110 lines
3.5 KiB
Markdown
110 lines
3.5 KiB
Markdown
# CSV
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The `csv` parser creates metrics from a document containing comma separated
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values.
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### Configuration
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```toml
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[[inputs.file]]
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files = ["example"]
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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 = "csv"
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## Indicates how many rows to treat as a header. By default, the parser assumes
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## there is no header and will parse the first row as data. If set to anything more
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## than 1, column names will be concatenated with the name listed in the next header row.
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## If `csv_column_names` is specified, the column names in header will be overridden.
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csv_header_row_count = 0
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## For assigning custom names to columns
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## If this is specified, all columns should have a name
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## Unnamed columns will be ignored by the parser.
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## If `csv_header_row_count` is set to 0, this config must be used
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csv_column_names = []
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## For assigning explicit data types to columns.
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## Supported types: "int", "float", "bool", "string".
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## If this is not specified, type conversion will be done on the types above.
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csv_column_types = []
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## Indicates the number of rows to skip before looking for header information.
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csv_skip_rows = 0
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## Indicates the number of columns to skip before looking for data to parse.
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## These columns will be skipped in the header as well.
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csv_skip_columns = 0
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## The seperator between csv fields
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## By default, the parser assumes a comma (",")
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csv_delimiter = ","
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## The character reserved for marking a row as a comment row
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## Commented rows are skipped and not parsed
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csv_comment = ""
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## If set to true, the parser will remove leading whitespace from fields
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## By default, this is false
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csv_trim_space = false
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## Columns listed here will be added as tags. Any other columns
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## will be added as fields.
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csv_tag_columns = []
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## The column to extract the name of the metric from
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csv_measurement_column = ""
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## The column to extract time information for the metric
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## `csv_timestamp_format` must be specified if this is used
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csv_timestamp_column = ""
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## The format of time data extracted from `csv_timestamp_column`
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## this must be specified if `csv_timestamp_column` is specified
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csv_timestamp_format = ""
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```
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#### csv_timestamp_column, csv_timestamp_format
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By default the current time will be used for all created metrics, to set the
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time using the JSON document you can use the `csv_timestamp_column` and
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`csv_timestamp_format` options together to set the time to a value in the parsed
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document.
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The `csv_timestamp_column` option specifies the column name containing the
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time value and `csv_timestamp_format` must be set to a Go "reference time"
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which is defined to be the specific time: `Mon Jan 2 15:04:05 MST 2006`.
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Consult the Go [time][time parse] package for details and additional examples
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on how to set the time format.
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### Metrics
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One metric is created for each row with the columns added as fields. The type
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of the field is automatically determined based on the contents of the value.
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### Examples
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Config:
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```
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[[inputs.file]]
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files = ["example"]
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data_format = "csv"
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csv_header_row_count = 1
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csv_timestamp_column = "time"
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csv_timestamp_format = "2006-01-02T15:04:05Z07:00"
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```
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Input:
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```
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measurement,cpu,time_user,time_system,time_idle,time
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cpu,cpu0,42,42,42,2018-09-13T13:03:28Z
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```
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Output:
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```
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cpu cpu=cpu0,time_user=42,time_system=42,time_idle=42 1536869008000000000
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```
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