The dropEvent()
function can be used both
during queries and within the parser pipeline.
Depending on usage, the function has different behavior:
If used during parsing, the event is dropped and removed entirely from the query output, meaning that the event data will not be stored in Falcon LogScale.
If used within normal searching, the
dropEvent()
function is simply an alias for false - it behaves the same asfalse
.
Note
The dropEvent()
does not accept any
arguments. The dropEvent()
has different
behaviour depending on usage in parser or in normal searches.
dropEvent()
Examples
Click
next to an example below to get the full details.Drop Event During Parsing
Drop event during parsing using the
dropEvent()
function
Query
parseJson()
| case { someField = "some_value"
| dropEvent(); * }
| parseTimestamp(field=@timestamp)
Introduction
The dropEvent()
function is often used within
parsers to drop events during parsing that do not need to be
ingested. The following example shows how to filter events as part
of a parser by matching a particular field value from being
ingested.
Step-by-Step
Starting with the source repository events.
- logscale
parseJson()
Parses the incoming data to identify JSON values and converts them into a usable field.
- logscale
| case { someField = "some_value" | dropEvent(); * }
Starts a
case
statement, with the first matching expression identifying a field value in the extracted JSON field from the returned results. Then drops the event. This has the effect of terminating the parsing for this event, as there is no more data to be processed. - logscale
| parseTimestamp(field=@timestamp)
Parses the timestamp from the @timestamp field for all other events that do not match the JSON value.
Event Result set.
Summary and Results
This query is used to drop events at ingestion. When used within the
parser pipeline, the dropEvent()
is a simple and
practical way of eliminating events during the parsing of incoming data.
Drop Events Based on Parsing JSON Value
Query
case {
@rawstring="#*"
| dropEvent();
* }
Introduction
When parsing incoming data, it is sometimes the case that the data
includes 'commented' data, where,for example, the
#
character is used to
identify comments in files rather than real data. This example
removes those lines from the ingest process during parsing using
the dropEvent()
function to drop the entire
event from the ingest pipeline.
Step-by-Step
Starting with the source repository events.
- logscale
case { @rawstring="#*" | dropEvent();
Starts a
case
statement, with the first matching expression looking for the hash symbol in a line to indicate that it could be removed, then dropping the entire event usingdropEvent()
- logscale
* }
For all other lines, the
case
expression matches all other events and lets them through. Event Result set.
Summary and Results
This query is used to remove data at ingestion, in this example data
that matches a typical source construct (the comment). When used within
the parser pipeline, the dropEvent()
function
ensures that the data is removed entirely from the query output, meaning
that the event data will not be stored in LogScale.
Drop Events Based on Specific Field Values or Patterns
Drop events based on specific field values or patterns during
normal searching using the dropEvent()
function with case statement
Query
case {
fielda = badresult | dropEvent();
fieldb = badresult | dropEvent();
wildcard("badip", field[fieldc, fieldd] | dropEvent())
}
Introduction
In this example, the dropEvent()
function is
used within normal searching with a case statement to drop events
based on specific values and patterns. When used within normal
searching, the dropEvent()
function is simply
an alias for false
- it behaves the same as
false. It filters out specific events from the results.
Step-by-Step
Starting with the source repository events.
- logscale
case { fielda = badresult | dropEvent(); fieldb = badresult | dropEvent(); wildcard("badip", field[fieldc, fieldd] | dropEvent()) }
Starts a
case
statement containing the following three conditions:If fielda equals
badresult
, drop the event.If fieldb equals
badresult
, drop the event.If either fieldc or fieldd contains the string
badip
(using wildcard matching), drop the event.Each condition uses the
dropEvent()
function as the action to take when the condition is met. Thewildcard()
function is used in the third condition to perform pattern matching with wildcards against multiple fields specified in the array notationfield[fieldc, fieldd]
. Event Result set.
Summary and Results
This query is used to drop events based on specific field values or patterns. In all three cases, the events that contain the filtered information will be removed from the results. This is useful, for example, for event processing or log filtering.