorrect data being logged in subsequent log messages.

Solution: Always ensure to clear the MDC using MDC.clear() after logging in each thread.

Mistake: Setting MDC values outside the parallel stream, risking the loss of context when tasks switch threads.

Solution: Set MDC values immediately before the logging occurs within the parallel stream.

Helpers

Java parallel stream
MDC logging in Java
Logback MDC usage
Java logging best practices
Thread-safe logging with MDC