} else {
                t.url = args[ai];
            }
        }

        final Thread[] threads = new Thread[t.numThreads];
        int ti;

        for (ti = 0; ti < t.numThreads; ti++) {
            threads[ti] = new Thread(t);
            logger.info(threads[ti].getName());
            threads[ti].start();
        }

        while (t.numComplete < t.numThreads) {
            long delay;

Framing rules make it impractical to implement http/2 correctly on a single blocking thread. The flow-control features introduce feedback between reads and writes, requiring writes to acknowledge reads and reads to throttle writes.

In OkHttp we expose a blocking API over a framed protocol. This document explains the code and policy that makes that work.

 *   <li>a {@linkplain ThreadFactoryBuilder#setNameFormat naming format}
 *   <li>a {@linkplain Thread#setPriority thread priority}
 *   <li>an {@linkplain Thread#setUncaughtExceptionHandler uncaught exception handler}
 *   <li>a {@linkplain ThreadFactory#newThread backing thread factory}
 * </ul>
 *
 * <p>If no backing thread factory is provided, a default backing thread factory is used as if by

    }

    @Test
    public void testThreadSafety() throws InterruptedException {
        // Test concurrent updates from multiple threads
        Thread[] threads = new Thread[10];

        for (int i = 0; i < threads.length; i++) {
            final int index = i;
            threads[i] = new Thread(() -> {
                for (int j = 0; j < 100; j++) {
                    String name = "file" + index + "_" + j + ".txt";

    void testConcurrentAccess() throws InterruptedException {
        // Test thread safety of getInstance
        LogStream.setInstance(testStream);

        final LogStream[] instances = new LogStream[10];
        Thread[] threads = new Thread[10];

        for (int i = 0; i < threads.length; i++) {
            final int index = i;
            threads[i] = new Thread(() -> {
                instances[index] = LogStream.getInstance();

    @Nonnull
    Optional<Boolean> alsoMakeDependents();

    /**
     * Returns the number of threads used for parallel builds.
     *
     * @return an {@link Optional} containing the number of threads (or "1C" for one thread per CPU core), or empty if not specified
     */
    @Nonnull
    Optional<String> threads();

    /**
     * Returns the id of the build strategy to use.
     *

            return b.toString();
        }).collect(Collectors.joining(",")));
        buf.append("},");
        final Threads threads = jvmStats.getThreads();
        buf.append("\"threads\":{");
        append(buf, "count", () -> threads.getCount()).append(',');
        append(buf, "peak", () -> threads.getPeakCount());
        buf.append("},");
        final Classes classes = jvmStats.getClasses();

    void testConcurrentLogging() throws InterruptedException {
        int threadCount = 10;
        int eventsPerThread = 100;
        Thread[] threads = new Thread[threadCount];

        for (int i = 0; i < threadCount; i++) {
            final int threadId = i;
            threads[i] = new Thread(() -> {
                for (int j = 0; j < eventsPerThread; j++) {

import org.opensearch.action.admin.cluster.node.hotthreads.NodesHotThreadsResponse;
import org.opensearch.common.unit.TimeValue;

/**
 * Monitor target for tracking hot threads in the OpenSearch cluster.
 * This class extends MonitorTarget to provide monitoring functionality for
 * hot threads, which helps identify performance bottlenecks and resource
 * usage issues in the search engine cluster.
 */
public class HotThreadMonitorTarget extends MonitorTarget {

        // Simulate concurrent failures
        Thread[] threads = new Thread[5];
        for (int i = 0; i < threads.length; i++) {
            threads[i] = new Thread(() -> failover.handleFailure(failedChannel, error));
            threads[i].start();
        }

        // Wait for all threads to complete
        for (Thread thread : threads) {
            thread.join(1000);
        }