Dropwizard 输入数据格式
使用 dropwizard 输入数据格式来解析 JSON Dropwizard 的单个 dropwizard 指标注册表的表示形式到 Telegraf 指标中。默认情况下，标签从指标名称中解析，就像它们是实际的 InfluxDB 行协议键 (measurement<,tag_set>) 一样，这可以通过定义自定义的 模板模式 来覆盖。支持所有字段值类型，string、number 和 boolean。
配置
[[inputs.file]]
files = ["example"]
## Data format to consume.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
data_format = "dropwizard"
## Used by the templating engine to join matched values when cardinality is > 1
separator = "_"
## Each template line requires a template pattern. It can have an optional
## filter before the template and separated by spaces. It can also have optional extra
## tags following the template. Multiple tags should be separated by commas and no spaces
## similar to the line protocol format. There can be only one default template.
## Templates support below format:
## 1. filter + template
## 2. filter + template + extra tag(s)
## 3. filter + template with field key
## 4. default template
## By providing an empty template array, templating is disabled and measurements are parsed as InfluxDB line protocol keys (measurement<,tag_set>)
templates = []
## You may use an appropriate [gjson path](https://github.com/tidwall/gjson#path-syntax)
## to locate the metric registry within the JSON document
# dropwizard_metric_registry_path = "metrics"
## You may use an appropriate [gjson path](https://github.com/tidwall/gjson#path-syntax)
## to locate the default time of the measurements within the JSON document
# dropwizard_time_path = "time"
# dropwizard_time_format = "2006-01-02T15:04:05Z07:00"
## You may use an appropriate [gjson path](https://github.com/tidwall/gjson#path-syntax)
## to locate the tags map within the JSON document
# dropwizard_tags_path = "tags"
## You may even use tag paths per tag
# [inputs.exec.dropwizard_tag_paths]
# tag1 = "tags.tag1"
# tag2 = "tags.tag2"
示例
dropwizard 指标注册表的典型 JSON
{
"version": "3.0.0",
"counters" : {
"measurement,tag1=green" : {
"count" : 1
}
},
"meters" : {
"measurement" : {
"count" : 1,
"m15_rate" : 1.0,
"m1_rate" : 1.0,
"m5_rate" : 1.0,
"mean_rate" : 1.0,
"units" : "events/second"
}
},
"gauges" : {
"measurement" : {
"value" : 1
}
},
"histograms" : {
"measurement" : {
"count" : 1,
"max" : 1.0,
"mean" : 1.0,
"min" : 1.0,
"p50" : 1.0,
"p75" : 1.0,
"p95" : 1.0,
"p98" : 1.0,
"p99" : 1.0,
"p999" : 1.0,
"stddev" : 1.0
}
},
"timers" : {
"measurement" : {
"count" : 1,
"max" : 1.0,
"mean" : 1.0,
"min" : 1.0,
"p50" : 1.0,
"p75" : 1.0,
"p95" : 1.0,
"p98" : 1.0,
"p99" : 1.0,
"p999" : 1.0,
"stddev" : 1.0,
"m15_rate" : 1.0,
"m1_rate" : 1.0,
"m5_rate" : 1.0,
"mean_rate" : 1.0,
"duration_units" : "seconds",
"rate_units" : "calls/second"
}
}
}
将被翻译成 4 种不同的指标
measurement,metric_type=counter,tag1=green count=1
measurement,metric_type=meter count=1,m15_rate=1.0,m1_rate=1.0,m5_rate=1.0,mean_rate=1.0
measurement,metric_type=gauge value=1
measurement,metric_type=histogram count=1,max=1.0,mean=1.0,min=1.0,p50=1.0,p75=1.0,p95=1.0,p98=1.0,p99=1.0,p999=1.0
measurement,metric_type=timer count=1,max=1.0,mean=1.0,min=1.0,p50=1.0,p75=1.0,p95=1.0,p98=1.0,p99=1.0,p999=1.0,stddev=1.0,m15_rate=1.0,m1_rate=1.0,m5_rate=1.0,mean_rate=1.0
您还可以从任何 JSON 文档中解析 dropwizard 注册表，该文档在某些内部字段中包含 dropwizard 注册表。例如，要解析以下 JSON 文档
{
"time" : "2017-02-22T14:33:03.662+02:00",
"tags" : {
"tag1" : "green",
"tag2" : "yellow"
},
"metrics" : {
"counters" : {
"measurement" : {
"count" : 1
}
},
"meters" : {},
"gauges" : {},
"histograms" : {},
"timers" : {}
}
}
并将其翻译成
measurement,metric_type=counter,tag1=green,tag2=yellow count=1 1487766783662000000
您只需使用以下附加配置属性
dropwizard_metric_registry_path = "metrics"
dropwizard_time_path = "time"
dropwizard_time_format = "2006-01-02T15:04:05Z07:00"
dropwizard_tags_path = "tags"
## tag paths per tag are supported too, eg.
#[inputs.yourinput.dropwizard_tag_paths]
# tag1 = "tags.tag1"
# tag2 = "tags.tag2"
此页是否对您有帮助？
感谢您的反馈！