In this example, the *path operations* under the `router` will use the custom `TimedRoute` class, and will have an extra `X-Response-Time` header in the response with the time it took to generate the response:

        .addHeader("Retry-After", "1")
        .body("You took too long!")
        .onResponseEnd(ShutdownConnection)
        .build(),
    )
    val request = Request(server.url("/"))
    val response = client.newCall(request).execute()
    assertThat(response.body.string()).isEqualTo("You took too long!")
  }

  @Test
  fun requestBodyRetransmittedOnClientRequestTimeout() {

#### The time to answer helps the attackers { #the-time-to-answer-helps-the-attackers }

At that point, by noticing that the server took some microseconds longer to send the "Incorrect username or password" response, the attackers will know that they got _something_ right, some of the initial letters were right.

    //    queue, immediately followed by another thread taking the next element in the queue. That
    //    second thread can then dispatch to the subscriber it took before the first thread does.
    //
    // All this makes me really wonder if there's any value in queueing here at all. A dispatcher
    // that simply loops through the subscribers and dispatches the event to each would actually

			} else {
				took := time.Since(refreshStart).Seconds()
				if took > maxDurationSecondsForLog {
					// Log if we took a lot of time to load.
					logger.Info("IAM refresh took (duration: %.2fs)", took)
				}
			}

			// Run purge routines once in each hour.
			if refreshStart.Hour() != lastPurgeHour {

        long duration = endTime - startTime;

        // Then - should complete quickly (this is more of a performance indicator)
        assertTrue(duration < 1000, "Creating and using 10000 EmptyIterators should be fast (took " + duration + "ms)");
    }

    @Test
    @DisplayName("EmptyIterator should work correctly in nested iteration")
    void testNestedIteration() {
        // When & Then
        assertDoesNotThrow(() -> {

    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```
17/03/22 23:21:10 INFO DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 1.302805 s
Pi is roughly 3.1445191445191445
```

Job status can also be viewed in a browser by navigating to the YARN ResourceManager Web UI and clicking on job history server information.

### **4.2 WordCount**

				c.healBuckets(ctx, objAPI)   // heal buckets subsequently

				took := time.Since(refreshStart).Seconds()
				if took > maxRefreshDurationSecondsForLog {
					// Log if we took a lot of time.
					logger.Info("Site replication healing refresh took %.2fs", took)
				}

				// wait for 200 millisecond, if we are experience lot of I/O

 *  Upgrade: [Okio 3.9.0][okio_3_9_0].

 *  Upgrade: [Kotlin 1.9.23][kotlin_1_9_23].

 *  Upgrade: [Unicode® IDNA 15.1.0][idna_15_1_0]


## Version 5.0.0-alpha.12

_2023-12-17_

We took too long to cut this release and there's a lot of changes in it. We've been busy.

Although this release is labeled _alpha_, the only unstable thing in it is our new APIs. This

    // for 5.5 seconds happens about 2% of the time.
    boolean longWait = NANOSECONDS.toSeconds(thread.timeSpentBlocked) >= 5;
    // Count how long it actually took to return; we'll accept any number between the expected delay
    // and the approximate actual delay, to be robust to variance in thread scheduling.
    char overWaitNanosFirstDigit =