在汇总到dataDog上的数字之前的过滤值“ query_value”可视化

发布于 2025-01-22 16:58:29 字数 1642 浏览 2 评论 0原文

我在Datadog中有一个计数指标,该指标具有正数和负数。当使用“时间剧”可视化仅显示正计数时,我只需应用clamp_min(query1,0),它可以正常工作。

本质上,当我尝试做同样的事情时,JSON看起来像“时间”

{
    "viz": "timeseries",
    "requests": [
        {
            "style": {
                "palette": "dog_classic",
                "type": "solid",
                "width": "normal"
            },
            "type": "line",
            "formulas": [
                {
                    "formula": "clamp_min(query1, 0)"
                }
            ],
            "response_format": "timeseries",
            "queries": [
                {
                    "query": "sum:my_counting_metric.as_count()",
                    "data_source": "metrics",
                    "name": "query1"
                }
            ]
        }
    ]
}

,并汇总了我在“ query_value”上过滤的所有这些正数,即我找不到一种方法任何类似的事物,因为它将所有计数总结到一个数字之前,然后才能将过滤器应用于上面的clamp_min。理想情况下,如果可能的话,我想在下面做类似的事情。

{
    "viz": "query_value",
    "requests": [
        {
            "response_format": "scalar",
            "formulas": [
                {
                    "formula": "query1"
                }
            ],
            "queries": [
                {
                    "query": "sum:clamp_min(my_counting_metric.as_count(), 0)",
                    "data_source": "metrics",
                    "name": "query1",
                    "aggregator": "avg"
                }
            ]
        }
    ],
    "precision": 2,
    "autoscale": true
}

有什么办法做到这一点吗?我感到非常困惑,非常感谢任何帮助!

I have a counting metric in DataDog, that has positive and negative counts. When using a "timeseries" visualization to show only the positive counts, I simply just apply a clamp_min(query1, 0), and it works.

Essentially, the JSON looks like below for the "timeseries"

{
    "viz": "timeseries",
    "requests": [
        {
            "style": {
                "palette": "dog_classic",
                "type": "solid",
                "width": "normal"
            },
            "type": "line",
            "formulas": [
                {
                    "formula": "clamp_min(query1, 0)"
                }
            ],
            "response_format": "timeseries",
            "queries": [
                {
                    "query": "sum:my_counting_metric.as_count()",
                    "data_source": "metrics",
                    "name": "query1"
                }
            ]
        }
    ]
}

When I try to do this same thing, and aggregate all these positive numbers that I've filtered for on a "query_value" viz, I can't find a single way to do anything similar because it sums all the counts to a number before making it possible to apply filters like clamp_min above. Ideally, I would like to do something like below if possible.

{
    "viz": "query_value",
    "requests": [
        {
            "response_format": "scalar",
            "formulas": [
                {
                    "formula": "query1"
                }
            ],
            "queries": [
                {
                    "query": "sum:clamp_min(my_counting_metric.as_count(), 0)",
                    "data_source": "metrics",
                    "name": "query1",
                    "aggregator": "avg"
                }
            ]
        }
    ],
    "precision": 2,
    "autoscale": true
}

Is there any way to do this? I'm feeling pretty stuck and would greatly appreciate any help! ????????

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孤芳又自赏 2025-01-29 16:58:29

在这个问题上,我能够与Datadog联系。

他们基本上告诉我我的帖子中提到的这种行为是可以预期的,因为“ query_value”正在运行一个称为点减少的过程。这就是为什么clamp_min函数没有效果的原因。简而言之,在执行“ query_value”初始聚合函数之前,没有办法过滤/映射。

I was able to get in contact with DataDog on this question.

They basically told me this behavior mentioned in my post is expected because the "query_value" viz runs a procedure called point reduction. This is why the clamp_min function had no effect. To put it short, there's not a way to filter/map before the execution of the initial aggregating function on a "query_value" viz.

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