Math filter plugin v1.1.0

The calculation to be performed. As can be seen from the example above by using multiple inner arrays one can perform calculation with multiple steps or multiple distinct calculations on a single event.

Each inner array must have 4 elements

The first element must be the operator. Valid operators are:

The second element is the left hand side operand. It can be a field, a literal or a memory register. If referring to a memory register, ensure that it has been set to a value in a previous calculation.

The third element is the right hand side operand. It can be a field, a literal or a memory register.

The fourth element is the "target". It is where the result is stored and can be a memory register or a field in your event. It cannot be a literal.

For a calculation to continue, any operand taken from a field in the event must be Numeric or a Logstash Timestamp and not nil. Timestamps are converted to floating point seconds since the UNIX epoch (Jan, 1 1970 00:00:00 UTC) before being operated on.

The operators Divide, FloatDivide and Modulo have a divide by zero check before the operation is executed.
The Power operator has a check for a negative number being raised to a fractional power as this results in a Complex number that can’t be stored in an event or serialized to JSON.
The Round operator can convert integers to floats round(42, 1) -> 42.0 and floats to integers (rounding up or down) round(0.75, 0) -> 1.

You can choose not to use memory registers and store intermediate results in fields instead but then you may need to remove the fields later.
Memory registers are implemented as a sparse array and the integer between the square brackets is a zero based direct index into the array. For example, MEM[5], 5 is a reference to the 6th element in the array. The array is cleared for each event, this means that you can’t leave a value behind for a later event to use. Each math filter will have its own memory register array so you can’t share values between math filters in the same pipeline or across pipelines.

There is some logging of the calculation progress at the debug logging level.
This is an excerpt from the full example at the top of this page:

[DEBUG][logstash.filters.math    ] executing {"function"=>"float_divide", "left_field"=>"operand 1: 5", "right_field"=>"operand 2: 9", "target"=>"register 0: 'MEM[0]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"float_divide", "target"=>"register 0: 'MEM[0]'", "result"=>0.5555555555555556}
[DEBUG][logstash.filters.math    ] executing {"function"=>"subtract", "left_field"=>"event operand 1: '[outside]'", "right_field"=>"operand 2: 32", "target"=>"register 1: 'MEM[1]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"subtract", "target"=>"register 1: 'MEM[1]'", "result"=>#<BigDecimal:2c16adee,'0.297E2',3(4)>}
[DEBUG][logstash.filters.math    ] executing {"function"=>"multiply", "left_field"=>"register operand 1: 'MEM[1]'", "right_field"=>"register operand 2: 'MEM[0]'", "target"=>"register 1: 'MEM[1]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"multiply", "target"=>"register 1: 'MEM[1]'", "result"=>#<BigDecimal:76bc6a4c,'0.1650000000000000132E2',19(20)>}
[DEBUG][logstash.filters.math    ] executing {"function"=>"subtract", "left_field"=>"event operand 1: '[inside]'", "right_field"=>"operand 2: 32", "target"=>"register 2: 'MEM[2]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"subtract", "target"=>"register 2: 'MEM[2]'", "result"=>#<BigDecimal:6761cedc,'0.3924E2',4(8)>}
[DEBUG][logstash.filters.math    ] executing {"function"=>"multiply", "left_field"=>"register operand 1: 'MEM[2]'", "right_field"=>"register operand 2: 'MEM[0]'", "target"=>"register 2: 'MEM[2]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"multiply", "target"=>"register 2: 'MEM[2]'", "result"=>#<BigDecimal:5b03b20a,'0.21800000000000001744E2',20(24)>}
[DEBUG][logstash.filters.math    ] executing {"function"=>"subtract", "left_field"=>"register operand 1: 'MEM[2]'", "right_field"=>"register operand 2: 'MEM[1]'", "target"=>"register 3: 'MEM[3]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"subtract", "target"=>"register 3: 'MEM[3]'", "result"=>#<BigDecimal:2e0e043,'0.5300000000000000424E1',19(20)>}
[DEBUG][logstash.filters.math    ] executing {"function"=>"round", "left_field"=>"register operand 1: 'MEM[3]'", "right_field"=>"operand 2: 1", "target"=>"event result: '[delta_in_c]'"}
[DEBUG][logstash.filters.math    ] calculation result stored {"function"=>"round", "target"=>"event result: '[delta_in_c]'", "result"=>#<BigDecimal:5415cc0,'0.53E1',2(4)>}

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

    # You can also add multiple fields at once:
    filter {
      math {
        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 {
      math {
        add_tag => [ "foo_%{somefield}" ]
      }
    }

    # You can also add multiple tags at once:
    filter {
      math {
        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 math filters. Adding a named ID in this case will help in monitoring Logstash when using the monitoring APIs.

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

    # You can also remove multiple fields at once:
    filter {
      math {
        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 {
      math {
        remove_tag => [ "foo_%{somefield}" ]
      }
    }

    # You can also remove multiple tags at once:
    filter {
      math {
        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.