Apache Storm ui 容量指标 [英] Apache storm ui capacity metric

问题描述

容量"指标非常有用，它告诉您在过去 10 分钟内，bolt 执行元组所用的时间百分比.如果此值接近 1，则螺栓处于满负荷状态"并且是拓扑中的瓶颈.满负荷螺栓的解决方案是增加螺栓的平行度.

The "capacity" metric is very useful and tells you what % of the time in the last 10 minutes the bolt spent executing tuples. If this value is close to 1, then the bolt is "at capacity" and is a bottleneck in your topology. The solution to at-capacity bolts is to increase the parallelism of that bolt.

我不太明白% 的时间.因此，如果该值为 0.75 - 它的真正含义是什么?

I don't quite understand % of time. So if the value is 0.75 - what does it really mean?

推荐答案

这是 Bolt 忙与空闲的时间百分比.0.75 意味着 25% 的时间在等待处理新数据.

It's the percent of time that the bolt is busy vs idle. 0.75 would mean that 25% of the time is waiting for new data to be processed.

假设您每秒收到一个新的输入元组，但您的 bolt 需要 0.1 秒来处理它，bolt 将在 90% 的时间处于空闲状态，容量为 0.1.

Lets say you receive a new input tuple every second but your bolt takes 0.1 seconds to process it, the bolt will be idle 90% of the time and the capacity will be 0.1.

另一个示例:假设您实时接收更多可以处理的数据，并且您有两个螺栓，并且执行第一个螺栓的任务比第二个螺栓花费的时间更多，因此第一个螺栓是您的瓶颈.第一个螺栓的容量将在 1 左右，第二个螺栓的容量将低于 1.

Another example: Imagine you receive more data in real time that you can process and you have two bolts and the task that is doing the first bolt takes more time than the second so the first bolt is your bottleneck. The capacity of the first bolt will be around 1 and the capacity of the second will be below 1.

在上面的两个示例中，您可以通过查看此数字来确定您需要为每个螺栓设置的并行度(或处理能力).

In both examples above, then you can determine the parallelism (or processing power) that you need to set up for each bolt by looking at this number.

如果第一个螺栓容量为 1，第二个为 0.5，您可能希望为第一个螺栓设置两倍于第二个螺栓的执行器数量.同时(也是最重要的)，你必须增加执行器的数量，直到螺栓容量低于 1，这样你才能确定你的拓扑能够跟上并处理所有传入的数据实时.

If the first bolt capacity is 1 and the second is 0.5 you probably want to set up twice the number of executors to the first bolt than two the second. At the same time (and most importantly), you have to increase the number of executors until that bolt capacity is below 1, so you are sure that your topology is able to keep up and process all the data that is coming in real time.

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