Csv filter plugin

Define whether column names should be auto-detected from the header column or not. Defaults to false.

Define whether column names should autogenerated or not. Defaults to true. If set to false, columns not having a header specified will not be parsed.

Define a list of column names (in the order they appear in the CSV, as if it were a header line). If columns is not configured, or there are not enough columns specified, the default column names are "column1", "column2", etc. In the case that there are more columns in the data than specified in this column list, extra columns will be auto-numbered: (e.g. "user_defined_1", "user_defined_2", "column3", "column4", etc.)

Define a set of datatype conversions to be applied to columns. Possible conversions are integer, float, date, date_time, boolean

Example:

    filter {
      csv {
        convert => {
          "column1" => "integer"
          "column2" => "boolean"
        }
      }
    }

Define the character used to quote CSV fields. If this is not specified the default is a double quote ". Optional.

Define the column separator value. If this is not specified, the default is a comma ,. If you want to define a tabulation as a separator, you need to set the value to the actual tab character and not \t. Optional.

Define whether empty columns should be skipped. Defaults to false. If set to true, columns containing no value will not get set.

Define whether empty rows could potentially be skipped. Defaults to false. If set to true, rows containing no value will be tagged with "_csvskippedemptyfield". This tag can referenced by users if they wish to cancel events using an if conditional statement.

Define whether the header should be skipped. Defaults to false. If set to true, the header will be skipped. Assumes that header is not repeated within further rows as such rows will also be skipped. If skip_header is set without autodetect_column_names being set then columns should be set which will result in the skipping of any row that exactly matches the specified column values. If skip_header and autodetect_column_names are specified then columns should not be specified, in this case autodetect_column_names will fill the columns setting in the background, from the first event seen, and any subsequent values that match what was autodetected will be skipped.

The CSV data in the value of the source field will be expanded into a data structure.

Define target field for placing the data. Defaults to writing to the root of the event.

If this filter is successful, add any arbitrary fields to this event. Field names can be dynamic and include parts of the event using the %{field}.

Example:

    filter {
      csv {
        add_field => { "foo_%{somefield}" => "Hello world, from %{host}" }
      }
    }

    # You can also add multiple fields at once:
    filter {
      csv {
        add_field => {
          "foo_%{somefield}" => "Hello world, from %{host}"
          "new_field" => "new_static_value"
        }
      }
    }

If the event has field "somefield" == "hello" this filter, on success, would add field foo_hello if it is present, with the value above and the %{host} piece replaced with that value from the event. The second example would also add a hardcoded field.

If this filter is successful, add arbitrary tags to the event. Tags can be dynamic and include parts of the event using the %{field} syntax.

Example:

    filter {
      csv {
        add_tag => [ "foo_%{somefield}" ]
      }
    }

    # You can also add multiple tags at once:
    filter {
      csv {
        add_tag => [ "foo_%{somefield}", "taggedy_tag"]
      }
    }

If the event has field "somefield" == "hello" this filter, on success, would add a tag foo_hello (and the second example would of course add a taggedy_tag tag).

Disable or enable metric logging for this specific plugin instance by default we record all the metrics we can, but you can disable metrics collection for a specific plugin.

Add a unique ID to the plugin configuration. If no ID is specified, Logstash will generate one. It is strongly recommended to set this ID in your configuration. This is particularly useful when you have two or more plugins of the same type, for example, if you have 2 csv filters. Adding a named ID in this case will help in monitoring Logstash when using the monitoring APIs.

    filter {
      csv {
        id => "ABC"
      }
    }

Call the filter flush method at regular interval. Optional.

If this filter is successful, remove arbitrary fields from this event. Fields names can be dynamic and include parts of the event using the %{field} Example:

    filter {
      csv {
        remove_field => [ "foo_%{somefield}" ]
      }
    }

    # You can also remove multiple fields at once:
    filter {
      csv {
        remove_field => [ "foo_%{somefield}", "my_extraneous_field" ]
      }
    }

If the event has field "somefield" == "hello" this filter, on success, would remove the field with name foo_hello if it is present. The second example would remove an additional, non-dynamic field.

If this filter is successful, remove arbitrary tags from the event. Tags can be dynamic and include parts of the event using the %{field} syntax.

Example:

    filter {
      csv {
        remove_tag => [ "foo_%{somefield}" ]
      }
    }

    # You can also remove multiple tags at once:
    filter {
      csv {
        remove_tag => [ "foo_%{somefield}", "sad_unwanted_tag"]
      }
    }

If the event has field "somefield" == "hello" this filter, on success, would remove the tag foo_hello if it is present. The second example would remove a sad, unwanted tag as well.