Operator Market
Manage and use DataMate operators
Operator marketplace provides rich data processing operators and supports custom operator development.
Features Overview
Operator marketplace provides:
- Built-in Operators: Rich built-in data processing operators
- Operator Publishing: Publish and share custom operators
- Operator Installation: Install third-party operators
- Custom Development: Develop custom operators
Built-in Operators
Data Cleaning Operators
| Operator | Function | Input | Output |
|---|---|---|---|
| Deduplication | Remove duplicates | Dataset | Deduplicated data |
| Null Handler | Handle nulls | Dataset | Filled data |
| Format Converter | Convert format | Original format | New format |
Text Processing Operators
| Operator | Function |
|---|---|
| Text Segmentation | Chinese word segmentation |
| Remove Stopwords | Remove common stopwords |
| Text Cleaning | Clean special characters |
Quick Start
1. Browse Operators
Step 1: Enter Operator Market
Select Operator Market in the left navigation.
Step 2: Browse Operators
View all available operators with ratings and installation counts.
2. Install Operator
Install Built-in Operator
Built-in operators are installed by default.
Install Third-party Operator
- In operator details page, click Install
- Wait for installation completion
3. Use Operator
After installation, use in:
- Data Cleaning: Add operator node to cleaning pipeline
- Pipeline Orchestration: Add operator node to workflow
Advanced Features
Develop Custom Operator
Create Operator
- In operator market page, click Create Operator
- Fill operator information
- Write operator code (Python)
- Package and publish
Python Operator Example:
class MyTextCleaner:
def __init__(self, config):
self.remove_special_chars = config.get('remove_special_chars', True)
def process(self, data):
if isinstance(data, str):
result = data
if self.remove_special_chars:
import re
result = re.sub(r'[^\w\s]', '', result)
return result
return data
Best Practices
1. Operator Design
Good operator design:
- Single responsibility: One operator does one thing
- Configurable: Rich configuration options
- Error handling: Comprehensive error handling
- Performance: Consider large-scale data
Common Questions
Q: Operator execution failed?
A: Troubleshoot:
- View logs
- Check configuration
- Check data format
- Test locally
Related Documentation
- Data Cleaning - Use operators for cleaning
- Pipeline Orchestration - Use operators in pipelines
Feedback
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.