Saving MCPs to a File
What is an MCP?
A MetadataChangeProposal
(MCP) represents an atomic unit of change in the DataHub Metadata Graph. Each MCP carries a single aspect in its payload and is used to propose changes to DataHub's metadata.
- Represents a single aspect change
- Used for proposing metadata changes to DataHub
- Serves as the basic building block for metadata ingestion
For more information, please see guides on DataHub Metadata Events and MCPs.
Why Write MCPs as Files?
MCPs in JSON file format are particularly valuable because they represent the lowest and most granular form of events in DataHub. There are two main use cases for using previously saved MCP files:
Testing
MCPs allow you to easily ingest metadata. You can:
- Use it for entity ingestion by running a simple command, without a dependency on a ingestion connector:
datahub ingest mcps <file_name>.json
- Create reproducible test cases for metadata ingestion
- Write and run tests when contributing to DataHub (see DataHub Testing Guide for more details)
Debugging
MCPs are valuable for debugging because they let you:
- Examine entities in your DataHub instance at a granular level
- Export existing entities to MCP files for analysis
- Verify entity structures and relationships before ingestion
For example, if you want to understand the structure of entities in your DataHub instance, you can emit them as MCP files and examine their contents in detail.
Saving MCPs to a file
Exporting rom DataHub Instance
You can export MCPs directly from your DataHub instance using a recipe file. This is useful when you want to:
- Examine existing entities in your DataHub instance
- Create test cases based on real data
- Debug entity relationships
First, create a recipe file (e.g., export_mcps.yaml
):
source:
type: datahub
config:
# Add your DataHub connection configuration here
server: "http://localhost:8080"
token: "your-access-token" # If authentication is required
sink:
type: "file"
config:
filename: "mcps.json"
Run the ingestion:
datahub ingest -c export_mcps.yaml
This will write all the entities from your DataHub instance to mcps.json
in MCP format.
Creating MCPs with Python SDK
You can use the write_metadata_file
helper to generate MCPs programmatically:
from datahub.ingestion.sink.file import write_metadata_file
from pathlib import Path
from datahub.metadata.schema_classes import DatasetPropertiesClass
from datahub.emitter.mcp import MetadataChangeProposalWrapper
records = [
MetadataChangeProposalWrapper(
entityType="dataset",
entityUrn="urn:li:dataset:(urn:li:dataPlatform:hive,example_dataset,PROD)",
changeType="UPSERT",
aspectName="datasetProperties",
aspect=DatasetPropertiesClass(
description="Example dataset description",
customProperties={"encoding": "utf-8"}
))
]
write_metadata_file(
file=Path("mcps.json"),
records=records,
)
Edit records
to create the event and entities for your needs.
Run the Python script to generate your defined MCPs and save them to a file:
python <file_name>.py
For example, the above script will generate an MCP file with a single dataset entity.
[
{
"entityType": "dataset",
"entityUrn": "urn:li:dataset:(urn:li:dataPlatform:hive,example_dataset,PROD)",
"changeType": "UPSERT",
"aspectName": "datasetProperties",
"aspect": {
"json": {
"customProperties": {
"encoding": "utf-8"
},
"description": "Example dataset description",
"tags": []
}
}
}
]