JarCastingKafka Connect Grok Transformation
Description
The Apache Kafka® SMT io.streamthoughts.kafka.connect.transform.Grok allows parsing unstructured data text into a data Struct from the entire key or value using a Grok expression.
Installation
Grok SMT can be installed using the Confluent Hub Client with:
-
Download the distribution ZIP file for the latest available version.
export VERSION=1.1.0 export GITHUB_HUB_REPO=https://github.com/streamthoughts/kafka-connect-transform-grok $ curl -sSL $GITHUB_HUB_REPO/releases/download/v$VERSION/streamthoughts-kafka-connect-transform-grok-$VERSION.zip
-
Use the
confluent-hubCLI for installing it.$ confluent-hub install streamthoughts-kafka-connect-transform-grok-$VERSION.zip
Alternatively, you can extract the ZIP file into one of the directories that is listed on the plugin.path worker configuration property.
Grok Basics
The syntax for a grok pattern is %{SYNTAX:SEMANTIC} or %{SYNTAX:SEMANTIC:TYPE}
The SYNTAX is the name of the pattern that should match the input text value.
The SEMANTIC is the field name for the data field that will contain the piece of text being matched.
The TYPE is the target type to which the data field must be converted.
- Supported types are:
-
-
SHORT -
INTEGER -
LONG -
FLOAT -
DOUBLE -
BOOLEAN -
STRING
-
The Kafka Connect Grok Transformer ships with a lot of reusable grok patterns. See the complete list of patterns.
Debugging Gook Expression
You can build and debug your patterns using the useful online tools: Grok Debug and Grok Constructor.
Regular Expressions
Grok sits on top of regular expressions, so any regular expressions are valid in grok as well.
The Grok SMT uses the regular expression Joni library which is the Java port of Oniguruma regexp library used by the Elastic stack (i.e Logstash).
Custom Patterns
Sometimes, the patterns provided by the Grok SMT will not be sufficient to match your data. Therefore, you have a few options to define custom patterns.
- Option #1
-
You can use the Oniguruma syntax for named capture which allows you to match a piece of text and capture it as a field:
(?<field_name>the regex pattern)For example, if you need to capture parts of an email we can you the following pattern :
(?<EMAILADDRESS>(?<EMAILLOCALPART>^[A-Z0-9._%+-]+)(?<HOSTNAME>@[A-Z0-9.-]+\.[A-Z]{2,6})$)- Configuration
transforms=Grok
transforms.Grok.type=io.streamthoughts.kafka.connect.transform.Grok$Value
transforms.Grok.pattern=(?<EMAILADDRESS>(?<EMAILLOCALPART>[A-Za-z0-9._%+-]+)@(?<HOSTNAME>[A-Za-z0-9.-]+\\.[A-Za-z]{2,6}))
Note: The pattern EMAILADDRESS is already provided by the Grok SMT.
- Option #2
-
You can create a custom patterns file that will loaded the first time the Grok SMT is used :
- For example, defining the pattern needed to parse NGINX access logs
-
-
Create a directory (e.g.
grok-patterns) with a file in it callednginx. -
Then, write the pattern you need in that file as:
<the pattern name><a space><the regexp for that pattern>.
-
$ mkdir ./grok-patterns
$ cat <<EOF > ./grok-patterns/nginx
NGINX_ACCESS %{IPORHOST:remote_addr} - %{USERNAME:remote_user} \[%{HTTPDATE:time_local}\] \"%{DATA:request}\" %{INT:status} %{NUMBER:bytes_sent} \"%{DATA:http_referer}\" \"%{DATA:http_user_agent}\"
EOF
- Configuration
transforms=Grok
transforms.Grok.type=io.streamthoughts.kafka.connect.transform.Grok$Value
transforms.Grok.pattern=%{NGINX_ACCESS}
transforms.Grok.patternsDir=/tmp/grok-patterns
Grok Configuration
| Property | Description | Type | Importance | Default |
|---|---|---|---|---|
|
If true break on the first successful matching. Otherwise |
the transformation will try all configured grok patterns |
|
|
|
The grok expression to match and extract named captures (i.e data fields) with. |
|
High |
- |
|
An ordered list of grok expression to match and extract named captures (i.e data fields) with. |
|
High |
- |
|
Custom pattern definitions |
|
Low |
- |
|
List of user-defined pattern directories |
|
Low |
- |
|
If true then only store named captures from grok |
|
Medium |
|
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Contributions
Any feedback, bug reports and PRs are greatly appreciated!
About
Originally, most of the source code used by the Apache Kafka® SMT io.streamthoughts.kafka.connect.transform.Grok was developed within the Kafka Connect File Pulse connector plugin.
Licence
Copyright 2020-2021 StreamThoughts.
Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
