### Concurrency and Burgers { #concurrency-and-burgers }

This idea of **asynchronous** code described above is also sometimes called **"concurrency"**. It is different from **"parallelism"**.

**Concurrency** and **parallelism** both relate to "different things happening more or less at the same time".

But the details between *concurrency* and *parallelism* are quite different.

  // methods is identical, save for method being invoked.

  /** Invokes {@code latch.}{@link CountDownLatch#await() await()} uninterruptibly. */
  @J2ktIncompatible
  @GwtIncompatible // concurrency
  public static void awaitUninterruptibly(CountDownLatch latch) {
    boolean interrupted = false;
    try {
      while (true) {
        try {
          latch.await();
          return;

  }

  /**
   * Guides the allowed concurrency among update operations. Used as a hint for internal sizing. The
   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to

    FakeTicker ticker = new FakeTicker();
    assertThrows(
        IllegalArgumentException.class, () -> ticker.setAutoIncrementStep(-1, NANOSECONDS));
  }

  @GwtIncompatible // concurrency

  public void testConcurrentAdvance() throws Exception {
    FakeTicker ticker = new FakeTicker();

    int numberOfThreads = 64;
    runConcurrentTest(
        numberOfThreads,

  }

  /**
   * Guides the allowed concurrency among update operations. Used as a hint for internal sizing. The
   * table is internally partitioned to try to permit the indicated number of concurrent updates
   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to

    FakeTicker ticker = new FakeTicker();
    assertThrows(
        IllegalArgumentException.class, () -> ticker.setAutoIncrementStep(-1, NANOSECONDS));
  }

  @GwtIncompatible // concurrency

  public void testConcurrentAdvance() throws Exception {
    FakeTicker ticker = new FakeTicker();

    int numberOfThreads = 64;
    runConcurrentTest(
        numberOfThreads,

			Region:    region,
		})
		if err != nil {
			return res, err
		}
	}

	var mu sync.Mutex
	var uploadTimes madmin.TimeDurations
	wg.Add(opts.concurrency)
	for i := 0; i < opts.concurrency; i++ {
		go func(i int) {
			defer wg.Done()
			for {
				t := time.Now()
				reader := newRandomReader(opts.objectSize)

 * represents the task. This maximizes concurrency by having each unique key mapped to a unique
 * lock, but also maximizes memory footprint. On the other extreme, one could use a single lock for
 * all tasks, which minimizes memory footprint but also minimizes concurrency. Instead of choosing
 * either of these extremes, {@code Striped} allows the user to trade between required concurrency

            // Verify it works by testing a known mapping
            assertEquals("application/pdf", map.getMimeType("pdf"));
        }
    }

    @Nested
    @DisplayName("Performance and concurrency")
    class PerformanceTests {

        @Test
        @DisplayName("Should handle multiple lookups efficiently")
        void testMultipleLookups() throws IOException {

Guava is a set of core Java libraries from Google that includes new collection
types (such as multimap and multiset), immutable collections, a graph library,
and utilities for concurrency, I/O, hashing, primitives, strings, and more! It
is widely used on most Java projects within Google, and widely used by many
other companies as well.



Guava comes in two flavors: