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* updated documentation * addressing pyline findings * addressing pyline findings * doc update Co-authored-by: parthp2107 <parth@getcollate.io>
2.1 KiB
2.1 KiB
| description |
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| This guide will help install Kafka connector and run manually |
Kafka
{% hint style="info" %} Prerequisites
OpenMetadata is built using Java, DropWizard, Jetty, and MySQL.
- Python 3.7 or above {% endhint %}
Install from PyPI or Source
{% tabs %} {% tab title="Install Using PyPI" %}
pip install 'openmetadata-ingestion[kafka]'
python -m spacy download en_core_web_sm
{% endtab %} {% endtabs %}
Run Manually
metadata ingest -c ./pipelines/confluent_kafka.json
Configuration
{% code title="confluent_kafka.json" %}
{
"source": {
"type": "kafka",
"config": {
"service_name": "local_kafka",
"bootstrap_servers": "192.168.1.32:9092",
"schema_registry_url": "http://192.168.1.32:8081",
"filter_pattern": {
"excludes": ["_confluent.*"]
}
}
},
...
{% endcode %}
- service_name - Service Name for this Kafka cluster. If you added Kafka cluster through OpenMetadata UI, make sure the service name matches the same.
- filter_pattern - It contains includes, excludes options to choose which pattern of datasets you want to ingest into OpenMetadata
Publish to OpenMetadata
Below is the configuration to publish Kafka data into the OpenMetadata service.
Add optionally pii processor and metadata-rest-tables sink along with metadata-server config
{% code title="confluent_kafka.json" %}
{
"source": {
"type": "kafka",
"config": {
"service_name": "local_kafka",
"bootstrap_servers": "192.168.1.32:9092",
"schema_registry_url": "http://192.168.1.32:8081",
"filter_pattern": {
"excludes": ["_confluent.*"]
}
}
},
"sink": {
"type": "metadata-rest",
"config": {
}
},
"metadata_server": {
"type": "metadata-server",
"config": {
"api_endpoint": "http://localhost:8585/api",
"auth_provider_type": "no-auth"
}
},
"cron": {
"minute": "*/5",
"hour": null,
"day": null,
"month": null,
"day_of_week": null
}
}
{% endcode %}