Backoff.DecorrelatedJitterBackoffV2, 1秒启动，等待最长大约32秒，带有failFast

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英文:

Backoff.DecorrelatedJitterBackoffV2, 1 second start, max around 32 sec in waits, with failFast

问题

I'm using Polly.Contrib for HttpClient retries.

var delay = Backoff.DecorrelatedJitterBackoffV2(
    medianFirstRetryDelay: TimeSpan.FromSeconds(1),
    retryCount: 4,
    fastFirst: true);

If I want the maximum time waiting to be ~32 seconds median (could be much higher because of randomness in the jitter, which is why I say median). I carefully read the docs which use this for maximum median wait for this API: "between 0 and f * 2^(t+1)".

Here f=1 and t=4, which comes out to max=32. But the WaitAndRetry says that doesn't include the failFast 1st retry in the count? So if I want max wait to be ~32 sec with failFast then is retryCount 4 or 5?

Update

Environment

  • I'm in kubernetes using microservices, using HTTP.
  • There are some single-instance workloads that manage state. If hit OOM they could be down while restarting.
    • 12-30 sec if scheduled on node that doesn't have that container image to download it and restart
    • 5 sec restart if container image is ready on the k8s node

Goals by priority

  1. Retry the HTTP op on restarted workload as quickly as possible but without spamming 1 per second.
  2. I'd also like to use firstFast: true, which would be convenient for example SQL deadlock (UPDATE or DELETE on busy table).
  3. If possible use the same retry strategy all the time, including for both startup and normal calls. There are some workloads that have multiple instances (k8s replicas 3-8) that have to support stop/pause/start mid-day. Hence jitter, especially if 1st attempt result is a timeout during mid-day start.
  4. Keep it simple and understandable, so less experienced devs and non-C# devs can reason about the retry call timing.

I can tweak parameters to meet all the goals except the last one. There's just too much variation for me to reason about when retry might happen after a failure, and don't think I can explain this behavior to non-C# devs.

英文:

I'm using Polly.Contrib for HttpClient retries.

var delay = Backoff.DecorrelatedJitterBackoffV2(
    medianFirstRetryDelay: TimeSpan.FromSeconds(1),
    retryCount: 4,
    fastFirst: true);

If I want the maximum time waiting to be ~32 seconds median (could be much higher because of randomness in the jitter, which is why I say median). I carefully read the docs which use this for maximum median wait for this API: "between 0 and f * 2^(t+1)".

Here f=1 and t=4, which comes out to max=32. But the WaitAndRetry says that doesn't include the failFast 1st retry in the count? So if I want max wait to be ~32 sec with failFast then is retryCount 4 or 5?

Update

Environment

  • I'm in kubernetes using microservices, using HTTP.
  • There are some single-instance workloads that manage state. If hit OOM they could be down while restarting.
    • 12-30 sec if scheduled on node that doesn't have that container image to download it and restart
    • 5 sec restart if container image is ready on the k8s node

Goals by priority

  1. Retry the HTTP op on restarted workload as quickly as possible but without spamming 1 per second.
  2. I'd also like to use firstFast: true, which would be convenient for example SQL deadlock (UPDATE or DELETE on busy table).
  3. If possible use same retry strategy all the time, including for both startup and normal calls. There are some workloads that have multiple instances (k8s replicas 3-8) that have to support stop/pause/start mid-day. Hence jitter, esp if 1st attempt result is a timeout during mid-day start.
  4. Keep it simple and understandable and so less experienced devs and non-C# devs can reason about the retry call timing.

I can tweak parameters to meet all the goals except the last one. There's just too much variation for me to reason about when retry might happen after a failure, and don't think I can explain this behavior to non-C# devs.

答案1

得分: 2

以下是您要翻译的部分：

DecorrelatedJitterBackoffV2

这是一个专门的休眠持续时间提供者。根据提供的参数，它将生成一个休眠持续时间序列 IEnumerable<TimeSpan>。因此，它是可迭代的。

如果您在重试策略中使用此提供者，它将在失败尝试和新的重试尝试之间等待与此可迭代的下一个值一样长的时间。

  • 第1次尝试失败（原始操作）
  • 策略评估是否应该触发 >> 假设应该触发
  • 等待与提供者的第一项定义的一样长时间
  • 第2次尝试失败（第一次重试）
  • 策略评估是否应该触发 >> 假设应该触发
  • 等待与提供者的第二项定义的一样长时间
  • 等等。

时间约束

休眠持续时间提供者仅控制两次尝试之间的延迟。换句话说，它不会对给定尝试需要多长时间产生影响。

如果您有这样的策略链 Policy.WrapAsync(retryPolicy, timeoutPolicy)，则已经限制了各个尝试（包括原始操作）。因此，您可以计算最坏情况下可能发出多少次重试，每次尝试可能需要多长时间，以及两次尝试之间的延迟时间。

如果您有这样的策略链 Policy.WrapAsync(timeoutPolicy, retryPolicy)，则已经限制了用于重试的总时间。因此，这是一个全面的时间约束。有了这个，您只能说在最坏的情况下何时应该放弃重试。但是您不知道在此期间可能发出多少重试尝试，因为每次尝试都没有明确的上限。

您可以将这两种方法组合起来，创建这样的策略链：

Policy.WrapAsync(globalTimeoutPolicy, retryPolicy, perAttemptTimeoutPolicy);

在这里，您将限制每次尝试以及所有尝试作为一个整体的上限。

组合策略

如果您在内部策略中使用超时策略，并在外部策略中使用重试策略，那么您应该调整您的重试策略以处理超时情况。在Polly中，超时策略引发 TimeoutRejectedException 而不是 OperationCanceledException。

因此，您应该在您的重试策略定义中添加 .Or<TimeoutRejectedException>() 构建方法调用。

英文:

Quite frankly I don't understand your requirements in entirety but here are my thoughts.

DecorrelatedJitterBackoffV2

This is a specialized sleep duration provider. Depending on the provided parameters it will generate a sequence of sleep durations IEnumerable<TimeSpan>. So, it is iterable.

If you use this provider in your retry policy it will wait between the failed attempt and a new retry attempt as much as the next value from this iterable.

  • The 1st attempt fails (original action)
  • Policy evaluates whether it should trigger or not >> let's suppose it should
  • Sleeps as much as it was defined by the provider's first item
  • The 2nd attempt fails (first retry)
  • Policy evaluates whether it should trigger or not >> let's suppose it should
  • Sleeps as much as it was defined by the provider's second item
  • etc.

Time constraints

The sleep duration provider controls only the delays between two attempts. In other words it does not have any affect on how long a given attempt takes.

If you have a policy chain like this Policy.WrapAsync(retryPolicy, timeoutPolicy) then you have constrained the individual attempts (including the original action as well). So, with this in your hand you could calculate the worst case scenario: at most how many retries could be issued, how much time could each attempt take and what are the delays between two attempts.

If you would have a policy chain like this Policy.WrapAsync(timeoutPolicy, retryPolicy) then you have constrained the overall time which could be spent for retries. So, this is an overarching time constraint. With this in your hand all you can say is that in worst case when should the retry give up. But you don't know how many retry attempts could be issued during this period since you don't have an explicit upper bound on each attempt.

You can combine the two approaches and create a policy chain like this:

Policy.WrapAsync(globalTimeoutPolicy, retryPolicy, perAttemptTimeoutPolicy);

Here you would have a limit for each attempt and for all attempts as a whole as well.

Combining policies

If you have a timeout policy as an inner policy and a retry as an outer policy then you should alter your retry to trigger for timeouts as well. In case of Polly the timeout policy throws a TimeoutRejectedException not an OperationCanceledException.

So, you should add .Or<TimeoutRejectedException>() builder method call to your retry policy definition.

UPDATE #1

> which parameters control WAIT TIME?

The medianFirstRetryDelay is used to calculate the next values. You can consider it as a seed for the exponential backoff function.

You can't control the max generated delay via the parameters.
But with the following simply wrapper you can:

IEnumerable<TimeSpan> GetCappedSleepDurations(TimeSpan? maxDelay = null)
{
    maxDelay ??= TimeSpan.FromSeconds(32);
    var delays = Backoff.DecorrelatedJitterBackoffV2(
        medianFirstRetryDelay: TimeSpan.FromSeconds(1),
        retryCount: 10,
        fastFirst: false);

    foreach (var delay in delays)
    {
        yield return delay < maxDelay.Value ? delay : maxDelay.Value;
    }

}

Then if your print out the results then you should see something like this:

00:00:00.7942099
00:00:01.2404539
00:00:02.0858948
00:00:01.8598678
00:00:12.2435673
00:00:08.1000294
00:00:32
00:00:32
00:00:32
00:00:32

答案2

得分: 1

I wrote a .NET Fiddle to answer this.

我写了一个.NET Fiddle来回答这个问题。

https://dotnetfiddle.net/QgUqq0

我明白你的意思，@PeterCsala。我以为我可以通过改变参数来控制等待时间的基本边界（文档中似乎隐含了这一点）。但抖动比我想象的要随机得多。我没有意识到每次等待的变化范围如此之大，当总等待时间为count=4或count=5时，也会有很大的变化。中位数也比我预期的要低。

And take this example output from the .NET Fiddle:

并且看一下来自.NET Fiddle的示例输出：

...
    00:00:00    00:00:02.4274782    00:00:01.1342445    00:00:05.9134879
    sum: 9.48 sec

注意2.4秒后的1.1秒等待。我从“指数回退”基本算法中不会预期到这种情况。这并不罕见。

I don't think I can explain this behavior to my other teammates (mostly Java and Python developers). So I think I'm going to have to use something simpler.

我认为我无法向我的其他团队成员（大多数是Java和Python开发人员）解释这种行为。所以我认为我需要使用更简单的方法。

Fiddle Ouput

以下是Fiddle的完整输出：

    00:00:00    00:00:01.3908135    00:00:03.6539260    00:00:05.8674163
    sum: 10.91 sec
    00:00:00    00:00:02.8356851    00:00:02.0988871    00:00:05.5788317
    sum: 10.51 sec
    00:00:00    00:00:02.2710896    00:00:01.6223447    00:00:07.2301703
    sum: 11.12 sec
    00:00:00    00:00:01.8503867    00:00:02.3001164    00:00:05.9391929
    sum: 10.09 sec
    00:00:00    00:00:01.7118342    00:00:01.1271053    00:00:08.2654298
    sum: 11.10 sec
    00:00:00    00:00:01.5934536    00:00:01.4503908    00:00:06.0499969
    sum: 9.09 sec
    00:00:00    00:00:01.8295553    00:00:02.3008588    00:00:05.7575813
    sum: 9.89 sec
    00:00:00    00:00:01.6955469    00:00:02.2361896    00:00:03.1572746
    sum: 7.09 sec
    00:00:00    00:00:01.6458597    00:00:02.5933294    00:00:05.4516284
    sum: 9.69 sec
    00:00:00    00:00:02.6751631    00:00:00.3368498    00:00:06.5234695
    sum: 9.54 sec
    00:00:00    00:00:02.7957035    00:00:01.6330546    00:00:06.2968850
    sum: 10.73 sec
    00:00:00    00:00:02.4284071    00:00:03.0204295    00:00:01.5322586
    sum: 6.98 sec
    00:00:00    00:00:02.4912384    00:00:00.6106680    00:00:07.2869721
    sum: 10.39 sec
    00:00:00    00:00:01.5209607    00:00:04.0020657    00:00:04.1196119
    sum: 9.64 sec
    00:00:00    00:00:02.5200905    00:00:00.5708792    00:00:3.3635606
    sum: 6.45 sec
    00:00:00    00:00:01.9854414    00:00:03.0925564    00:00:1.6569407
    sum: 6.73 sec
    00:00:00    00:00:01.4412447    00:00:02.8806764    00:00:05.7825008
    sum: 10.10 sec
    00:00:00    00:00:02.0367938    00:00:02.2873604    00:00:04.3724692
    sum: 8.70 sec
    00:00:00    00:00:01.5629809    00:00:01.4608352    00:00:04.3596487
    sum: 7.38 sec
    00:00:00    00:00:01.9355692    00:00:02.2350188    00:00:04.3516659
    sum: 8.52 sec
1 sec, retryCount: 4, firstFast: False
    00:00:01.3290191    00:00:01.2202047    00:00:02.5260844    00:00:04.5466469
    sum: 9.62 sec
    00:00:00.7939010    00:00:00.7185783    00:00:03.2866291    00:00:04.4188223

<details>
<summary>英文:</summary>

I wrote a .NET Fiddle to answer this.  

https://dotnetfiddle.net/QgUqq0

I see what you mean @PeterCsala.  I thought I could control basic boundaries of the wait time just by varying the parameters (which seems to be implied by the docs).  But the jitter is way more random than I thought.  I didn&#39;t realize each wait could vary so widely, when summed the total wait for count=4 or count=5 also varies widely.  The median is also way lower than I expected.

And take this example output from the .NET Fiddle:

1 sec, retryCount: 4, firstFast: True
...
00:00:00 00:00:02.4274782 00:00:01.1342445 00:00:05.9134879
sum: 9.48 sec


Notice 1.1 sec wait AFTER a 2.4 sec wait.  I&#39;d never expect that from an &quot;exponential backoff&quot; base algo.  It&#39;s not rare. 

I don&#39;t think I can explain this behavior to my other teammates (mostly Java and Python developers).  So I think I&#39;m going to have to use something simpler.

## Fiddle Ouput

Here&#39;s the entire output of the Fiddle:

1 sec, retryCount: 4, firstFast: True
00:00:00 00:00:01.3908135 00:00:03.6539260 00:00:05.8674163
sum: 10.91 sec
00:00:00 00:00:02.8356851 00:00:02.0988871 00:00:05.5788317
sum: 10.51 sec
00:00:00 00:00:02.2710896 00:00:01.6223447 00:00:07.2301703
sum: 11.12 sec
00:00:00 00:00:01.8503867 00:00:02.3001164 00:00:05.9391929
sum: 10.09 sec
00:00:00 00:00:01.7118342 00:00:01.1271053 00:00:08.2654298
sum: 11.10 sec
00:00:00 00:00:01.5934536 00:00:01.4503908 00:00:06.0499969
sum: 9.09 sec
00:00:00 00:00:01.8295553 00:00:02.3008588 00:00:05.7575813
sum: 9.89 sec
00:00:00 00:00:01.6955469 00:00:02.2361896 00:00:03.1572746
sum: 7.09 sec
00:00:00 00:00:01.6458597 00:00:02.5933294 00:00:05.4516284
sum: 9.69 sec
00:00:00 00:00:02.6751631 00:00:00.3368498 00:00:06.5234695
sum: 9.54 sec
00:00:00 00:00:02.7957035 00:00:01.6330546 00:00:06.2968850
sum: 10.73 sec
00:00:00 00:00:02.4284071 00:00:03.0204295 00:00:01.5322586
sum: 6.98 sec
00:00:00 00:00:02.4912384 00:00:00.6106680 00:00:07.2869721
sum: 10.39 sec
00:00:00 00:00:01.5209607 00:00:04.0020657 00:00:04.1196119
sum: 9.64 sec
00:00:00 00:00:02.5200905 00:00:00.5708792 00:00:03.3635606
sum: 6.45 sec
00:00:00 00:00:01.9854414 00:00:03.0925564 00:00:01.6569407
sum: 6.73 sec
00:00:00 00:00:01.4412447 00:00:02.8806764 00:00:05.7825008
sum: 10.10 sec
00:00:00 00:00:02.0367938 00:00:02.2873604 00:00:04.3724692
sum: 8.70 sec
00:00:00 00:00:01.5629809 00:00:01.4608352 00:00:04.3596487
sum: 7.38 sec
00:00:00 00:00:01.9355692 00:00:02.2350188 00:00:04.3516659
sum: 8.52 sec
1 sec, retryCount: 4, firstFast: False
00:00:01.3290191 00:00:01.2202047 00:00:02.5260844 00:00:04.5466469
sum: 9.62 sec
00:00:00.7939010 00:00:00.7185783 00:00:03.2866291 00:00:04.4188223
sum: 9.22 sec
00:00:00.8904751 00:00:01.5267582 00:00:01.9186966 00:00:02.7913326
sum: 7.13 sec
00:00:00.6996185 00:00:00.7980595 00:00:01.8574831 00:00:03.6783710
sum: 7.03 sec
00:00:01.0187006 00:00:00.3737117 00:00:01.9765276 00:00:07.2216291
sum: 10.59 sec
00:00:01.3125672 00:00:01.3634863 00:00:01.8514689 00:00:02.7068033
sum: 7.23 sec
00:00:00.2745151 00:00:01.4576401 00:00:02.2336140 00:00:02.8430108
sum: 6.81 sec
00:00:01.1477933 00:00:00.6611546 00:00:03.8388333 00:00:00.3550863
sum: 6.00 sec
00:00:00.4087674 00:00:02.1939583 00:00:02.0896311 00:00:03.6630476
sum: 8.36 sec
00:00:01.3315603 00:00:01.3381451 00:00:00.2394113 00:00:04.5502384
sum: 7.46 sec
00:00:00.8031900 00:00:01.2612702 00:00:02.8399373 00:00:01.6098031
sum: 6.51 sec
00:00:01.1330562 00:00:01.1283540 00:00:00.9933361 00:00:02.4510240
sum: 5.71 sec
00:00:00.8316597 00:00:01.4024509 00:00:01.3783882 00:00:04.6346268
sum: 8.25 sec
00:00:00.7928881 00:00:01.5069425 00:00:01.1867454 00:00:03.5611036
sum: 7.05 sec
00:00:01.0969670 00:00:00.3476740 00:00:01.6399054 00:00:02.6186090
sum: 5.70 sec
00:00:00.3568919 00:00:01.2218998 00:00:03.3102970 00:00:01.5471265
sum: 6.44 sec
00:00:00.3974019 00:00:01.0342039 00:00:01.4164161 00:00:04.8298397
sum: 7.68 sec
00:00:00.9928894 00:00:01.1151883 00:00:01.7575383 00:00:05.1898116
sum: 9.06 sec
00:00:00.5711161 00:00:01.4577355 00:00:01.0355913 00:00:07.8069874
sum: 10.87 sec
00:00:00.3197731 00:00:01.7880796 00:00:00.9016027 00:00:06.9888528
sum: 10.00 sec
0.5 sec, retryCount: 5, firstFast: True
00:00:00 00:00:01.3546792 00:00:00.7053145 00:00:03.1648237 00:00:02.5794683
sum: 7.80 sec
00:00:00 00:00:00.7510212 00:00:01.4794709 00:00:02.8552752 00:00:03.2562177
sum: 8.34 sec
00:00:00 00:00:01.0308662 00:00:00.4891457 00:00:02.1505252 00:00:06.7936745
sum: 10.46 sec
00:00:00 00:00:01.0453633 00:00:00.8946597 00:00:01.7640227 00:00:04.8035002
sum: 8.51 sec
00:00:00 00:00:00.8090960 00:00:00.8605115 00:00:01.2240451 00:00:04.4458000
sum: 7.34 sec
00:00:00 00:00:01.2711564 00:00:01.2777960 00:00:02.5999912 00:00:04.8633200
sum: 10.01 sec
00:00:00 00:00:01.3006120 00:00:00.3349617 00:00:03.7801364 00:00:05.2703497
sum: 10.69 sec
00:00:00 00:00:01.1173007 00:00:01.3774040 00:00:00.8674170 00:00:05.6837357
sum: 9.05 sec
00:00:00 00:00:01.0098212 00:00:00.6186374 00:00:02.1325980 00:00:02.6069504
sum: 6.37 sec
00:00:00 00:00:00.9025802 00:00:01.5986111 00:00:03.1227179 00:00:05.1528147
sum: 10.78 sec
00:00:00 00:00:01.3149453 00:00:00.6077659 00:00:01.6087266 00:00:04.1025526
sum: 7.63 sec
00:00:00 00:00:00.7264336 00:00:01.9088567 00:00:00.8443737 00:00:04.4497130
sum: 7.93 sec
00:00:00 00:00:01.1333575 00:00:01.2017326 00:00:01.0382133 00:00:08.0170088
sum: 11.39 sec
00:00:00 00:00:00.8767042 00:00:00.9866298 00:00:01.1425718 00:00:05.9847881
sum: 8.99 sec
00:00:00 00:00:00.8028736 00:00:01.1827370 00:00:02.9544043 00:00:06.3254855
sum: 11.27 sec
00:00:00 00:00:00.7629045 00:00:01.6695153 00:00:01.5461169 00:00:03.3028042
sum: 7.28 sec
00:00:00 00:00:00.9148938 00:00:01.1600169 00:00:02.5117271 00:00:01.3261893
sum: 5.91 sec
00:00:00 00:00:01.1267806 00:00:00.4564534 00:00:02.4212050 00:00:06.3470234
sum: 10.35 sec
00:00:00 00:00:01.3391868 00:00:01.0126013 00:00:00.5598949 00:00:06.9540418
sum: 9.87 sec
00:00:00 00:00:01.0319109 00:00:01.6532412 00:00:00.8366237 00:00:05.0481157
sum: 8.57 sec
1 sec, retryCount: 5, firstFast: True
00:00:00 00:00:01.7036852 00:00:01.2349855 00:00:03.1197186 00:00:16.0773452
sum: 22.14 sec
00:00:00 00:00:02.2658393 00:00:02.9162426 00:00:05.9138160 00:00:09.9773757
sum: 21.07 sec
00:00:00 00:00:01.9868814 00:00:02.0973613 00:00:01.9061254 00:00:05.9060386
sum: 11.90 sec
00:00:00 00:00:02.0072594 00:00:00.8320461 00:00:03.4227425 00:00:08.6058840
sum: 14.87 sec
00:00:00 00:00:01.4876995 00:00:01.6473985 00:00:03.8461699 00:00:09.9558171
sum: 16.94 sec
00:00:00 00:00:01.5546186 00:00:03.2393016 00:00:03.5368912 00:00:09.9090074
sum: 18.24 sec
00:00:00 00:00:02.6238426 00:00:01.6294628 00:00:06.0053214 00:00:03.7444907
sum: 14.00 sec
00:00:00 00:00:02.5793887 00:00:01.6679957 00:00:03.5116129 00:00:10.1809312
sum: 17.94 sec
00:00:00 00:00:01.3904824 00:00:02.4303553 00:00:06.7797002 00:00:02.9103902
sum: 13.51 sec
00:00:00 00:00:01.5879946 00:00:04.0853268 00:00:00.6255776 00:00:05.6349109
sum: 11.93 sec
00:00:00 00:00:01.4367477 00:00:03.8219711 00:00:02.6701373 00:00:09.3499156
sum: 17.28 sec
00:00:00 00:00:01.7639718 00:00:03.2156965 00:00:06.3168010 00:00:04.0324835
sum: 15.33 sec
00:00:00 00:00:01.5818707 00:00:03.9788198 00:00:05.0944585 00:00:10.7327818
sum: 21.39 sec
00:00:00 00:00:01.7912938 00:00:01.5854307 00:00:04.2299682 00:00:11.6892054
sum: 19.30 sec
00:00:00 00:00:02.0104886 00:00:00.8440592 00:00:05.2010443 00:00:13.9254070
sum: 21.98 sec
00:00:00 00:00:02.6279233 00:00:00.3518791 00:00:06.6170555 00:00:12.1033067
sum: 21.70 sec
00:00:00 00:00:02.1354632 00:00:01.2299710 00:00:05.2079696 00:00:08.4223971
sum: 17.00 sec
00:00:00 00:00:01.4818039 00:00:02.6026511 00:00:03.2391221 00:00:04.3425045
sum: 11.67 sec
00:00:00 00:00:01.4059338 00:00:04.1479147 00:00:04.2587746 00:00:12.9392626
sum: 22.75 sec
00:00:00 00:00:01.9507035 00:00:02.1151440 00:00:04.6839676 00:00:06.0393732
sum: 14.79 sec
1 sec, retryCount: 5, firstFast: False
00:00:00.6788230 00:00:01.4203410 00:00:02.6245586 00:00:01.7675321 00:00:05.2430371
sum: 11.73 sec
00:00:00.6529607 00:00:00.8373318 00:00:01.8539233 00:00:02.6559658 00:00:09.7934878
sum: 15.79 sec
00:00:01.0441502 00:00:00.4420462 00:00:03.0931698 00:00:03.9559396 00:00:11.7269578
sum: 20.26 sec
00:00:00.7728833 00:00:01.8642782 00:00:00.3419784 00:00:06.8331030 00:00:12.1200427
sum: 21.93 sec
00:00:00.5639535 00:00:01.5233071 00:00:01.4933406 00:00:06.4421055 00:00:04.4632977
sum: 14.49 sec
00:00:01.1370886 00:00:00.2474113 00:00:02.6039481 00:00:05.7760278 00:00:05.6636975
sum: 15.43 sec
00:00:00.6823440 00:00:01.7238784 00:00:01.1997150 00:00:05.8404974 00:00:02.8699631
sum: 12.32 sec
00:00:00.7725670 00:00:01.6544065 00:00:02.8142650 00:00:04.2002013 00:00:11.5602015
sum: 21.00 sec
00:00:00.7588586 00:00:00.9165350 00:00:02.1185922 00:00:02.1696501 00:00:11.3773388
sum: 17.34 sec
00:00:00.8974586 00:00:01.4088610 00:00:03.2732610 00:00:02.8008394 00:00:14.0565266
sum: 22.44 sec
00:00:01.2319287 00:00:00.5067809 00:00:02.4601368 00:00:06.0496388 00:00:04.1287814
sum: 14.38 sec
00:00:00.9695386 00:00:00.8180148 00:00:02.0015145 00:00:02.8972007 00:00:07.5788910
sum: 14.27 sec
00:00:00.9019472 00:00:00.8590886 00:00:01.4123911 00:00:07.3444693 00:00:01.3780976
sum: 11.90 sec
00:00:01.3009539 00:00:00.5818398 00:00:03.4664505 00:00:02.0787111 00:00:14.7543293
sum: 22.18 sec
00:00:00.4767782 00:00:01.4488689 00:00:01.1506591 00:00:07.1873676 00:00:02.1024607
sum: 12.37 sec
00:00:01.0843076 00:00:01.2420571 00:00:01.1056183 00:00:03.9690401 00:00:08.3664444
sum: 15.77 sec
00:00:01.2792085 00:00:00.4144544 00:00:01.8363079 00:00:03.9080785 00:00:06.1009469
sum: 13.54 sec
00:00:00.4607123 00:00:01.0653234 00:00:02.4233058 00:00:02.5853980 00:00:06.3878357
sum: 12.92 sec
00:00:00.9477224 00:00:00.8579657 00:00:03.8231531 00:00:04.7891651 00:00:05.8468680
sum: 16.26 sec
00:00:00.4714534 00:00:01.8518566 00:00:02.5178993 00:00:06.5791304 00:00:01.0214230
sum: 12.44 sec

--- SUMMARY ---------------------
1 sec, retryCount: 4, firstFast: True median wait: 9.23
1 sec, retryCount: 4, firstFast: False median wait: 7.84
0.5 sec, retryCount: 5, firstFast: True median wait: 8.93
1 sec, retryCount: 5, firstFast: True median wait: 17.29
1 sec, retryCount: 5, firstFast: False median wait: 15.94

Last Run: 7:21:14 am
Compile: 0.015s
Execute: 0.08s


</details>

huangapple
  • 本文由 发表于 2023年2月7日 04:15:41
  • 转载请务必保留本文链接：https://go.coder-hub.com/75366134.html
  • c#
  • dotnet-httpclient
  • exponential-backoff
  • polly
  • retry-logic
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