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Run Nifi Connector using the CLI /connectors/pipeline/nifi/cli

Run Nifi using the metadata CLI

In this section, we provide guides and references to use the Nifi connector.

Configure and schedule Nifi metadata and profiler workflows from the OpenMetadata UI:

Requirements

{%inlineCallout icon="description" bold="OpenMetadata 0.12 or later" href="/deployment"%} To deploy OpenMetadata, check the Deployment guides. {% /inlineCallout %}

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.

Python Requirements

To run the Nifi ingestion, you will need to install:

pip3 install "openmetadata-ingestion[nifi]"

Metadata Ingestion

All connectors are defined as JSON Schemas. Here you can find the structure to create a connection to Nifi.

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 Nifi:

{% codePreview %}

{% codeInfoContainer %}

Source Configuration - Service Connection

{% codeInfo srNumber=1 %}

hostPort: Pipeline Service Management UI URL nifiConfig: one of 1. Using Basic authentication
- username: Username to connect to Nifi. This user should be able to send request to the Nifi API and access the Resources endpoint. - password: Password to connect to Nifi. - verifySSL: Whether SSL verification should be perform when authenticating. 2. Using client certificate authentication - certificateAuthorityPath: Path to the certificate authority (CA) file. This is the certificate used to store and issue your digital certificate. This is an optional parameter. If omitted SSL verification will be skipped; this can present some sever security issue. important: This file should be accessible from where the ingestion workflow is running. For example, if you are using OpenMetadata Ingestion Docker container, this file should be in this container. - clientCertificatePath: Path to the certificate client file. important: This file should be accessible from where the ingestion workflow is running. For example, if you are using OpenMetadata Ingestion Docker container, this file should be in this container. - clientkeyPath: Path to the client key file. important: This file should be accessible from where the ingestion workflow is running. For example, if you are using OpenMetadata Ingestion Docker container, this file should be in this container.

{% /codeInfo %}

Source Configuration - Source Config

{% codeInfo srNumber=2 %}

The sourceConfig is defined here:

dbServiceNames: Database Service Name for the creation of lineage, if the source supports it.

includeTags: Set the 'Include Tags' toggle to control whether to include tags as part of metadata ingestion.

markDeletedPipelines: Set the Mark Deleted Pipelines toggle to flag pipelines as soft-deleted if they are not present anymore in the source system.

pipelineFilterPattern and chartFilterPattern: Note that the pipelineFilterPattern and chartFilterPattern both support regex as include or exclude.

{% /codeInfo %}

Sink Configuration

{% codeInfo srNumber=3 %}

To send the metadata to OpenMetadata, it needs to be specified as type: metadata-rest.

{% /codeInfo %}

{% partial file="workflow-config.md" /%}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}

source:
  type: nifi
  serviceName: nifi_source
  serviceConnection:
    config:
      type: Nifi
      hostPort: my_host:8433
      nifiConfig:
        username: my_username
        password: my_password
        verifySSL: <true or false>
        ## client certificate authentication
        # certificateAuthorityPath: path/to/CA
        # clientCertificatePath: path/to/clientCertificate
        # clientkeyPath: path/to/clientKey
      hostPort: http://localhost:8000
  sourceConfig:
    config:
      type: PipelineMetadata
      # markDeletedPipelines: True
      # includeTags: True
      # includeLineage: true
      # pipelineFilterPattern:
      #   includes:
      #     - pipeline1
      #     - pipeline2
      #   excludes:
      #     - pipeline3
      #     - pipeline4
sink:
  type: metadata-rest
  config: {}

{% partial file="workflow-config-yaml.md" /%}

{% /codeBlock %}

{% /codePreview %}

2. Run with the CLI

First, we will need to save the YAML file. Afterward, and with all requirements installed, we can run:

metadata ingest -c <path-to-yaml>

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.