-
Notifications
You must be signed in to change notification settings - Fork 490
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
[DOC] Add new doc for grok processor (#5019)
* Add new doc for grok processor Signed-off-by: Melissa Vagi <[email protected]> * Writing Signed-off-by: Melissa Vagi <[email protected]> * Writing Signed-off-by: Melissa Vagi <[email protected]> * Add custom patterns Signed-off-by: Melissa Vagi <[email protected]> * Update _api-reference/ingest-apis/processors/grok.md Co-authored-by: Heemin Kim <[email protected]> Signed-off-by: Melissa Vagi <[email protected]> * Update _api-reference/ingest-apis/processors/grok.md Co-authored-by: Heemin Kim <[email protected]> Signed-off-by: Melissa Vagi <[email protected]> * Address tech feedback Signed-off-by: Melissa Vagi <[email protected]> * Address tech feedback Signed-off-by: Melissa Vagi <[email protected]> * Revise content Signed-off-by: Melissa Vagi <[email protected]> * Revise intro section based on doc review Signed-off-by: Melissa Vagi <[email protected]> * Revise intro section based on doc review Signed-off-by: Melissa Vagi <[email protected]> * Revise intro section based on doc review Signed-off-by: Melissa Vagi <[email protected]> * Change example and intro sentences to examples Signed-off-by: Fanit Kolchina <[email protected]> * Link fix Signed-off-by: Fanit Kolchina <[email protected]> * Address doc review feedback Signed-off-by: Melissa Vagi <[email protected]> --------- Signed-off-by: Melissa Vagi <[email protected]> Signed-off-by: Fanit Kolchina <[email protected]> Co-authored-by: Heemin Kim <[email protected]> Co-authored-by: Fanit Kolchina <[email protected]> (cherry picked from commit 06fdfd7) Signed-off-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
- Loading branch information
1 parent
af7cf91
commit a923d26
Showing
1 changed file
with
212 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,212 @@ | ||
--- | ||
layout: default | ||
title: Grok | ||
parent: Ingest processors | ||
grand_parent: Ingest pipelines | ||
nav_order: 140 | ||
--- | ||
|
||
# Grok | ||
|
||
The `grok` processor is used to parse and structure unstructured data using pattern matching. You can use the `grok` processor to extract fields from log messages, web server access logs, application logs, and other log data that follows a consistent format. | ||
|
||
## Grok basics | ||
|
||
The `grok` processor uses a set of predefined patterns to match parts of the input text. Each pattern consists of a name and a regular expression. For example, the pattern `%{IP:ip_address}` matches an IP address and assigns it to the field `ip_address`. You can combine multiple patterns to create more complex expressions. For example, the pattern `%{IP:client} %{WORD:method} %{URIPATHPARM:request} %{NUMBER:bytes %NUMBER:duration}` matches a line from a web server access log and extracts the client IP address, the HTTP method, the request URI, the number of bytes sent, and the duration of the request. | ||
|
||
The `grok` processor is built on the [Oniguruma regular expression library](https://github.com/kkos/oniguruma/blob/master/doc/RE) and supports all the patterns from that library. You can use the [Grok Debugger](https://grokdebugger.com/) tool to test and debug your grok expressions. | ||
|
||
## Grok processor syntax | ||
|
||
The following is the basic syntax for the `grok` processor: | ||
|
||
```json | ||
{ | ||
"grok": { | ||
"field": "your_message", | ||
"patterns": ["your_patterns"] | ||
} | ||
} | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
## Configuration parameters | ||
|
||
To configure the `grok` processor, you have various options that allow you to define patterns, match specific keys, and control the processor's behavior. The following table lists the required and optional parameters for the `grok` processor. | ||
|
||
Parameter | Required | Description | | ||
|-----------|-----------|-----------| | ||
`field` | Required | The name of the field containing the text that should be parsed. | | ||
`patterns` | Required | A list of grok expressions used to match and extract named captures. The first matching expression in the list is returned. | | ||
`pattern_definitions` | Optional | A dictionary of pattern names and pattern tuples used to define custom patterns for the current processor. If a pattern matches an existing name, it overrides the pre-existing definition. | | ||
`trace_match` | Optional | When the parameter is set to `true`, the processor adds a field named `_grok_match_index` to the processed document. This field contains the index of the pattern within the `patterns` array that successfully matched the document. This information can be useful for debugging and understanding which pattern was applied to the document. Default is `false`. | | ||
`description` | Optional | A brief description of the processor. | | ||
`if` | Optional | A condition for running this processor. | | ||
`ignore_failure` | Optional | If set to `true`, failures are ignored. Default is `false`. | | ||
`ignore_missing` | Optional | If set to `true`, the processor does not modify the document if the field does not exist or is `null`. Default is `false`. | | ||
`on_failure` | Optional | A list of processors to run if the processor fails. | | ||
`tag` | Optional | An identifier tag for the processor. Useful for debugging to distinguish between processors of the same type. | | ||
|
||
## Creating a pipeline | ||
|
||
The following steps guide you through creating an [ingest pipeline]({{site.url}}{{site.baseurl}}/ingest-pipelines/index/) with the `grok` processor. | ||
|
||
**Step 1: Create a pipeline.** | ||
|
||
The following query creates a pipeline, named `log_line`. It extracts fields from the `message` field of the document using the specified pattern. In this case, it extracts the `clientip`, `timestamp`, and `response_status` fields: | ||
|
||
```json | ||
PUT _ingest/pipeline/log_line | ||
{ | ||
"description": "Extract fields from a log line", | ||
"processors": [ | ||
{ | ||
"grok": { | ||
"field": "message", | ||
"patterns": ["%{IPORHOST:clientip} %{HTTPDATE:timestamp} %{NUMBER:response_status:int}"] | ||
} | ||
} | ||
] | ||
} | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
**Step 2 (Optional): Test the pipeline.** | ||
|
||
{::nomarkdown}<img src="{{site.url}}{{site.baseurl}}/images/icons/alert-icon.png" class="inline-icon" alt="alert icon"/>{:/} **NOTE**<br>It is recommended that you test your pipeline before you ingest documents. | ||
{: .note} | ||
|
||
To test the pipeline, run the following query: | ||
|
||
```json | ||
POST _ingest/pipeline/log_line/_simulate | ||
{ | ||
"docs": [ | ||
{ | ||
"_source": { | ||
"message": "127.0.0.1 198.126.12 10/Oct/2000:13:55:36 -0700 200" | ||
} | ||
} | ||
] | ||
} | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
#### Response | ||
|
||
The following response confirms that the pipeline is working as expected: | ||
|
||
```json | ||
{ | ||
"docs": [ | ||
{ | ||
"doc": { | ||
"_index": "_index", | ||
"_id": "_id", | ||
"_source": { | ||
"message": "127.0.0.1 198.126.12 10/Oct/2000:13:55:36 -0700 200", | ||
"response_status": 200, | ||
"clientip": "198.126.12", | ||
"timestamp": "10/Oct/2000:13:55:36 -0700" | ||
}, | ||
"_ingest": { | ||
"timestamp": "2023-09-13T21:41:52.064540505Z" | ||
} | ||
} | ||
} | ||
] | ||
} | ||
``` | ||
|
||
**Step 3: Ingest a document.** | ||
|
||
The following query ingests a document into an index named `testindex1`: | ||
|
||
```json | ||
PUT testindex1/_doc/1?pipeline=log_line | ||
{ | ||
"message": "127.0.0.1 198.126.12 10/Oct/2000:13:55:36 -0700 200" | ||
} | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
**Step 4 (Optional): Retrieve the document.** | ||
|
||
To retrieve the document, run the following query: | ||
|
||
```json | ||
GET testindex1/_doc/1 | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
## Custom patterns | ||
|
||
You can use default patterns, or you can add custom patterns to your pipelines using the `patterns_definitions` parameter. Custom grok patterns can be used in a pipeline to extract structured data from log messages that do not match the built-in grok patterns. This can be useful for parsing log messages from custom applications or for parsing log messages that have been modified in some way. Custom patterns adhere to a straightforward structure: each pattern has a unique name and the corresponding regular expression that defines its matching behavior. | ||
|
||
The following is an example of how to include a custom pattern in your configuration. In this example, the issue number is between 3 and 4 digits and is parsed into the `issue_number` field and the status is parsed into the `status` field: | ||
|
||
```json | ||
PUT _ingest/pipeline/log_line | ||
{ | ||
"processors": [ | ||
{ | ||
"grok": { | ||
"field": "message", | ||
"patterns": ["The issue number %{NUMBER:issue_number} is %{STATUS:status}"], | ||
"pattern_definitions" : { | ||
"NUMBER" : "\\d{3,4}", | ||
"STATUS" : "open|closed" | ||
} | ||
} | ||
} | ||
] | ||
} | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
## Tracing which patterns matched | ||
|
||
To trace which patterns matched and populated the fields, you can use the `trace_match` parameter. The following is an example of how to include this parameter in your configuration: | ||
|
||
```json | ||
PUT _ingest/pipeline/log_line | ||
{ | ||
"description": "Extract fields from a log line", | ||
"processors": [ | ||
{ | ||
"grok": { | ||
"field": "message", | ||
"patterns": ["%{HTTPDATE:timestamp} %{IPORHOST:clientip}", "%{IPORHOST:clientip} %{HTTPDATE:timestamp} %{NUMBER:response_status:int}"], | ||
"trace_match": true | ||
} | ||
} | ||
] | ||
} | ||
``` | ||
{% include copy-curl.html %} | ||
|
||
When you simulate the pipeline, OpenSearch returns the `_ingest` metadata that includes the `grok_match_index`, as shown in the following output: | ||
|
||
```json | ||
{ | ||
"docs": [ | ||
{ | ||
"doc": { | ||
"_index": "_index", | ||
"_id": "_id", | ||
"_source": { | ||
"message": "127.0.0.1 198.126.12 10/Oct/2000:13:55:36 -0700 200", | ||
"response_status": 200, | ||
"clientip": "198.126.12", | ||
"timestamp": "10/Oct/2000:13:55:36 -0700" | ||
}, | ||
"_ingest": { | ||
"_grok_match_index": "1", | ||
"timestamp": "2023-11-02T18:48:40.455619084Z" | ||
} | ||
} | ||
} | ||
] | ||
} | ||
``` | ||
|