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1.6 KiB
| description |
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| This guide will help install ElasticSearch connector and run manually to index the metadata stored in OpenMetadata. |
ElasticSearch
{% hint style="info" %} Prerequisites
OpenMetadata is built using Java, DropWizard, Jetty, and MySQL.
- Python 3.7 or above {% endhint %}
Install from PyPI
{% tabs %} {% tab title="Install Using PyPI" %}
pip install 'openmetadata-ingestion[elasticsearch]'
{% endtab %} {% endtabs %}
Run Manually
metadata ingest -c ./examples/workflows/metadata_to_es.json
Configuration
{% code title="metadata_to_es.json" %}
"sink": {
"type": "elasticsearch",
"config": {
"index_tables": "true",
"index_topics": "true",
"index_dashboards": "true",
"es_host": "localhost",
"es_port": 9200
}
...
{% endcode %}
Publish to OpenMetadata
Below is the configuration to publish Elastic Search data into the OpenMetadata service.
{% code title="metadata_to_es.json" %}
{
"source": {
"type": "metadata",
"config": {
"include_tables": "true",
"include_topics": "true",
"include_dashboards": "true",
"limit_records": 10
}
},
"sink": {
"type": "elasticsearch",
"config": {
"index_tables": "true",
"index_topics": "true",
"index_dashboards": "true",
"es_host": "localhost",
"es_port": 9200
}
},
"metadata_server": {
"type": "metadata-server",
"config": {
"api_endpoint": "http://localhost:8585/api",
"auth_provider_type": "no-auth"
}
}
}
{% endcode %}