The Grep Filter plugin allows you to match or exclude specific records based on regular expression patterns for values or nested values.
Configuration Parameters
The plugin supports the following configuration parameters:
Key
Value Format
Description
Regex
KEY REGEX
Keep records in which the content of KEY matches the regular expression.
Exclude
KEY REGEX
Exclude records in which the content of KEY matches the regular expression.
Logical_Op
Operation
Specify which logical operator to use. AND , OR and legacy are allowed as an Operation. Default is legacy for backward compatibility. In legacy mode the behaviour is either AND or OR depending whether the grep is including (uses AND) or excluding (uses OR). Only available from 2.1+.
Record Accessor Enabled
This plugin enables the Record Accessor feature to specify the KEY. Using the record accessor is suggested if you want to match values against nested values.
Getting Started
In order to start filtering records, you can run the filter from the command line or through the configuration file. The following example assumes that you have a file called lines.txt with the following content:
Note: using the command line mode need special attention to quote the regular expressions properly. It's suggested to use a configuration file.
The following command will load the tail plugin and read the content of lines.txt file. Then the grep filter will apply a regular expression rule over the log field (created by tail plugin) and only pass the records which field value starts with aa:
[SERVICE] parsers_file /path/to/parsers.conf[INPUT] name tail path lines.txt parser json[FILTER] name grep match * regex log aa[OUTPUT] name stdout match *
The filter allows to use multiple rules which are applied in order, you can have many Regex and Exclude entries as required.
Nested fields example
If you want to match or exclude records based on nested values, you can use a Record Accessor format as the KEY name. Consider the following record example:
It may be that in your processing pipeline you want to drop records that are missing certain keys.
A simple way to do this is just to exclude with a regex that matches anything, a missing key will fail this check.
Here is an example that checks for a specific valid value for the key as well:
# Use Grep to verify the contents of the iot_timestamp value.
# If the iot_timestamp key does not exist, this will fail
# and exclude the row.
[FILTER]
Name grep
Alias filter-iots-grep
Match iots_thread.*
Regex iot_timestamp ^\d{4}-\d{2}-\d{2}
The specified key iot_timestamp must match the expected expression - if it does not or is missing/empty then it will be excluded.
Multiple conditions
If you want to set multiple Regex or Exclude, you can use Logical_Op property to use logical conjuction or disjunction.
Note: If Logical_Op is set, setting both 'Regex' and Exclude results in an error.
[INPUT] Name dummy Dummy {"endpoint":"localhost","value":"something"} Tag dummy[FILTER] Name grep Match * Logical_Op or Regex value something Regex value error[OUTPUT] Name stdout
pipeline:inputs: - name:dummydummy:'{"endpoint":"localhost", "value":"something"}'tag:dummyfilters: - name:grepmatch:'*'logical_op:orregex: - value something - value erroroutputs: - name:stdout
Output will be
Fluent Bit v2.0.9
* Copyright (C) 2015-2022 The Fluent Bit Authors
* Fluent Bit is a CNCF sub-project under the umbrella of Fluentd
* https://fluentbit.io
[2023/01/22 09:46:49] [ info] [fluent bit] version=2.0.9, commit=16eae10786, pid=33268
[2023/01/22 09:46:49] [ info] [storage] ver=1.2.0, type=memory, sync=normal, checksum=off, max_chunks_up=128
[2023/01/22 09:46:49] [ info] [cmetrics] version=0.5.8
[2023/01/22 09:46:49] [ info] [ctraces ] version=0.2.7
[2023/01/22 09:46:49] [ info] [input:dummy:dummy.0] initializing
[2023/01/22 09:46:49] [ info] [input:dummy:dummy.0] storage_strategy='memory' (memory only)
[2023/01/22 09:46:49] [ info] [filter:grep:grep.0] OR mode
[2023/01/22 09:46:49] [ info] [sp] stream processor started
[2023/01/22 09:46:49] [ info] [output:stdout:stdout.0] worker #0 started
[0] dummy: [1674348410.558341857, {"endpoint"=>"localhost", "value"=>"something"}]
[0] dummy: [1674348411.546425499, {"endpoint"=>"localhost", "value"=>"something"}]