And also after the `response` is generated, before returning it.

For example, you could add a custom header `X-Process-Time` containing the time in seconds that it took to process the request and generate a response:

{* ../../docs_src/middleware/tutorial001_py39.py hl[10,12:13] *}

/// tip

        .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() {

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:

#### 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.

}

// respHandler
func (m *muxClient) handleOneWayStream(respHandler chan<- Response, respServer <-chan Response) {
	if debugPrint {
		start := time.Now()
		defer func() {
			fmt.Println("Mux", m.MuxID, "Request took", time.Since(start).Round(time.Millisecond))
		}()
	}
	defer func() {
		// addErrorNonBlockingClose will close the response channel
		// - maybe async, so we shouldn't do it here.
		if m.respErr.Load() == nil {

    //    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

	start := time.Now()
	defer func() {
		if debugPrint {
			fmt.Println("Mux", m.ID, "Handler took", time.Since(start).Round(time.Millisecond))
		}
		if r := recover(); r != nil {
			gridLogIf(ctx, fmt.Errorf("grid handler (%v) panic: %v", msg.Handler, r))
			err := RemoteErr(fmt.Sprintf("handler panic: %v", r))

        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(() -> {

			} 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 {

    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**