go - Prometheus Type Collector-如何使用我自己的数据来提供 map

免责声明:我是Golang的新手，以前没有做过任何其他语言的编程工作。
我仍然希望有人能指出我正确的方向。

目标是:
按照Prometheus Golang模块(https://godoc.org/github.com/prometheus/client_golang/prometheus#Collector)下的“示例”部分及其提到的部分“//只是示例伪数据”。当然要使用我自己的真实数据。

我的数据来自RabbitMQ端点，格式为JSON。我解析了JSON，然后可以使用func main()范围内的goroutine所需的正确key:value来创建自己的 map 。

假设我的 map 如下所示:
[
“device1”:754，
“device2”:765，
]

对于代码，让我们遵循原始示例。

package main

import (
    "log"
    "net/http"
    "fmt"

    "github.com/prometheus/client_golang/prometheus"
    "github.com/prometheus/client_golang/prometheus/promhttp"
)

type ClusterManager struct {
    Zone string
    // Contains many more fields not listed in this example.
}

func (c *ClusterManager) ReallyExpensiveAssessmentOfTheSystemState() (
    oomCountByHost map[string]int, ramUsageByHost map[string]float64,
) {
        // Just example fake data.
        oomCountByHost = map[string]int{
            "foo.example.org": 42,
            "bar.example.org": 2001,
        }
        ramUsageByHost = map[string]float64{
            "foo.example.org": 6.023e23,
            "bar.example.org": 3.14,
        }
        return
}

type ClusterManagerCollector struct {
    ClusterManager *ClusterManager
}

var (
    oomCountDesc = prometheus.NewDesc(
        "clustermanager_oom_crashes_total",
        "Number of OOM crashes.",
        []string{"host"}, nil,
    )
    ramUsageDesc = prometheus.NewDesc(
        "clustermanager_ram_usage_bytes",
        "RAM usage as reported to the cluster manager.",
        []string{"host"}, nil,
    )
)

func (cc ClusterManagerCollector) Describe(ch chan<- *prometheus.Desc) {
    prometheus.DescribeByCollect(cc, ch)
}

func (cc ClusterManagerCollector) Collect(ch chan<- prometheus.Metric) {
    oomCountByHost, ramUsageByHost := cc.ClusterManager.ReallyExpensiveAssessmentOfTheSystemState()
    for host, oomCount := range oomCountByHost {
        ch <- prometheus.MustNewConstMetric(
            oomCountDesc,
            prometheus.CounterValue,
            float64(oomCount),
            host,
        )
    }
    for host, ramUsage := range ramUsageByHost {
        ch <- prometheus.MustNewConstMetric(
            ramUsageDesc,
            prometheus.GaugeValue,
            ramUsage,
            host,
        )
    }
}

func NewClusterManager(zone string, reg prometheus.Registerer) *ClusterManager {
    c := &ClusterManager{
        Zone: zone,
    }
    cc := ClusterManagerCollector{ClusterManager: c}
    prometheus.WrapRegistererWith(prometheus.Labels{"zone": zone}, reg).MustRegister(cc)
    return c
}

func main() {
    conn, err := amqp.Dial("amqp://guest:guest@localhost:5672/")
    failOnError(err, "Failed to connect to RabbitMQ")
    defer conn.Close()

    ch, err := conn.Channel()
    failOnError(err, "Failed to open a channel")
    defer ch.Close()

    q, err := ch.QueueDeclare("hello", false, false, false, false, nil)
    failOnError(err, "Failed to declare a queue")

    msgs, err := ch.Consume(q.Name, "", true, false, false, false, nil)
    failOnError(err, "Failed to register a consumer")

    forever := make(chan bool)

    go func() {
        for d := range msgs {
            var streams []byte
            streams = d.Body

            var metrics sStreamingMetrics
            err := json.Unmarshal(streams, &metrics)
            if err != nil {
                fmt.Println(err)
            }

            var category string
            category = metrics.Resource.Category

            if category == "server" {
               myMap := make(map[string]float64)
               MyMap [metrics.Resource.ResourceDataList[0].ResourceId] = metrics.Resource.ResourceDataList[0].MetricSampleList[0].ValueArray[0]
             }
    }()

    reg := prometheus.NewPedanticRegistry()

    NewClusterManager("zone", reg)

    reg.MustRegister(
        prometheus.NewProcessCollector(prometheus.ProcessCollectorOpts{}),
        prometheus.NewGoCollector(),
    )

    http.Handle("/metrics", promhttp.HandlerFor(reg, promhttp.HandlerOpts{}))
    log.Fatal(http.ListenAndServe(":8080", nil))
    log.Printf(" [*] Waiting for logs. To exit press CTRL+C")
    <-forever
}

//relevant structs go here for parsing JSON

添加了goroutine和main以获得更大的图像。
有一致性，因为我会不时接收数据。
我认为我在这里缺少的技能是如何调用函数，以便将myMap中的key:values放入
func(c * ClusterManager)ReallyExpensiveAssessmentOfTheSystemState()(
oomCountByHost map [string] int，ramUsageByHost map [string] float64，){}

最佳答案

我认为我在这里缺少的技能是如何调用函数，以便使myMap中的key:values进入func(c * ClusterManager)ReallyExpensiveAssessmentOfTheSystemState()(oomCountByHost map [string] int，ramUsageByHost map [string] float64，){}

在ReallyExpensiveAssessmentOfTheSystemState方法中调用Collect。您的 map 不会“进入”该方法，而是由ReallyExpensiveAssessmentOfTheSystemState返回。

只需将代码从goroutine移到ReallyExpensiveAssessmentOfTheSystemState:

func (c *ClusterManager) ReallyExpensiveAssessmentOfTheSystemState() map[string]float64 {
    myMap := make(map[string]float64)
    myMap["device1"] = 754
    myMap["device2"] = 765

    return myMap
}

func (cc ClusterManagerCollector) Collect(ch chan<- prometheus.Metric) {
    values := cc.ClusterManager.ReallyExpensiveAssessmentOfTheSystemState()

    for key, value := range values {
        ch <- prometheus.MustNewConstMetric(
            valueDesc,
            prometheus.CounterValue,
            value,
            key,
        )
    }
}

关于go - Prometheus Type Collector-如何使用我自己的数据来提供 map ，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/54400025/