In this section, we provide guides and references to use the Elasticsearch connector.
Configure and schedule Elasticsearch metadata and profiler workflows from the OpenMetadata UI:
How to Run the Connector Externally
To run the Ingestion via the UI you'll need to use the OpenMetadata Ingestion Container, which comes shipped with custom Airflow plugins to handle the workflow deployment.
If, instead, you want to manage your workflows externally on your preferred orchestrator, you can check the following docs to run the Ingestion Framework anywhere.
Requirements
We support Elasticsearch 7.0 and above.
We extract Elasticsearch's metadata by using its API. To run this ingestion, you just need a user with permissions to the ElasticSearch instance.
Python Requirements
We have support for Python versions 3.8-3.11
To run the Elasticsearch ingestion, you will need to install:
Metadata Ingestion
All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to ElasticSearch.
In order to create and run a Metadata Ingestion workflow, we will follow the steps to create a YAML configuration able to connect to the source, process the Entities if needed, and reach the OpenMetadata server.
The workflow is modeled around the following JSON Schema
1. Define the YAML Config
This is a sample config for Elasticsearch:
Source Configuration - Service Connection
hostPort: This parameter specifies the host and port of the Elasticsearch instance. This should be specified as a URI string in the format http://hostname:port or https://hostname:port. For example, you might set it to https://localhost:9200.
Basic Authentication
username: Username to connect to Elasticsearch required when Basic Authentication is enabled on Elasticsearch. password: Password of the user account to connect with Elasticsearch.
API Key Authentication
apiKey: API Key to connect to Elasticsearch required when API Key Authentication is enabled on Elasticsearch. apiKeyId: Enter API Key ID In case of API Key Authentication if there is any API Key ID associated with the API Key, otherwise this field can be left blank or skipped.
sslConfig:
- SSL Certificates By Path
- caCertPath: This field specifies the path of CA certificate required for authentication.
- clientCertPath: This field specifies the path of Clint certificate required for authentication.
- privateKeyPath: This field specifies the path of Clint Key/Private Key required for authentication.
- SSL Certificates By Value
- caCertValue: This field specifies the value of CA certificate required for authentication.
- clientCertValue: This field specifies the value of Clint certificate required for authentication.
- privateKeyValue: This field specifies the value of Clint Key/Private Key required for authentication.
- stagingDir: This field specifies the path to temporary staging directory, where the certificates will be stored temporarily during the ingestion process, which will de deleted once the ingestion job is over.
- when you are using this approach make sure you are passing the key in a correct format. If your certificate looks like this:
You will have to replace new lines with
\nand the final value that you need to pass should look like this:
connectionTimeoutSecs: Connection timeout configuration for communicating with Elasticsearch APIs.
Source Configuration - Source Config
The sourceConfig is defined here:
includeSampleData: Set the Ingest Sample Data toggle to control whether to ingest sample data as part of metadata ingestion.
sampleSize: If include sample data is enabled, 10 records will be ingested by default. Using this field you can customize the size of sample data.
markDeletedSearchIndexes: Optional configuration to soft delete search indexes in OpenMetadata if the source search indexes are deleted. After deleting, all the associated entities like lineage, etc., with that search index will be deleted.
searchIndexFilterPattern: Note that the searchIndexFilterPattern support regex to include or exclude search indexes during metadata ingestion process.
Sink Configuration
To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.
Workflow Configuration
The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.
Logger Level
You can specify the loggerLevel depending on your needs. If you are trying to troubleshoot an ingestion, running with DEBUG will give you far more traces for identifying issues.
JWT Token
JWT tokens will allow your clients to authenticate against the OpenMetadata server. To enable JWT Tokens, you will get more details here.
You can refer to the JWT Troubleshooting section link for any issues in your JWT configuration.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
Store Service Connection
If set to true (default), we will store the sensitive information either encrypted via the Fernet Key in the database or externally, if you have configured any Secrets Manager.
If set to false, the service will be created, but the service connection information will only be used by the Ingestion Framework at runtime, and won't be sent to the OpenMetadata server.
SSL Configuration
If you have added SSL to the OpenMetadata server, then you will need to handle the certificates when running the ingestion too. You can either set verifySSL to ignore, or have it as validate, which will require you to set the sslConfig.caCertificate with a local path where your ingestion runs that points to the server certificate file.
Find more information on how to troubleshoot SSL issues here.
2. Run with the CLI
First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:
Note that from connector to connector, this recipe will always be the same. By updating the YAML configuration, you will be able to extract metadata from different sources.