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13be70e416
* updated documentation * addressing pyline findings * addressing pyline findings * doc update Co-authored-by: parthp2107 <parth@getcollate.io>
1.6 KiB
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 or Source
{% tabs %} {% tab title="Install Using PyPI" %}
pip install 'openmetadata-ingestion[elasticsearch]'
{% endtab %} {% endtabs %}
Run Manually
metadata ingest -c ./pipelines/metadata_to_es.json
Configuration
{% code title="metadata_to_es.json" %}
{
"source": {
"type": "metadata_es",
"config": {}
},
...
{% endcode %}
Publish to OpenMetadata
Below is the configuration to publish Elastic Search data into the OpenMetadata service.
Add Optionally file stage and elasticsearch bulk_sink along with metadata-server config
{% code title="metadata_to_es.json" %}
{
"source": {
"type": "metadata_es",
"config": {}
},
"stage": {
"type": "file",
"config": {
"filename": "/tmp/tables.txt"
}
},
"bulk_sink": {
"type": "elasticsearch",
"config": {
"filename": "/tmp/tables.txt",
"es_host_port": "localhost",
"index_name": "table_search_index"
}
},
"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 %}