60 lines
2.4 KiB
Markdown
60 lines
2.4 KiB
Markdown
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# Value Parser Plugin
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The "value" data format translates single values into Telegraf metrics. This
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is done by assigning a measurement name and setting a single field ("value")
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as the parsed metric.
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## Configuration
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```toml
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[[inputs.exec]]
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## Commands array
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commands = ["cat /proc/sys/kernel/random/entropy_avail"]
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## override the default metric name of "exec"
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name_override = "entropy_available"
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## override the field name of "value"
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# value_field_name = "value"
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## Data format to consume.
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## Each data format has its own unique set of configuration options, read
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## more about them here:
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## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
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data_format = "value"
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data_type = "integer" # required
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```
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### Metric name
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It is recommended to set `name_override` to a measurement name that makes sense
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for your metric, otherwise it will just be set to the name of the plugin.
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### Datatype
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You **must** tell Telegraf what type of metric to collect by using the
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`data_type` configuration option. Available options are:
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- `integer`: converts the received data to an integer value. This setting will
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produce an error on non-integer data.
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- `float`: converts the received data to a floating-point value. This setting
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will treat integers as floating-point values and produces an error
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on data that cannot be converted (e.g. strings).
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- `string`: outputs the data as a string.
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- `base64`: outputs the data as a base64 encoded string.
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- `boolean`: converts the received data to a boolean value. This setting will
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produce an error on any data except for `true` and `false` strings.
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- `auto_integer`: converts the received data to an integer value if possible and
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will return the data as string otherwise. This is helpful for
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mixed-type data.
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- `auto_float`: converts the received data to a floating-point value if possible
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and will return the data as string otherwise. This is helpful
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for mixed-type data. Integer data will be treated as
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floating-point values.
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**NOTE**: The `auto` conversions might convert data to their prioritized type
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by accident, for example if a string data-source provides `"55"` it will be
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converted to integer/float. This might break outputs that require the same
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datatype within a field or column. It is thus recommended to use *strict* typing
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whenever possible.
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