Python SDK for Lineage
In this guide, we will use the Python SDK to create and fetch Lineage information.
For simplicity, we are going to create lineage between Tables. However, this would work with ANY entity.
You can find the Lineage Entity defined here, as well as the Entity defining the payload to add a new lineage: AddLineage.
Note that in OpenMetadata, the Lineage information is just a possible relationship between Entities. Other types of relationships for example could be:
- Contains (a Database contains Schemas, which at the same time contain Tables),
- or Ownership of any asset.
The point being, any Entity existent in OpenMetadata can be related to any other via Lineage.
In the following sections we will:
- Create a Database Service, a Database, a Schema and two Tables,
- Add Lineage between both Tables,
- Get the Lineage information back.
A prerequisite for this section is to have previously gone through the following docs.
Creating the Entities
To prepare the necessary ingredients, execute the following steps.
All functions that we are going to use related to Lineage can be found in here
1. Preparing the Client
2. Creating the Database Service
We are mocking a MySQL instance. Note how we need to pass the right configuration class MysqlConnection
, as a parameter for the generic DatabaseConnection
type.
3. Creating the Database
Any Entity that is created and linked to another Entity, has to hold the fullyQualifiedName
to the Entity it relates to. In this case, a Database is bound to a specific service.
4. Creating the Schema
The same happens with the Schemas. They are related to a Database.
5. Creating the Tables
And finally, Tables are contained in a specific Schema, so we use the fullyQualifiedName
here as well.
We are doing a simple example with a single column.
6. Adding Lineage
With everything prepared, we can now create the Lineage between both Entities. An AddLineageRequest
type represents the edge between two Entities, typed under EntitiesEdge
.
The Python client will already return us a JSON object with the Lineage information about the fromEntity
node we added:
If the node were to have other edges already, they would be showing up here.
If we validate the Lineage from the UI, we will see:
![simple-lineage](/images/v1.6/sdk/python/ingestion/lineage/simple-lineage.png)
7. Fetching Lineage
Finally, let's fetch the lineage from the other node involved:
Which will give us the symmetric results from above
You can also get lineage by ID using the get_lineage_by_id
method, which accepts entity_id
instead of fqn
.
Lineage Details
Note how when adding lineage information we give to the API an AddLineage Request. This is composed of an Entity Edge, whose definition you can find here.
In a nutshell, an Entity Edge has:
- The Entity Reference as the lineage origin,
- The Entity Reference as the lineage destination,
- Optionally, Lineage Details.
In the Lineage Details property we can pass further information specific about Table to Table lineage:
sqlQuery
specifying the transformation,- An array of
columnsLineage
as an object with an array of source and destination columns, as well as their own specific transformation function, - Optionally, the Entity Reference of a Pipeline powering the transformation from Table A to Table B.
The API call will be exactly the same as before, but now we will add more ingredients when defining our objects. Let's see how to do that and play with the possible combinations:
First, import the required classes and create a new table:
Column Level Lineage
We can start by linking our columns together. For that we are going to create:
- A
ColumnLineage
object, linking our Table A column ID -> Table C column ID. Note that this can be a list! - A
LineageDetails
object, passing the column lineage and the SQL query that powers the transformation.
This information will now be reflected in the UI as well:
![lineage-col](/images/v1.6/sdk/python/ingestion/lineage/lineage-col.png)
Adding a Pipeline Reference
We can as well pass the reference to the pipeline used to create the lineage (e.g., the ETL feeding the tables).
To prepare this example, we need to start by creating the Pipeline Entity. Again, we'll need first to prepare the Pipeline Service:
With these ingredients ready, we can then follow the code above and add there a pipeline
argument as an Entity Reference:
The UI currently supports showing the column lineage information. Data about the SQL queries and the Pipeline Entities will be surfaced soon. Thanks!
Automated SQL lineage
In case you want OpenMetadata to identify the lineage based on the sql query, then you can make use of the method add_lineage_by_query
of the python SDK to parser the sql and generate the lineage in OpenMetadata.
follow the below code snippet for the example:
Above example would create a lineage between target_table
and source_table
within my_service
database service.
Automated SQL lineage via CLI
To create the automated sql lineage via CLI, you need to make sure that you have installed the openmetadata-ingestion package in your local environment using command pip install openmetadata-ingestion
.
Once that is done you will have to prepare a yaml file as follows.
- serviceName: Name of the database service which contains the table involved in query.
- query: You can specify the raw sql query within the yaml file itself.
- filePath: In case the query is too big then you can also save query in a file and pass the path to the file in this field.
- parseTimeout: Timeout for the lineage parsing process.
- workflowConfig: The main property here is the openMetadataServerConfig, where you can define the host and security provider of your OpenMetadata installation.
Once the yaml file is prepare you can run the command