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# DataHub
## DataHub Rest
For context on getting started with ingestion, check out our [metadata ingestion guide](../README.md).
### 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](#config-details) for full configuration options.
For general pointers on writing and running a recipe, see our [main recipe guide](../README.md#recipes). This should point to the GMS server.
```yml
source:
# source configs
sink:
type: "datahub-rest"
config:
server: "http://localhost:8080"
```
If you are connecting to a hosted DataHub Cloud instance, your sink will look like
```yml
source:
# source configs
sink:
type: "datahub-rest"
config:
server: "https://<your-instance>.acryl.io/gms"
token: <token>
```
If you are running the ingestion in a container in docker and your [GMS is also running in docker](../../docker/README.md) then you should use the internal docker hostname of the GMS pod. Usually it would look something like
```yml
source:
# source configs
sink:
type: "datahub-rest"
config:
server: "http://datahub-gms:8080"
```
If GMS is running in a kubernetes pod [deployed through the helm charts](../../docs/deploy/kubernetes.md) and you are trying to connect to it from within the kubernetes cluster then you should use the Kubernetes service name of GMS. Usually it would look something like
```yml
source:
# source configs
sink:
type: "datahub-rest"
config:
server: "http://datahub-datahub-gms.datahub.svc.cluster.local:8080"
```
If you are using [UI based ingestion](../../docs/ui-ingestion.md) then where GMS is deployed decides what hostname you should use.
### 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. |
| `token` | | | Bearer token used for authentication. |
| `timeout_sec` | | 30 | Per-HTTP request timeout. |
| `retry_max_times` | | 1 | Maximum times to retry if HTTP request fails. The delay between retries is increased exponentially |
| `retry_status_codes` | | [429, 502, 503, 504] | Retry HTTP request also on these status codes |
| `extra_headers` | | | Extra headers which will be added to the request. |
| `max_threads` | | `15` | Max parallelism for REST API calls |
| `mode` | | `ASYNC_BATCH` | [Advanced] Mode of operation - `SYNC`, `ASYNC`, or `ASYNC_BATCH` |
| `ca_certificate_path` | | | Path to server's CA certificate for verification of HTTPS communications |
| `client_certificate_path` | | | Path to client's CA certificate for HTTPS communications |
| `disable_ssl_verification` | | false | Disable ssl certificate validation |
## DataHub Kafka
For context on getting started with ingestion, check out our [metadata ingestion guide](../README.md).
### 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](#config-details) for full configuration options.
For general pointers on writing and running a recipe, see our [main recipe guide](../README.md#recipes).
```yml
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 |
| `topic_routes.MetadataChangeEvent` | | MetadataChangeEvent | Overridden Kafka topic name for the MetadataChangeEvent |
| `topic_routes.MetadataChangeProposal` | | MetadataChangeProposal | Overridden Kafka topic name for the MetadataChangeProposal |
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](../examples/recipes/secured_kafka.dhub.yaml).
## DataHub Lite (experimental)
A sink that provides integration with [DataHub Lite](../../docs/datahub_lite.md) for local metadata exploration and serving.
### Setup
To install this plugin, run `pip install 'acryl-datahub[datahub-lite]'`.
### Capabilities
Pushes metadata to a local DataHub Lite instance.
### Quickstart recipe
Check out the following recipe to get started with ingestion! See [below](#config-details) for full configuration options.
For general pointers on writing and running a recipe, see our [main recipe guide](../README.md#recipes).
```yml
source:
# source configs
sink:
type: "datahub-lite"
```
By default, `datahub-lite` uses a **DuckDB** database and will write to a database file located under **~/.datahub/lite/**.
To configure the location, you can specify it directly in the config:
```yml
source:
# source configs
sink:
type: "datahub-lite"
config:
type: "duckdb"
config:
file: "<path_to_duckdb_file>"
```
:::note
DataHub Lite currently doesn't support stateful ingestion, so you'll have to turn off stateful ingestion in your recipe to use it. This will be fixed shortly.
:::
### Config details
Note that a `.` is used to denote nested fields in the YAML recipe.
| Field | Required | Default | Description |
| -------- | -------- | -------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
| `type` | | duckdb | Type of DataHub Lite implementation to use |
| `config` | | `{"file": "~/.datahub/lite/datahub.duckdb"}` | Config dictionary to pass through to the DataHub Lite implementation. See below for fields accepted by the DuckDB implementation |
#### DuckDB Config Details
| Field | Required | Default | Description |
| --------- | -------- | ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| `file` | | `"~/.datahub/lite/datahub.duckdb"` | File to use for DuckDB storage |
| `options` | | `{}` | Options dictionary to pass through to DuckDB library. See [the official spec](https://duckdb.org/docs/sql/configuration.html) for the options supported by DuckDB. |