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DataHub

DataHub Rest

For context on getting started with ingestion, check out our metadata ingestion guide.

Setup

To install this plugin, run pip install 'acryl-datahub[datahub-rest]'.

Capabilities

Pushes metadata to DataHub using the GMS REST API. The advantage of the REST-based interface is that any errors can immediately be reported.

Quickstart recipe

Check out the following recipe to get started with ingestion! See below for full configuration options.

For general pointers on writing and running a recipe, see our main recipe guide.

source:
  # source configs
sink:
  type: "datahub-rest"
  config:
    server: "http://localhost:8080"

Config details

Note that a . is used to denote nested fields in the YAML recipe.

Field Required Default Description
server ✅ URL of DataHub GMS endpoint.
timeout_sec 30 Per-HTTP request timeout.
token Bearer token used for authentication.
extra_headers Extra headers which will be added to the request.
max_threads 1 Experimental: Max parallelism for REST API calls

DataHub Kafka

For context on getting started with ingestion, check out our metadata ingestion guide.

Setup

To install this plugin, run pip install 'acryl-datahub[datahub-kafka]'.

Capabilities

Pushes metadata to DataHub by publishing messages to Kafka. The advantage of the Kafka-based interface is that it's asynchronous and can handle higher throughput.

Quickstart recipe

Check out the following recipe to get started with ingestion! See below for full configuration options.

For general pointers on writing and running a recipe, see our main recipe guide.

source:
  # source configs

sink:
  type: "datahub-kafka"
  config:
    connection:
      bootstrap: "localhost:9092"
      schema_registry_url: "http://localhost:8081"

Config details

Note that a . is used to denote nested fields in the YAML recipe.

Field Required Default Description
connection.bootstrap ✅ Kafka bootstrap URL.
connection.producer_config.<option> Passed to https://docs.confluent.io/platform/current/clients/confluent-kafka-python/html/index.html#confluent_kafka.SerializingProducer
connection.schema_registry_url ✅ URL of schema registry being used.
connection.schema_registry_config.<option> Passed to https://docs.confluent.io/platform/current/clients/confluent-kafka-python/html/index.html#confluent_kafka.schema_registry.SchemaRegistryClient

The options in the producer config and schema registry config are passed to the Kafka SerializingProducer and SchemaRegistryClient respectively.

For a full example with a number of security options, see this example recipe.

Questions

If you've got any questions on configuring this sink, feel free to ping us on our Slack!