234 lines
8.9 KiB
Markdown
234 lines
8.9 KiB
Markdown
# Grok
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The grok data format parses line delimited data using a regular expression like
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language.
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The best way to get acquainted with grok patterns is to read the logstash docs,
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which are available here:
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https://www.elastic.co/guide/en/logstash/current/plugins-filters-grok.html
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The grok parser uses a slightly modified version of logstash "grok"
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patterns, with the format:
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```
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%{<capture_syntax>[:<semantic_name>][:<modifier>]}
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```
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The `capture_syntax` defines the grok pattern that's used to parse the input
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line and the `semantic_name` is used to name the field or tag. The extension
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`modifier` controls the data type that the parsed item is converted to or
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other special handling.
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By default all named captures are converted into string fields.
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If a pattern does not have a semantic name it will not be captured.
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Timestamp modifiers can be used to convert captures to the timestamp of the
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parsed metric. If no timestamp is parsed the metric will be created using the
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current time.
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You must capture at least one field per line.
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- Available modifiers:
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- string (default if nothing is specified)
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- int
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- float
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- duration (ie, 5.23ms gets converted to int nanoseconds)
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- tag (converts the field into a tag)
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- drop (drops the field completely)
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- measurement (use the matched text as the measurement name)
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- Timestamp modifiers:
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- ts (This will auto-learn the timestamp format)
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- ts-ansic ("Mon Jan _2 15:04:05 2006")
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- ts-unix ("Mon Jan _2 15:04:05 MST 2006")
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- ts-ruby ("Mon Jan 02 15:04:05 -0700 2006")
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- ts-rfc822 ("02 Jan 06 15:04 MST")
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- ts-rfc822z ("02 Jan 06 15:04 -0700")
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- ts-rfc850 ("Monday, 02-Jan-06 15:04:05 MST")
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- ts-rfc1123 ("Mon, 02 Jan 2006 15:04:05 MST")
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- ts-rfc1123z ("Mon, 02 Jan 2006 15:04:05 -0700")
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- ts-rfc3339 ("2006-01-02T15:04:05Z07:00")
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- ts-rfc3339nano ("2006-01-02T15:04:05.999999999Z07:00")
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- ts-httpd ("02/Jan/2006:15:04:05 -0700")
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- ts-epoch (seconds since unix epoch, may contain decimal)
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- ts-epochnano (nanoseconds since unix epoch)
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- ts-syslog ("Jan 02 15:04:05", parsed time is set to the current year)
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- ts-"CUSTOM"
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CUSTOM time layouts must be within quotes and be the representation of the
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"reference time", which is `Mon Jan 2 15:04:05 -0700 MST 2006`.
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To match a comma decimal point you can use a period. For example `%{TIMESTAMP:timestamp:ts-"2006-01-02 15:04:05.000"}` can be used to match `"2018-01-02 15:04:05,000"`
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To match a comma decimal point you can use a period in the pattern string.
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See https://golang.org/pkg/time/#Parse for more details.
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Telegraf has many of its own [built-in patterns](/plugins/parsers/grok/influx_patterns.go),
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as well as support for most of
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[logstash's builtin patterns](https://github.com/logstash-plugins/logstash-patterns-core/blob/master/patterns/grok-patterns).
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_Golang regular expressions do not support lookahead or lookbehind.
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logstash patterns that depend on these are not supported._
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If you need help building patterns to match your logs,
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you will find the https://grokdebug.herokuapp.com application quite useful!
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### Configuration
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```toml
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[[inputs.file]]
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## Files to parse each interval.
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## These accept standard unix glob matching rules, but with the addition of
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## ** as a "super asterisk". ie:
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## /var/log/**.log -> recursively find all .log files in /var/log
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## /var/log/*/*.log -> find all .log files with a parent dir in /var/log
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## /var/log/apache.log -> only tail the apache log file
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files = ["/var/log/apache/access.log"]
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## The dataformat to be read from files
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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 = "grok"
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## This is a list of patterns to check the given log file(s) for.
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## Note that adding patterns here increases processing time. The most
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## efficient configuration is to have one pattern.
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## Other common built-in patterns are:
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## %{COMMON_LOG_FORMAT} (plain apache & nginx access logs)
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## %{COMBINED_LOG_FORMAT} (access logs + referrer & agent)
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grok_patterns = ["%{COMBINED_LOG_FORMAT}"]
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## Full path(s) to custom pattern files.
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grok_custom_pattern_files = []
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## Custom patterns can also be defined here. Put one pattern per line.
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grok_custom_patterns = '''
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'''
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## Timezone allows you to provide an override for timestamps that
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## don't already include an offset
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## e.g. 04/06/2016 12:41:45 data one two 5.43µs
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##
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## Default: "" which renders UTC
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## Options are as follows:
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## 1. Local -- interpret based on machine localtime
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## 2. "Canada/Eastern" -- Unix TZ values like those found in https://en.wikipedia.org/wiki/List_of_tz_database_time_zones
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## 3. UTC -- or blank/unspecified, will return timestamp in UTC
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grok_timezone = "Canada/Eastern"
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```
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#### Timestamp Examples
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This example input and config parses a file using a custom timestamp conversion:
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```
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2017-02-21 13:10:34 value=42
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```
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```toml
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[[inputs.file]]
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grok_patterns = ['%{TIMESTAMP_ISO8601:timestamp:ts-"2006-01-02 15:04:05"} value=%{NUMBER:value:int}']
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```
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This example input and config parses a file using a timestamp in unix time:
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```
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1466004605 value=42
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1466004605.123456789 value=42
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```
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```toml
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[[inputs.file]]
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grok_patterns = ['%{NUMBER:timestamp:ts-epoch} value=%{NUMBER:value:int}']
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```
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This example parses a file using a built-in conversion and a custom pattern:
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```
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Wed Apr 12 13:10:34 PST 2017 value=42
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```
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```toml
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[[inputs.file]]
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grok_patterns = ["%{TS_UNIX:timestamp:ts-unix} value=%{NUMBER:value:int}"]
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grok_custom_patterns = '''
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TS_UNIX %{DAY} %{MONTH} %{MONTHDAY} %{HOUR}:%{MINUTE}:%{SECOND} %{TZ} %{YEAR}
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'''
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```
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For cases where the timestamp itself is without offset, the `timezone` config var is available
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to denote an offset. By default (with `timezone` either omit, blank or set to `"UTC"`), the times
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are processed as if in the UTC timezone. If specified as `timezone = "Local"`, the timestamp
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will be processed based on the current machine timezone configuration. Lastly, if using a
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timezone from the list of Unix [timezones](https://en.wikipedia.org/wiki/List_of_tz_database_time_zones),
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grok will offset the timestamp accordingly.
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#### TOML Escaping
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When saving patterns to the configuration file, keep in mind the different TOML
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[string](https://github.com/toml-lang/toml#string) types and the escaping
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rules for each. These escaping rules must be applied in addition to the
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escaping required by the grok syntax. Using the Multi-line line literal
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syntax with `'''` may be useful.
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The following config examples will parse this input file:
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```
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|42|\uD83D\uDC2F|'telegraf'|
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```
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Since `|` is a special character in the grok language, we must escape it to
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get a literal `|`. With a basic TOML string, special characters such as
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backslash must be escaped, requiring us to escape the backslash a second time.
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```toml
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[[inputs.file]]
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grok_patterns = ["\\|%{NUMBER:value:int}\\|%{UNICODE_ESCAPE:escape}\\|'%{WORD:name}'\\|"]
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grok_custom_patterns = "UNICODE_ESCAPE (?:\\\\u[0-9A-F]{4})+"
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```
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We cannot use a literal TOML string for the pattern, because we cannot match a
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`'` within it. However, it works well for the custom pattern.
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```toml
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[[inputs.file]]
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grok_patterns = ["\\|%{NUMBER:value:int}\\|%{UNICODE_ESCAPE:escape}\\|'%{WORD:name}'\\|"]
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grok_custom_patterns = 'UNICODE_ESCAPE (?:\\u[0-9A-F]{4})+'
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```
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A multi-line literal string allows us to encode the pattern:
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```toml
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[[inputs.file]]
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grok_patterns = ['''
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\|%{NUMBER:value:int}\|%{UNICODE_ESCAPE:escape}\|'%{WORD:name}'\|
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''']
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grok_custom_patterns = 'UNICODE_ESCAPE (?:\\u[0-9A-F]{4})+'
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```
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#### Tips for creating patterns
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Writing complex patterns can be difficult, here is some advice for writing a
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new pattern or testing a pattern developed [online](https://grokdebug.herokuapp.com).
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Create a file output that writes to stdout, and disable other outputs while
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testing. This will allow you to see the captured metrics. Keep in mind that
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the file output will only print once per `flush_interval`.
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```toml
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[[outputs.file]]
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files = ["stdout"]
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```
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- Start with a file containing only a single line of your input.
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- Remove all but the first token or piece of the line.
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- Add the section of your pattern to match this piece to your configuration file.
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- Verify that the metric is parsed successfully by running Telegraf.
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- If successful, add the next token, update the pattern and retest.
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- Continue one token at a time until the entire line is successfully parsed.
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#### Performance
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Performance depends heavily on the regular expressions that you use, but there
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are a few techniques that can help:
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- Avoid using patterns such as `%{DATA}` that will always match.
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- If possible, add `^` and `$` anchors to your pattern:
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```
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[[inputs.file]]
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grok_patterns = ["^%{COMBINED_LOG_FORMAT}$"]
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```
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